diff --git a/.github/scripts/list_modified_files.py b/.github/scripts/list_modified_files.py
index c3c2260a7..7f406c0e4 100644
--- a/.github/scripts/list_modified_files.py
+++ b/.github/scripts/list_modified_files.py
@@ -8,7 +8,8 @@ def get_file_info(filepath):
     with open(filepath, 'r') as file:
         content = yaml.safe_load(file)
         tests = content.get('tests', [])
-        if tests:
+        needs_pat = content.get('needs_pat', False)
+        if tests and not needs_pat:
             num_tests = len(tests.get('run_inputs', []))
         else:
             num_tests = 0
@@ -17,7 +18,7 @@ def get_file_info(filepath):
 
 
 def process_files(files):
-    filenames = files.split()
+    filenames = files.split(",")
     return [
         {
             "file": file,
@@ -34,4 +35,4 @@ def process_files(files):
     changed_files = sys.stdin.read().strip()
     processed_files = process_files(changed_files)
     json_processed_files = json.dumps(processed_files)
-    print(f"::set-output name=processed_files::{json_processed_files}")
+    print(json_processed_files)
diff --git a/.github/workflows/build_wheels.yml b/.github/workflows/build_wheels.yml
index 86b93ac06..55e79c0ae 100644
--- a/.github/workflows/build_wheels.yml
+++ b/.github/workflows/build_wheels.yml
@@ -5,6 +5,7 @@ on:
     types: [published]
   workflow_dispatch: {}
 
+
 jobs:
   build_wheels:
     if: github.repository_owner == 'mlcommons'
diff --git a/.github/workflows/run-tests-on-modified-meta.yml b/.github/workflows/run-tests-on-modified-meta.yml
index 244b18a6f..a2f3a5fbe 100644
--- a/.github/workflows/run-tests-on-modified-meta.yml
+++ b/.github/workflows/run-tests-on-modified-meta.yml
@@ -33,7 +33,7 @@ jobs:
       run: |
         git remote add upstream ${{ github.event.pull_request.base.repo.clone_url }}
         git fetch upstream
-        changed_files=$(git diff upstream/${{ github.event.pull_request.base.ref }} --name-only)
+        changed_files=$(git diff upstream/${{ github.event.pull_request.base.ref }} --name-only | paste -sd, -)
         echo "$changed_files" | python3 .github/scripts/list_modified_files.py
 
   process_modified_files:
diff --git a/.github/workflows/test-mlc-script-features.yml b/.github/workflows/test-mlc-script-features.yml
index 8280cdf53..4570d5bdf 100644
--- a/.github/workflows/test-mlc-script-features.yml
+++ b/.github/workflows/test-mlc-script-features.yml
@@ -50,18 +50,15 @@ jobs:
         mlcr get,wkhtmltopdf --quiet
 
     - name: Test versions
-      continue-on-error: true
-      if: runner.os == 'linux'
+      if: runner.os == 'linux' && matrix.python-version == '3.8'
       run: |
         mlcr get,generic-python-lib,_package.scipy --version=1.9.3 --quiet
         test $? -eq 0 || exit $?
         mlcr get,generic-python-lib,_package.scipy --version=1.9.2 --quiet
         test $? -eq 0 || exit $?
-        mlc find cache --tags=get,generic-python-lib,_package.scipy,version-1.9.3
+        mlc find cache --tags=get,generic-python-lib,_package.scipy,version-1.9.2
         test $? -eq 0 || exit $?
-        # Need to add find cache here
-        # mlcr get,generic-python-lib,_package.scipy --version=1.9.3 --quiet --only_execute_from_cache=True
-        # test $? -eq 0 || exit 0
+       
 
     - name: Test python install from src
       run: |
@@ -94,6 +91,34 @@ jobs:
       run: |
         mlcr run,docker,container --adr.compiler.tags=gcc --docker_mlc_repo=mlcommons@mlperf-automations --docker_mlc_repo_branch=dev --image_name=mlc-script-app-image-classification-onnx-py --env.MLC_DOCKER_RUN_SCRIPT_TAGS=app,image-classification,onnx,python --env.MLC_DOCKER_IMAGE_BASE=ubuntu:22.04 --env.MLC_DOCKER_IMAGE_REPO=local --quiet
 
+  test_experiment:
+    runs-on: ${{ matrix.os }}
+    strategy:
+      fail-fast: false
+      matrix:
+        python-version: ["3.12", "3.8"]
+        os: ["ubuntu-latest", "windows-latest", "macos-latest"]
+
+    steps:
+    - uses: actions/checkout@v4
+    - name: Set up Python ${{ matrix.python-version }}
+      uses: actions/setup-python@v3
+      with:
+        python-version: ${{ matrix.python-version }}
+    - name: Configure git longpaths (Windows)
+      if: matrix.os == 'windows-latest'
+      run: |
+        git config --system core.longpaths true
+    - name: Pull MLOps repository
+      run: |
+        pip install mlcflow
+        mlc pull repo ${{ github.event.pull_request.head.repo.html_url }} --branch=${{ github.event.pull_request.head.ref }}
+
+    - name: Test mlc experiment script
+      run: |
+        mlc experiment script --tags=detect,os --quiet --exp.repeat,=1,2,3
+        mlc experiment script --tags=detect,cpu --quiet --exp.explore=2:10:2
+
   test_mlperf_retinanet_cpp_venv:
     runs-on: ubuntu-latest
     strategy:
diff --git a/.github/workflows/test-mlperf-automotive.yml b/.github/workflows/test-mlperf-automotive.yml
new file mode 100644
index 000000000..a03560dc1
--- /dev/null
+++ b/.github/workflows/test-mlperf-automotive.yml
@@ -0,0 +1,43 @@
+name: Test MLPerf automotive
+
+on:
+  pull_request_target:
+    branches: [ "main", "dev" ]
+    paths:
+      - 'script/**meta.yaml'
+
+jobs:
+  fetch-secret:
+    runs-on: ubuntu-latest
+    outputs:
+      gdrive_secret: ${{ steps.op-load-secret.outputs.GDRIVE_SERVICE_ACCOUNT_KEY }}
+    steps:
+      - name: Load secret from 1Password
+        id: op-load-secret
+        uses: 1password/load-secrets-action@v2
+        with:
+          export-env: false
+        env:
+          OP_SERVICE_ACCOUNT_TOKEN: ${{ secrets.OP_SERVICE_ACCOUNT_TOKEN }}
+          GDRIVE_SERVICE_ACCOUNT_KEY: op://7basd2jirojjckncf6qnq3azai/bzbaco3uxoqs2rcyu42rvuccga/credential
+
+  run-mlperf:
+    runs-on: ubuntu-latest
+    needs: 
+      - fetch-secret
+    steps:
+      - name: Checkout repository
+        uses: actions/checkout@v4
+        with:
+          fetch-depth: 2
+      - name: Set RCLONE Service account env var from secret
+        shell: bash
+        run: |
+          echo "::add-mask::${{ needs.fetch-secret.outputs.gdrive_secret }}"
+          echo "RCLONE_CONFIG_MLC_COGNATA_SERVICE_ACCOUNT_CREDENTIALS=${{ needs.fetch-secret.outputs.gdrive_secret }}" >> $GITHUB_ENV
+          echo "RCLONE_CONFIG_MLC_NUSCENES_SERVICE_ACCOUNT_CREDENTIALS=${{ needs.fetch-secret.outputs.gdrive_secret }}" >> $GITHUB_ENV
+      - name: Run MLPerf
+        run: |
+          pip install mlcflow
+          mlc pull repo ${{ github.event.pull_request.head.repo.html_url }} --branch=${{ github.event.pull_request.head.ref }}
+          mlc test script app,mlperf,automotive
diff --git a/automation/script/docker.py b/automation/script/docker.py
index c2f65ee5c..37fa84ab0 100644
--- a/automation/script/docker.py
+++ b/automation/script/docker.py
@@ -36,7 +36,6 @@ def dockerfile(self_module, input_params):
     state_data = input_params.get('state', {})
     constant_vars = input_params.get('const', {})
     constant_state = input_params.get('const_state', {})
-    dockerfile_env = input_params.get('dockerfile_env', {})
     tag_values = input_params.get('tags', '').split(",")
     variation_tags = [tag[1:] for tag in tag_values if tag.startswith("_")]
 
@@ -56,7 +55,6 @@ def dockerfile(self_module, input_params):
             'script_variation_tags': variation_tags
         }
         docker_settings = metadata.get('docker', {})
-        docker_settings['dockerfile_env'] = dockerfile_env
         state_data['docker'] = docker_settings
         add_deps_recursive = input_params.get('add_deps_recursive', {})
 
@@ -94,8 +92,6 @@ def dockerfile(self_module, input_params):
 
         # Set Docker-specific configurations
         docker_settings = state_data['docker']
-        docker_settings['dockerfile_env'] = dockerfile_env
-        dockerfile_env['MLC_RUN_STATE_DOCKER'] = True
 
         if not docker_settings.get('run', True) and not input_params.get(
                 'docker_run_override', False):
@@ -171,6 +167,10 @@ def dockerfile(self_module, input_params):
         if input_params.get('docker_push_image') in [True, 'True', 'yes']:
             env['MLC_DOCKER_PUSH_IMAGE'] = 'yes'
 
+        dockerfile_env = docker_inputs.get('env', {})
+        dockerfile_build_env = docker_inputs.get('build_env', {})
+
+        dockerfile_env['MLC_RUN_STATE_DOCKER'] = True
         # Generate Dockerfile
         mlc_docker_input = {
             'action': 'run', 'automation': 'script', 'tags': 'build,dockerfile',
@@ -178,6 +178,7 @@ def dockerfile(self_module, input_params):
             'comments': comments, 'run_cmd': f"{run_command_string} --quiet",
             'script_tags': input_params.get('tags'), 'env': env,
             'dockerfile_env': dockerfile_env,
+            'dockerfile_build_env': dockerfile_build_env,
             'quiet': True, 'real_run': True
         }
 
@@ -377,6 +378,9 @@ def docker_run(self_module, i):
             env.update({docker_input_mapping[key]: i[key]
                        for key in docker_input_mapping if key in i})
 
+        if docker_inputs.get('user'):
+            docker_settings['user'] = docker_inputs['user']
+
         # Handle environment variable-based mounts
         res = process_mounts(
             mounts,
@@ -412,6 +416,7 @@ def docker_run(self_module, i):
             'quiet': True, 'real_run': True, 'add_deps_recursive': {'build-docker-image': {'dockerfile': dockerfile_path}},
             **docker_inputs
         }
+
         r = self_module.action_object.access(mlc_docker_input)
         if r['return'] > 0:
             return r
diff --git a/automation/script/docker_utils.py b/automation/script/docker_utils.py
index a94e1a010..cb733f93a 100644
--- a/automation/script/docker_utils.py
+++ b/automation/script/docker_utils.py
@@ -134,7 +134,7 @@ def prepare_docker_inputs(input_params, docker_settings,
     keys = [
         "mlc_repo", "mlc_repo_branch", "base_image", "os", "os_version",
         "mlc_repos", "skip_mlc_sys_upgrade", "extra_sys_deps", "image_name",
-        "gh_token", "fake_run_deps", "run_final_cmds", "real_run", "copy_files", "path", "user"
+        "gh_token", "fake_run_deps", "run_final_cmds", "real_run", "copy_files", "path", "user", "env", "build_env"
     ]
 
     if run_stage:
@@ -452,7 +452,10 @@ def get_container_path(value, username="mlcuser", extract_parent_folder=False):
 
     new_value = ''
     if "cache" in path_split and "local" in path_split:
-        new_path_split = ["", "home", username, "MLC", "repos"]
+        if username == "root":
+            new_path_split = ["", "root", "MLC", "repos"]
+        else:
+            new_path_split = ["", "home", username, "MLC", "repos"]
         repo_entry_index = path_split.index("local")
         if len(path_split) >= repo_entry_index + 3:
             new_path_split1 = new_path_split + \
diff --git a/automation/script/experiment.py b/automation/script/experiment.py
new file mode 100644
index 000000000..8f4215933
--- /dev/null
+++ b/automation/script/experiment.py
@@ -0,0 +1,242 @@
+from collections import defaultdict
+import os
+from mlc.main import ExperimentAction
+import mlc.utils as utils
+from mlc import utils
+from utils import *
+import logging
+from pathlib import PureWindowsPath, PurePosixPath
+import time
+import copy
+from datetime import datetime
+
+
+def experiment_run(self_module, i):
+    """
+    Automates the exploration runs of MLC scripts.
+
+    Args:
+        self_module: Reference to the current module for internal calls.
+        i: Dictionary containing input parameters for the experiment execution.
+
+    Returns:
+        Dictionary with the result of the operation. Keys:
+        - 'return': 0 on success, >0 on error.
+        - 'error': Error message (if any).
+    """
+
+    # Extract and handle basic inputs
+    quiet = i.get('quiet', False)
+    show_time = i.get('show_time', False)
+    logger = self_module.logger
+    env = i.get('env', {})
+    experiment_action = ExperimentAction(self_module.action_object.parent)
+    skip_state_save = i.get('exp_skip_state_save', False)
+    extra_exp_tags = i.get('exp_tags', '').split(",")
+
+    prune_result = prune_input(
+        {'input': i, 'extra_keys_starts_with': ['exp.']})
+    if prune_result['return'] > 0:
+        return prune_result
+
+    run_input = prune_result['new_input']
+    if run_input.get('exp'):
+        del (run_input['exp'])
+
+    r = convert_input(i)
+    if r.get('exp'):
+        exp = r['exp']
+    else:
+        exp = {}
+
+    cur_dir = os.getcwd()
+    r = self_module.search(i.copy())
+    if r['return'] > 0:
+        return r
+
+    lst = r['list']
+    if not lst:
+        return {'return': 1, 'error': 'No scripts were found'}
+
+    # Process each artifact
+    for artifact in sorted(lst, key=lambda x: x.meta.get('alias', '')):
+        meta, script_path = artifact.meta, artifact.path
+        tags, script_alias, script_uid = meta.get(
+            "tags", []), meta.get(
+            'alias', ''), meta.get(
+            'uid', '')
+
+        # Execute the experiment script
+        mlc_script_input = {
+            'action': 'run', 'target': 'script'
+        }
+        if exp:
+            for key in exp:
+                ii = {**mlc_script_input, **run_input}
+                if isinstance(exp[key], list):
+                    for val in exp[key]:
+                        ii[key] = val
+                        r = run_script_and_tag_experiment(
+                            ii,
+                            self_module.action_object,
+                            experiment_action,
+                            tags,
+                            extra_exp_tags,
+                            meta,
+                            skip_state_save,
+                            logger)
+                        if r['return'] > 0:
+                            return r
+                elif isinstance(exp[key], dict):
+                    return {
+                        'return': 1, 'error': 'Dictionary inputs are not supported for mlc experiment script'}
+                else:
+                    ii[key] = exp[key]
+                    r = run_script_and_tag_experiment(
+                        ii,
+                        self_module.action_object,
+                        experiment_action,
+                        tags,
+                        extra_exp_tags,
+                        meta,
+                        skip_state_save,
+                        logger)
+                    if r['return'] > 0:
+                        return r
+
+    return {'return': 0}
+
+
+def run_script_and_tag_experiment(
+        ii, script_action, experiment_action, tags, extra_exp_tags, script_meta, skip_state_save, logger):
+
+    current_path = os.path.abspath(os.getcwd())
+    experiment_meta = {}
+    recursion_spaces = ''
+    exp_tags = tags + extra_exp_tags
+    ii = {'action': 'update',
+          'target': 'experiment',
+          'script_alias': script_meta['alias'],
+          'script_uid': script_meta['uid'],
+          'tags': ','.join(exp_tags),
+          'extra_tags': ",".join(extra_exp_tags),
+          'meta': experiment_meta,
+          'force': True}
+
+    r = experiment_action.access(ii)
+    if r['return'] > 0:
+        return r
+
+    experiment = r['list'][0]
+
+    logger.debug(
+        recursion_spaces +
+        '  - Changing to {}'.format(experiment.path))
+
+    os.chdir(experiment.path)
+    # Get current datetime in YYYY-MM-DD_HH-MM-SS format
+    timestamp = datetime.now().strftime("%Y-%m-%d_%H-%M-%S")
+
+    # Create a folder name using the timestamp
+    folder_name = f"run_{timestamp}"
+
+    # Create the directory
+    os.makedirs(folder_name, exist_ok=True)
+    os.chdir(folder_name)
+
+    if not skip_state_save:
+        ssi = {'action': 'run',
+               'target': 'script',
+               'tags': 'save,system,state',
+               'outfile': 'system_state_before.json',
+               'quiet': True
+               }
+        r = script_action.access(ssi)
+        if r['return'] > 0:
+            return r
+
+    start_time = time.time()
+    r = script_action.access(ii)
+    if r['return'] > 0:
+        return r
+
+    end_time = time.time()
+    elapsed = end_time - start_time
+    time_taken_string = format_elapsed(elapsed)
+    logger.info(f"Time taken: {time_taken_string}")
+
+    if not skip_state_save:
+        ssi['outfile'] = 'system_state_after.json'
+        r = script_action.access(ssi)
+        if r['return'] > 0:
+            return r
+
+    '''
+    exp_tags = tags
+    ii = {'action': 'update',
+          'target': 'experiment',
+          'uid': experiment.meta['uid'],
+          'meta': experiment.meta,
+          'script_alias': meta['alias'],
+          'replace_lists': True,  # To replace tags
+          'tags': ','.join(exp_tags)}
+
+    r = experiment_action.access(ii)
+    if r['return'] > 0:
+        return r
+   '''
+    os.chdir(current_path)
+    logger.info(
+        f"Experiment entry saved at: {os.path.join(experiment.path, folder_name)}")
+
+    return {'return': 0, 'experiment': experiment, 'folder_name': folder_name}
+
+
+def format_elapsed(seconds):
+    if seconds < 60:
+        return f"{seconds:.3f} seconds"
+    elif seconds < 3600:
+        mins, secs = divmod(seconds, 60)
+        return f"{int(mins)} minutes {secs:.1f} seconds"
+    else:
+        hours, remainder = divmod(seconds, 3600)
+        mins, secs = divmod(remainder, 60)
+        return f"{int(hours)} hours {int(mins)} minutes {secs:.1f} seconds"
+
+
+def parse_value(val):
+    if isinstance(val, list):
+        return [parse_value(v) for v in val]
+
+    val = str(val)
+
+    # Handle range inputs like 2:10 or 2:10:2
+    if ':' in val:
+        parts = val.split(':')
+        try:
+            parts = list(map(int, parts))
+            if len(parts) == 2:
+                return list(range(parts[0], parts[1] + 1))
+            elif len(parts) == 3:
+                return list(range(parts[0], parts[1] + 1, parts[2]))
+        except ValueError:
+            pass  # Not a valid range, fall through
+
+    # Convert to int if possible
+    if val.isdigit():
+        return int(val)
+
+    return val
+
+
+def convert_input(input_dict):
+    output = defaultdict(dict)
+
+    for key, value in input_dict.items():
+        if '.' in key:
+            main_key, sub_key = key.split('.', 1)
+            output[main_key][sub_key] = parse_value(value)
+        elif isinstance(value, dict):
+            output[key].update({k: parse_value(v) for k, v in value.items()})
+
+    return dict(output)
diff --git a/automation/script/module.py b/automation/script/module.py
index bb1f73440..6cc851fc0 100644
--- a/automation/script/module.py
+++ b/automation/script/module.py
@@ -937,32 +937,32 @@ def _run(self, i):
         #           VERSIONS SHOULD NOT BE USED INSIDE VARIATIONS (in meta)!
 
         # First, take version from input
-        version = i.get('version', '').strip()
-        version_min = i.get('version_min', '').strip()
-        version_max = i.get('version_max', '').strip()
-        version_max_usable = i.get('version_max_usable', '').strip()
+        version = str(i.get('version', '')).strip()
+        version_min = str(i.get('version_min', '')).strip()
+        version_max = str(i.get('version_max', '')).strip()
+        version_max_usable = str(i.get('version_max_usable', '')).strip()
 
         # Second, take from env
         if version == '':
-            version = env.get('MLC_VERSION', '')
+            version = str(env.get('MLC_VERSION', ''))
         if version_min == '':
-            version_min = env.get('MLC_VERSION_MIN', '')
+            version_min = str(env.get('MLC_VERSION_MIN', ''))
         if version_max == '':
-            version_max = env.get('MLC_VERSION_MAX', '')
+            version_max = str(env.get('MLC_VERSION_MAX', ''))
         if version_max_usable == '':
-            version_max_usable = env.get(
-                'MLC_VERSION_MAX_USABLE', '')
+            version_max_usable = str(env.get(
+                'MLC_VERSION_MAX_USABLE', ''))
 
         # Third, take from meta
         if version == '':
-            version = meta.get('version', '')
+            version = str(meta.get('version', ''))
         if version_min == '':
-            version_min = meta.get('version_min', '')
+            version_min = str(meta.get('version_min', ''))
         if version_max == '':
-            version_max = meta.get('version_max', '')
+            version_max = str(meta.get('version_max', ''))
         if version_max_usable == '':
-            version_max_usable = meta.get(
-                'version_max_usable', '')
+            version_max_usable = str(meta.get(
+                'version_max_usable', ''))
 
         # Update env with resolved versions
         notes = []
@@ -1388,6 +1388,7 @@ def _run(self, i):
                       'target': 'cache',
                       'search_tags': tmp_tags,
                       'script_alias': meta['alias'],
+                      'extra_tags': ",".join(extra_cache_tags),
                       'tags': ','.join(tmp_tags),
                       'meta': cached_meta,
                       'force': True}
@@ -3402,6 +3403,11 @@ def _run_deps(self, deps, clean_env_keys_deps, env, state, const, const_state, a
                     if env.get(t, '').strip() != '':
                         d['tags'] += "," + env[t]
 
+                update_tags_if_env = d.get("update_tags_if_env", [])
+                for t in update_tags_if_env:
+                    if not is_dep_tobe_skipped(update_tags_if_env[t], env):
+                        d['tags'] += "," + t
+
                 inherit_variation_tags = d.get("inherit_variation_tags", False)
                 skip_inherit_variation_groups = d.get(
                     "skip_inherit_variation_groups", [])
@@ -4470,11 +4476,9 @@ def docker(self, i):
         return docker_run(self, i)
 
     ############################################################
-    # portion for experiment action.
-    # as of now, the experiment action directly calls the run action.
-    # in the future, we will add more functionality to the experiment action.
     def experiment(self, i):
-        return self.run(i)
+        from script.experiment import experiment_run
+        return experiment_run(self, i)
 
     ##########################################################################
 
@@ -5772,10 +5776,16 @@ def update_state_from_meta(meta, env, state, const, const_state, deps, post_deps
     for c_meta in run_state['update_meta_if_env']:
         if is_dep_tobe_skipped(c_meta, env):
             continue
+        utils.merge_dicts({'dict1': default_env, 'dict2': c_meta.get(
+            'default_env', {}), 'append_lists': True, 'append_unique': True})
         utils.merge_dicts({'dict1': env, 'dict2': c_meta.get(
             'env', {}), 'append_lists': True, 'append_unique': True})
+        utils.merge_dicts({'dict1': const, 'dict2': c_meta.get(
+            'const', {}), 'append_lists': True, 'append_unique': True})
         utils.merge_dicts({'dict1': state, 'dict2': c_meta.get(
             'state', {}), 'append_lists': True, 'append_unique': True})
+        utils.merge_dicts({'dict1': const_state, 'dict2': c_meta.get(
+            'const_state', {}), 'append_lists': True, 'append_unique': True})
         if c_meta.get('docker', {}):
             if not state.get('docker', {}):
                 state['docker'] = {}
@@ -5784,6 +5794,10 @@ def update_state_from_meta(meta, env, state, const, const_state, deps, post_deps
                                'append_lists': True,
                                'append_unique': True})
 
+    # Updating again in case update_meta_if_env happened
+    for key in default_env:
+        env.setdefault(key, default_env[key])
+
     update_const = meta.get('const', {})
     if update_const:
         const.update(update_const)
diff --git a/automation/utils.py b/automation/utils.py
index 986888e87..98a3a3718 100644
--- a/automation/utils.py
+++ b/automation/utils.py
@@ -339,8 +339,8 @@ def compare_versions(i):
     # 3.9.6 vs 3.9
     # 3.9 vs 3.9.6
 
-    i_version1 = [int(v) if v.isdigit() else v for v in l_version1]
-    i_version2 = [int(v) if v.isdigit() else v for v in l_version2]
+    i_version1 = [int(v) for v in l_version1 if v.isdigit()]
+    i_version2 = [int(v) for v in l_version2 if v.isdigit()]
 
     comparison = 0
 
diff --git a/script/add-custom-nvidia-system/meta.yaml b/script/add-custom-nvidia-system/meta.yaml
index 6dce8414d..ec7202857 100644
--- a/script/add-custom-nvidia-system/meta.yaml
+++ b/script/add-custom-nvidia-system/meta.yaml
@@ -74,6 +74,11 @@ deps:
   # Detect pycuda
   - tags: get,generic-python-lib,_pycuda
 
+  - tags: get,generic-python-lib,_package.typeguard
+    enable_if_env:
+      MLC_MLPERF_INFERENCE_VERSION:
+      - "5.0"
+
 variations:
   nvidia-only:
     group: code
@@ -100,7 +105,10 @@ variations:
     add_deps_recursive:
       nvidia-inference-common-code:
         tags: _go
-
+  v5.0:
+    add_deps_recursive:
+      nvidia-inference-common-code:
+        tags: _v5.0
 
 
 
@@ -124,3 +132,8 @@ versions:
     add_deps_recursive:
       nvidia-inference-common-code:
         version: r4.0
+
+  r5.0:
+    add_deps_recursive:
+      nvidia-inference-common-code:
+        version: r5.0
diff --git a/script/app-mlperf-automotive-mlcommons-python/customize.py b/script/app-mlperf-automotive-mlcommons-python/customize.py
index 6ea96b377..806ff2951 100644
--- a/script/app-mlperf-automotive-mlcommons-python/customize.py
+++ b/script/app-mlperf-automotive-mlcommons-python/customize.py
@@ -1,254 +1,300 @@
-from mlc import utils
-from utils import is_true
-import os
-import json
-import shutil
-import subprocess
-
-
-def preprocess(i):
-
-    os_info = i['os_info']
-    env = i['env']
-    state = i['state']
-    script_path = i['run_script_input']['path']
-
-    if is_true(env.get('MLC_MLPERF_SKIP_RUN', '')):
-        return {'return': 0}
-
-    if is_true(env.get('MLC_RUN_DOCKER_CONTAINER', '')):
-        return {'return': 0}
-
-    if is_true(env.get('MLC_MLPERF_POWER', '')):
-        power = "yes"
-    else:
-        power = "no"
-
-    rerun = True if env.get("MLC_RERUN", "") != '' else False
-
-    if 'MLC_MLPERF_LOADGEN_SCENARIO' not in env:
-        env['MLC_MLPERF_LOADGEN_SCENARIO'] = "Offline"
-
-    if 'MLC_MLPERF_LOADGEN_MODE' not in env:
-        env['MLC_MLPERF_LOADGEN_MODE'] = "accuracy"
-
-    if 'MLC_MODEL' not in env:
-        return {
-            'return': 1, 'error': "Please select a variation specifying the model to run"}
-
-    # if env['MLC_MODEL'] == "resnet50":
-    #    cmd = "cp " + os.path.join(env['MLC_DATASET_AUX_PATH'], "val.txt") + " " + os.path.join(env['MLC_DATASET_PATH'],
-    #    "val_map.txt")
-    #    ret = os.system(cmd)
-
-    env['MLC_MLPERF_LOADGEN_EXTRA_OPTIONS'] = " " + \
-        env.get('MLC_MLPERF_LOADGEN_EXTRA_OPTIONS', '') + " "
-
-    if 'MLC_MLPERF_LOADGEN_QPS' not in env:
-        env['MLC_MLPERF_LOADGEN_QPS_OPT'] = ""
-    else:
-        env['MLC_MLPERF_LOADGEN_QPS_OPT'] = " --qps " + \
-            env['MLC_MLPERF_LOADGEN_QPS']
-
-    env['MLC_MLPERF_LOADGEN_EXTRA_OPTIONS'] += env['MLC_MLPERF_LOADGEN_QPS_OPT']
-
-    if 'MLC_NUM_THREADS' not in env:
-        if 'MLC_MINIMIZE_THREADS' in env:
-            env['MLC_NUM_THREADS'] = str(int(env['MLC_HOST_CPU_TOTAL_CORES']) //
-                                         (int(env.get('MLC_HOST_CPU_SOCKETS', '1')) * int(env.get('MLC_HOST_CPU_TOTAL_CORES', '1'))))
-        else:
-            env['MLC_NUM_THREADS'] = env.get('MLC_HOST_CPU_TOTAL_CORES', '1')
-
-    if env.get('MLC_MLPERF_LOADGEN_MAX_BATCHSIZE', '') != '' and not env.get(
-            'MLC_MLPERF_MODEL_SKIP_BATCHING', False):
-        env['MLC_MLPERF_LOADGEN_EXTRA_OPTIONS'] += " --max-batchsize " + \
-            str(env['MLC_MLPERF_LOADGEN_MAX_BATCHSIZE'])
-
-    if env.get('MLC_MLPERF_LOADGEN_BATCH_SIZE', '') != '':
-        env['MLC_MLPERF_LOADGEN_EXTRA_OPTIONS'] += " --batch-size " + \
-            str(env['MLC_MLPERF_LOADGEN_BATCH_SIZE'])
-
-    if env.get('MLC_MLPERF_LOADGEN_QUERY_COUNT', '') != '' and not env.get(
-            'MLC_TMP_IGNORE_MLPERF_QUERY_COUNT', False) and env.get('MLC_MLPERF_RUN_STYLE', '') != "valid":
-        env['MLC_MLPERF_LOADGEN_EXTRA_OPTIONS'] += " --count " + \
-            env['MLC_MLPERF_LOADGEN_QUERY_COUNT']
-
-    print("Using MLCommons Inference source from '" +
-          env['MLC_MLPERF_INFERENCE_SOURCE'] + "'")
-
-    if 'MLC_MLPERF_CONF' not in env:
-        env['MLC_MLPERF_CONF'] = os.path.join(
-            env['MLC_MLPERF_INFERENCE_SOURCE'], "mlperf.conf")
-
-    x = "" if os_info['platform'] == 'windows' else "'"
-    if "llama2-70b" in env['MLC_MODEL']:
-        env['MLC_MLPERF_LOADGEN_EXTRA_OPTIONS'] += " --mlperf-conf " + \
-            x + env['MLC_MLPERF_CONF'] + x
-    else:
-        env['MLC_MLPERF_LOADGEN_EXTRA_OPTIONS'] += " --mlperf_conf " + \
-            x + env['MLC_MLPERF_CONF'] + x
-
-    env['MODEL_DIR'] = env.get('MLC_ML_MODEL_PATH')
-    if not env['MODEL_DIR']:
-        env['MODEL_DIR'] = os.path.dirname(
-            env.get(
-                'MLC_MLPERF_CUSTOM_MODEL_PATH',
-                env.get('MLC_ML_MODEL_FILE_WITH_PATH')))
-
-    RUN_CMD = ""
-
-    scenario = env['MLC_MLPERF_LOADGEN_SCENARIO']
-    scenario_extra_options = ''
-
-    NUM_THREADS = env['MLC_NUM_THREADS']
-    if int(NUM_THREADS) > 2 and env['MLC_MLPERF_DEVICE'] == "gpu":
-        NUM_THREADS = "2"  # Don't use more than 2 threads when run on GPU
-
-    if env['MLC_MODEL'] in ['resnet50', 'retinanet', 'stable-diffusion-xl']:
-        scenario_extra_options += " --threads " + NUM_THREADS
-
-    ml_model_name = env['MLC_MODEL']
-    if 'MLC_MLPERF_USER_CONF' in env:
-        user_conf_path = env['MLC_MLPERF_USER_CONF']
-        x = "" if os_info['platform'] == 'windows' else "'"
-        scenario_extra_options += " --user_conf " + x + user_conf_path + x
-
-    mode = env['MLC_MLPERF_LOADGEN_MODE']
-    mode_extra_options = ""
-
-    # Grigori blocked for ABTF to preprocess data set on the fly for now
-    # we can later move it to a separate script to preprocess data set
-
-#    if 'MLC_DATASET_PREPROCESSED_PATH' in env and env['MLC_MODEL'] in  [ 'resnet50', 'retinanet' ]:
-#        #dataset_options = " --use_preprocessed_dataset --preprocessed_dir "+env['MLC_DATASET_PREPROCESSED_PATH']
-#        if env.get('MLC_MLPERF_LAST_RELEASE') not in [ "v2.0", "v2.1" ]:
-#            dataset_options = " --use_preprocessed_dataset --cache_dir "+env['MLC_DATASET_PREPROCESSED_PATH']
-#        else:
-#            dataset_options = ""
-#        if env['MLC_MODEL'] == "retinanet":
-#            dataset_options += " --dataset-list "+ env['MLC_DATASET_ANNOTATIONS_FILE_PATH']
-#        elif env['MLC_MODEL'] == "resnet50":
-#            dataset_options += " --dataset-list "+ os.path.join(env['MLC_DATASET_AUX_PATH'], "val.txt")
-#        env['DATA_DIR'] = env.get('MLC_DATASET_PREPROCESSED_PATH')
-#    else:
-#        if 'MLC_DATASET_PREPROCESSED_PATH' in env:
-#            env['DATA_DIR'] = env.get('MLC_DATASET_PREPROCESSED_PATH')
-#        else:
-#            env['DATA_DIR'] = env.get('MLC_DATASET_PATH')
-#        dataset_options = ''
-
-    # Grigori added for ABTF
-#    dataset_path = env.get('MLC_DATASET_PATH')
-#    env['DATA_DIR'] = dataset_path
-
-#    dataset_options = " --dataset-list " + env['MLC_DATASET_ANNOTATIONS_FILE_PATH']
-#    dataset_options += " --cache_dir " + os.path.join(script_path, 'preprocessed-dataset')
-
-    dataset_options = ''
-
-    if env.get('MLC_MLPERF_EXTRA_DATASET_ARGS', '') != '':
-        dataset_options += " " + env['MLC_MLPERF_EXTRA_DATASET_ARGS']
-
-    if mode == "accuracy":
-        mode_extra_options += " --accuracy"
-        env['MLC_OUTPUT_PREDICTIONS_PATH'] = os.path.join(
-            env['MLC_DATASET_MLCOMMONS_COGNATA_PATH'],
-            env['MLC_DATASET_MLCOMMONS_COGNATA_SERIAL_NUMBERS'],
-            'Cognata_Camera_01_8M_png',
-            'output')
-
-    elif mode == "performance":
-        pass
-
-    elif mode == "compliance":
-
-        audit_full_path = env['MLC_MLPERF_INFERENCE_AUDIT_PATH']
-        mode_extra_options = " --audit '" + audit_full_path + "'"
-
-    if env.get('MLC_MLPERF_OUTPUT_DIR', '') == '':
-        env['MLC_MLPERF_OUTPUT_DIR'] = os.getcwd()
-
-    mlperf_implementation = env.get('MLC_MLPERF_IMPLEMENTATION', 'reference')
-
-    # Generate CMD
-
-    # Grigori updated for ABTF demo
-#    cmd, run_dir = get_run_cmd(os_info, env, scenario_extra_options, mode_extra_options, dataset_options, mlperf_implementation)
-    cmd, run_dir = get_run_cmd_reference(
-        os_info, env, scenario_extra_options, mode_extra_options, dataset_options, script_path)
-
-    if env.get('MLC_NETWORK_LOADGEN', '') == "lon":
-
-        run_cmd = i['state']['mlperf_inference_run_cmd']
-        env['MLC_SSH_RUN_COMMANDS'] = []
-        env['MLC_SSH_RUN_COMMANDS'].append(
-            run_cmd.replace(
-                "--network=lon",
-                "--network=sut") + " &")
-
-    env['MLC_MLPERF_RUN_CMD'] = cmd
-    env['MLC_RUN_DIR'] = run_dir
-    env['MLC_RUN_CMD'] = cmd
-    env['CK_PROGRAM_TMP_DIR'] = env.get('MLC_ML_MODEL_PATH')  # for tvm
-
-    if env.get('MLC_HOST_PLATFORM_FLAVOR', '') == "arm64":
-        env['MLC_HOST_PLATFORM_FLAVOR'] = "aarch64"
-
-    if not env.get('MLC_COGNATA_ACCURACY_DUMP_FILE'):
-        env['MLC_COGNATA_ACCURACY_DUMP_FILE'] = os.path.join(
-            env['OUTPUT_DIR'], "accuracy.txt")
-
-    return {'return': 0}
-
-
-def get_run_cmd_reference(os_info, env, scenario_extra_options,
-                          mode_extra_options, dataset_options, script_path=None):
-
-    q = '"' if os_info['platform'] == 'windows' else "'"
-
-    ##########################################################################
-    # Grigori added for ABTF demo
-
-    if env['MLC_MODEL'] in ['retinanet']:
-
-        run_dir = os.path.join(script_path, 'ref')
-
-        env['RUN_DIR'] = run_dir
-
-        env['OUTPUT_DIR'] = env['MLC_MLPERF_OUTPUT_DIR']
-
-        cognata_dataset_path = env['MLC_DATASET_MLCOMMONS_COGNATA_PATH']
-# cognata_dataset_path = env['MLC_DATASET_PATH'] # Using open images
-# dataset for some tests
-
-        path_to_model = env.get(
-            'MLC_MLPERF_CUSTOM_MODEL_PATH',
-            env.get(
-                'MLC_ML_MODEL_FILE_WITH_PATH',
-                env.get('MLC_ML_MODEL_CODE_WITH_PATH')))
-        env['MODEL_FILE'] = path_to_model
-
-        cmd = env['MLC_PYTHON_BIN_WITH_PATH'] + " " + os.path.join(run_dir, "python", "main.py") + " --profile " + env['MLC_MODEL'] + "-" + env['MLC_MLPERF_BACKEND'] + \
-            " --model=" + q + path_to_model + q + \
-            " --dataset=" + env["MLC_MLPERF_VISION_DATASET_OPTION"] + \
-            " --dataset-path=" + q + cognata_dataset_path + q + \
-            " --cache_dir=" + q + os.path.join(script_path, 'tmp-preprocessed-dataset') + q + \
-            " --scenario " + env['MLC_MLPERF_LOADGEN_SCENARIO'] + " " + \
-            " --output " + q + env['OUTPUT_DIR'] + q + " " + \
-            env['MLC_MLPERF_LOADGEN_EXTRA_OPTIONS'] + \
-            scenario_extra_options + mode_extra_options + dataset_options
-
-    ##########################################################################
-
-    return cmd, run_dir
-
-
-def postprocess(i):
-
-    env = i['env']
-
-    state = i['state']
-
-    inp = i['input']
-
-    return {'return': 0}
+from mlc import utils
+from utils import is_true
+import os
+import json
+import shutil
+import subprocess
+
+
+def preprocess(i):
+
+    os_info = i['os_info']
+    env = i['env']
+    state = i['state']
+    script_path = i['run_script_input']['path']
+
+    logger = i['automation'].logger
+
+    if is_true(env.get('MLC_MLPERF_SKIP_RUN', '')):
+        return {'return': 0}
+
+    if is_true(env.get('MLC_RUN_DOCKER_CONTAINER', '')):
+        return {'return': 0}
+
+    if is_true(env.get('MLC_MLPERF_POWER', '')):
+        power = "yes"
+    else:
+        power = "no"
+
+    rerun = True if env.get("MLC_RERUN", "") != '' else False
+
+    if 'MLC_MLPERF_LOADGEN_SCENARIO' not in env:
+        env['MLC_MLPERF_LOADGEN_SCENARIO'] = "Offline"
+
+    if 'MLC_MLPERF_LOADGEN_MODE' not in env:
+        env['MLC_MLPERF_LOADGEN_MODE'] = "accuracy"
+
+    if 'MLC_MODEL' not in env:
+        return {
+            'return': 1, 'error': "Please select a variation specifying the model to run"}
+
+    # if env['MLC_MODEL'] == "resnet50":
+    #    cmd = "cp " + os.path.join(env['MLC_DATASET_AUX_PATH'], "val.txt") + " " + os.path.join(env['MLC_DATASET_PATH'],
+    #    "val_map.txt")
+    #    ret = os.system(cmd)
+
+    env['MLC_MLPERF_LOADGEN_EXTRA_OPTIONS'] = " " + \
+        env.get('MLC_MLPERF_LOADGEN_EXTRA_OPTIONS', '') + " "
+
+    if 'MLC_MLPERF_LOADGEN_QPS' not in env:
+        env['MLC_MLPERF_LOADGEN_QPS_OPT'] = ""
+    else:
+        env['MLC_MLPERF_LOADGEN_QPS_OPT'] = " --qps " + \
+            env['MLC_MLPERF_LOADGEN_QPS']
+
+    env['MLC_MLPERF_LOADGEN_EXTRA_OPTIONS'] += env['MLC_MLPERF_LOADGEN_QPS_OPT']
+
+    if 'MLC_NUM_THREADS' not in env:
+        if 'MLC_MINIMIZE_THREADS' in env:
+            env['MLC_NUM_THREADS'] = str(int(env['MLC_HOST_CPU_TOTAL_CORES']) //
+                                         (int(env.get('MLC_HOST_CPU_SOCKETS', '1')) * int(env.get('MLC_HOST_CPU_TOTAL_CORES', '1'))))
+        else:
+            env['MLC_NUM_THREADS'] = env.get('MLC_HOST_CPU_TOTAL_CORES', '1')
+
+    if env.get('MLC_MLPERF_LOADGEN_MAX_BATCHSIZE', '') != '' and not env.get(
+            'MLC_MLPERF_MODEL_SKIP_BATCHING', False):
+        env['MLC_MLPERF_LOADGEN_EXTRA_OPTIONS'] += " --max-batchsize " + \
+            str(env['MLC_MLPERF_LOADGEN_MAX_BATCHSIZE'])
+
+    if env.get('MLC_MLPERF_LOADGEN_BATCH_SIZE', '') != '':
+        env['MLC_MLPERF_LOADGEN_EXTRA_OPTIONS'] += " --batch-size " + \
+            str(env['MLC_MLPERF_LOADGEN_BATCH_SIZE'])
+
+    if env.get('MLC_MLPERF_LOADGEN_QUERY_COUNT', '') != '' and not env.get(
+            'MLC_TMP_IGNORE_MLPERF_QUERY_COUNT', False) and env.get('MLC_MLPERF_RUN_STYLE', '') != "valid":
+        env['MLC_MLPERF_LOADGEN_EXTRA_OPTIONS'] += " --count " + \
+            env['MLC_MLPERF_LOADGEN_QUERY_COUNT']
+
+    print("Using MLCommons Inference source from '" +
+          env['MLC_MLPERF_INFERENCE_SOURCE'] + "'")
+
+    env['MODEL_DIR'] = env.get('MLC_ML_MODEL_PATH')
+    if not env['MODEL_DIR']:
+        env['MODEL_DIR'] = os.path.dirname(
+            env.get(
+                'MLC_MLPERF_CUSTOM_MODEL_PATH',
+                env.get('MLC_ML_MODEL_FILE_WITH_PATH')))
+
+    RUN_CMD = ""
+
+    scenario = env['MLC_MLPERF_LOADGEN_SCENARIO']
+    scenario_extra_options = ''
+
+    NUM_THREADS = env['MLC_NUM_THREADS']
+    if int(NUM_THREADS) > 2 and env['MLC_MLPERF_DEVICE'] == "gpu":
+        NUM_THREADS = "2"  # Don't use more than 2 threads when run on GPU
+
+    if env['MLC_MODEL'] in ['resnet50', 'retinanet', 'stable-diffusion-xl']:
+        scenario_extra_options += " --threads " + NUM_THREADS
+
+    ml_model_name = env['MLC_MODEL']
+    if 'MLC_MLPERF_USER_CONF' in env:
+        user_conf_path = env['MLC_MLPERF_USER_CONF']
+        x = "" if os_info['platform'] == 'windows' else "'"
+        scenario_extra_options += " --user_conf " + x + user_conf_path + x
+
+    mode = env['MLC_MLPERF_LOADGEN_MODE']
+    mode_extra_options = ""
+
+    # Grigori blocked for ABTF to preprocess data set on the fly for now
+    # we can later move it to a separate script to preprocess data set
+
+#    if 'MLC_DATASET_PREPROCESSED_PATH' in env and env['MLC_MODEL'] in  [ 'resnet50', 'retinanet' ]:
+#        #dataset_options = " --use_preprocessed_dataset --preprocessed_dir "+env['MLC_DATASET_PREPROCESSED_PATH']
+#        if env.get('MLC_MLPERF_LAST_RELEASE') not in [ "v2.0", "v2.1" ]:
+#            dataset_options = " --use_preprocessed_dataset --cache_dir "+env['MLC_DATASET_PREPROCESSED_PATH']
+#        else:
+#            dataset_options = ""
+#        if env['MLC_MODEL'] == "retinanet":
+#            dataset_options += " --dataset-list "+ env['MLC_DATASET_ANNOTATIONS_FILE_PATH']
+#        elif env['MLC_MODEL'] == "resnet50":
+#            dataset_options += " --dataset-list "+ os.path.join(env['MLC_DATASET_AUX_PATH'], "val.txt")
+#        env['DATA_DIR'] = env.get('MLC_DATASET_PREPROCESSED_PATH')
+#    else:
+#        if 'MLC_DATASET_PREPROCESSED_PATH' in env:
+#            env['DATA_DIR'] = env.get('MLC_DATASET_PREPROCESSED_PATH')
+#        else:
+#            env['DATA_DIR'] = env.get('MLC_DATASET_PATH')
+#        dataset_options = ''
+
+    # Grigori added for ABTF
+#    dataset_path = env.get('MLC_DATASET_PATH')
+#    env['DATA_DIR'] = dataset_path
+
+#    dataset_options = " --dataset-list " + env['MLC_DATASET_ANNOTATIONS_FILE_PATH']
+#    dataset_options += " --cache_dir " + os.path.join(script_path, 'preprocessed-dataset')
+
+    dataset_options = ''
+
+    if env.get('MLC_MLPERF_EXTRA_DATASET_ARGS', '') != '':
+        dataset_options += " " + env['MLC_MLPERF_EXTRA_DATASET_ARGS']
+
+    if mode == "accuracy":
+        mode_extra_options += " --accuracy"
+        if env.get('MLC_MODEL', '') == "retinanet":
+            env['MLC_OUTPUT_PREDICTIONS_PATH'] = os.path.join(
+                env['MLC_DATASET_MLCOMMONS_COGNATA_PATH'],
+                env['MLC_DATASET_MLCOMMONS_COGNATA_SERIAL_NUMBERS'],
+                'Cognata_Camera_01_8M_png',
+                'output')
+
+    elif mode == "performance":
+        pass
+
+    elif mode == "compliance":
+
+        audit_full_path = env['MLC_MLPERF_INFERENCE_AUDIT_PATH']
+        mode_extra_options = " --audit '" + audit_full_path + "'"
+
+    if env.get('MLC_MLPERF_OUTPUT_DIR', '') == '':
+        env['MLC_MLPERF_OUTPUT_DIR'] = os.getcwd()
+
+    mlperf_implementation = env.get('MLC_MLPERF_IMPLEMENTATION', 'reference')
+
+    # Generate CMD
+
+    # Grigori updated for ABTF demo
+#    cmd, run_dir = get_run_cmd(os_info, env, scenario_extra_options, mode_extra_options, dataset_options, mlperf_implementation)
+    cmd, run_dir = get_run_cmd_reference(
+        os_info, env, scenario_extra_options, mode_extra_options, dataset_options, logger, script_path)
+
+    if env.get('MLC_NETWORK_LOADGEN', '') == "lon":
+
+        run_cmd = i['state']['mlperf_inference_run_cmd']
+        env['MLC_SSH_RUN_COMMANDS'] = []
+        env['MLC_SSH_RUN_COMMANDS'].append(
+            run_cmd.replace(
+                "--network=lon",
+                "--network=sut") + " &")
+
+    env['MLC_MLPERF_RUN_CMD'] = cmd
+    env['MLC_RUN_DIR'] = run_dir
+    env['MLC_RUN_CMD'] = cmd
+    env['CK_PROGRAM_TMP_DIR'] = env.get('MLC_ML_MODEL_PATH')  # for tvm
+
+    if env.get('MLC_HOST_PLATFORM_FLAVOR', '') == "arm64":
+        env['MLC_HOST_PLATFORM_FLAVOR'] = "aarch64"
+
+    if env.get('MLC_MODEL', '') == "retinanet":
+        if not env.get('MLC_COGNATA_ACCURACY_DUMP_FILE'):
+            env['MLC_COGNATA_ACCURACY_DUMP_FILE'] = os.path.join(
+                env['OUTPUT_DIR'], "accuracy.txt")
+
+    return {'return': 0}
+
+
+def get_run_cmd_reference(os_info, env, scenario_extra_options,
+                          mode_extra_options, dataset_options, logger, script_path=None):
+
+    q = '"' if os_info['platform'] == 'windows' else "'"
+
+    device = env['MLC_MLPERF_DEVICE']
+
+    ##########################################################################
+    # Grigori added for ABTF demo
+
+    if env['MLC_MODEL'] in ['retinanet']:
+
+        run_dir = os.path.join(script_path, 'ref')
+
+        env['RUN_DIR'] = run_dir
+
+        env['OUTPUT_DIR'] = env['MLC_MLPERF_OUTPUT_DIR']
+
+        cognata_dataset_path = env['MLC_DATASET_MLCOMMONS_COGNATA_PATH']
+# cognata_dataset_path = env['MLC_DATASET_PATH'] # Using open images
+# dataset for some tests
+
+        path_to_model = env.get(
+            'MLC_MLPERF_CUSTOM_MODEL_PATH',
+            env.get(
+                'MLC_ML_MODEL_FILE_WITH_PATH',
+                env.get('MLC_ML_MODEL_CODE_WITH_PATH')))
+        env['MODEL_FILE'] = path_to_model
+
+        cmd = env['MLC_PYTHON_BIN_WITH_PATH'] + " " + os.path.join(run_dir, "python", "main.py") + " --profile " + env['MLC_MODEL'] + "-" + env['MLC_MLPERF_BACKEND'] + \
+            " --model=" + q + path_to_model + q + \
+            " --dataset=" + env["MLC_MLPERF_VISION_DATASET_OPTION"] + \
+            " --dataset-path=" + q + cognata_dataset_path + q + \
+            " --cache_dir=" + q + os.path.join(script_path, 'tmp-preprocessed-dataset') + q + \
+            " --scenario " + env['MLC_MLPERF_LOADGEN_SCENARIO'] + " " + \
+            " --output " + q + env['OUTPUT_DIR'] + q + " " + \
+            env['MLC_MLPERF_LOADGEN_EXTRA_OPTIONS'] + \
+            scenario_extra_options + mode_extra_options + dataset_options
+
+    elif env['MLC_MODEL'] in ['bevformer']:
+        run_dir = env['MLC_MLPERF_INFERENCE_BEVFORMER_PATH']
+
+        env['RUN_DIR'] = run_dir
+
+        if device == "gpu":
+            logger.warning(
+                "Bevformer reference implementation is not supported on GPU, defaulting to CPU")
+            device = "cpu"
+
+        env['OUTPUT_DIR'] = env['MLC_MLPERF_OUTPUT_DIR']
+
+        if env['MLC_MLPERF_BACKEND'] != "onnxruntime":
+            logger.warning(
+                "Unsupported backend {MLC_MLPERF_BACKEND}, defaulting to onnx")
+            env['MLC_MLPERF_BACKEND'] = "onnx"
+
+        config_path = os.path.join(
+            run_dir,
+            "projects",
+            "configs",
+            "bevformer",
+            "bevformer_tiny.py")
+        print(env['MLC_MLPERF_LOADGEN_EXTRA_OPTIONS'])
+        cmd = f"""{env['MLC_PYTHON_BIN_WITH_PATH']} {os.path.join(run_dir, "main.py")} --output {env['OUTPUT_DIR']} --scenario {env['MLC_MLPERF_LOADGEN_SCENARIO']} --backend onnx --dataset nuscenes --device {"cuda" if device == "gpu" else "cpu"}  --nuscenes-root {os.path.dirname(env['MLC_PREPROCESSED_DATASET_NUSCENES_PATH'].rstrip("/"))} --dataset-path {env['MLC_PREPROCESSED_DATASET_NUSCENES_PATH']} --checkpoint {env['MLC_ML_MODEL_BEVFORMER_PATH']} --config {config_path} {env['MLC_MLPERF_LOADGEN_EXTRA_OPTIONS']} {scenario_extra_options} {mode_extra_options} {dataset_options}"""
+        print(cmd)
+    elif env['MLC_MODEL'] in ['ssd']:
+        run_dir = env['MLC_MLPERF_INFERENCE_SSD_RESNET50_PATH']
+
+        env['RUN_DIR'] = run_dir
+
+        env['OUTPUT_DIR'] = env['MLC_MLPERF_OUTPUT_DIR']
+
+        backend = "onnx" if env.get(
+            'MLC_MLPERF_BACKEND') == "onnxruntime" else env.get('MLC_MLPERF_BACKEND')
+
+        config_path = "baseline_8MP_ss_scales_fm1_5x5_all"
+
+        cmd = f"""{env['MLC_PYTHON_BIN_WITH_PATH']} {os.path.join(run_dir, "main.py")} --output {env['OUTPUT_DIR']} --scenario {env['MLC_MLPERF_LOADGEN_SCENARIO']} --backend {backend} --cognata-root-path {env['MLC_PREPROCESSED_DATASET_COGNATA_PATH']} --dataset-path {env['MLC_PREPROCESSED_DATASET_COGNATA_PATH']} --checkpoint {env['MLC_ML_MODEL_SSD_PATH']} --config {config_path} --device {"cuda" if device == "gpu" else "cpu"} {env['MLC_MLPERF_LOADGEN_EXTRA_OPTIONS']} {scenario_extra_options} {mode_extra_options} {dataset_options}"""
+
+    elif env['MLC_MODEL'] in ['deeplabv3plus']:
+        run_dir = env['MLC_MLPERF_INFERENCE_DEEPLABV3PLUS_PATH']
+
+        env['RUN_DIR'] = run_dir
+
+        env['OUTPUT_DIR'] = env['MLC_MLPERF_OUTPUT_DIR']
+
+        backend = "onnx" if env.get(
+            'MLC_MLPERF_BACKEND') == "onnxruntime" else env.get('MLC_MLPERF_BACKEND')
+
+        cmd = f"""{env['MLC_PYTHON_BIN_WITH_PATH']} {os.path.join(run_dir, "main.py")} --output {env['OUTPUT_DIR']} --scenario {env['MLC_MLPERF_LOADGEN_SCENARIO']} --backend {backend} --dataset cognata --device {"cuda" if device == "gpu" else "cpu"} --dataset-path {env['MLC_PREPROCESSED_DATASET_COGNATA_PATH']} --checkpoint {env['MLC_ML_MODEL_DEEPLABV3_PLUS_PATH']} {env['MLC_MLPERF_LOADGEN_EXTRA_OPTIONS']} {scenario_extra_options} {mode_extra_options} {dataset_options}"""
+
+    ##########################################################################
+
+    return cmd, run_dir
+
+
+def postprocess(i):
+
+    env = i['env']
+
+    state = i['state']
+
+    inp = i['input']
+
+    return {'return': 0}
diff --git a/script/app-mlperf-automotive-mlcommons-python/meta.yaml b/script/app-mlperf-automotive-mlcommons-python/meta.yaml
index e5567ac27..e7c863366 100644
--- a/script/app-mlperf-automotive-mlcommons-python/meta.yaml
+++ b/script/app-mlperf-automotive-mlcommons-python/meta.yaml
@@ -9,10 +9,13 @@ category: "Modular MLPerf inference benchmark pipeline for ABTF model"
 
 # User-friendly tags to find this CM script
 tags:
-- demo
+- automotive
+- mlcommons
+- reference
 - run-mlperf-inference
 - object-detection
 - abtf-model
+- demo
 
 
 # Default environment
@@ -57,6 +60,7 @@ input_mapping:
   target_latency: MLC_MLPERF_LOADGEN_TARGET_LATENCY
   offline_target_qps: MLC_MLPERF_LOADGEN_OFFLINE_TARGET_QPS
   server_target_qps: MLC_MLPERF_LOADGEN_SERVER_TARGET_QPS
+  constantstream_target_qps: MLC_MLPERF_LOADGEN_CONSTANTSTREAM_TARGET_QPS
   singlestream_target_latency: MLC_MLPERF_LOADGEN_SINGLESTREAM_TARGET_LATENCY
   multistream_target_latency: MLC_MLPERF_LOADGEN_MULTISTREAM_TARGET_LATENCY
   output: MLC_MLPERF_OUTPUT_DIR
@@ -174,26 +178,19 @@ deps:
     names:
     - ml-engine-pytorch
     - pytorch
-    enable_if_env:
-      MLC_MLPERF_BACKEND:
-      - pytorch
-      - tvm-pytorch
+    skip_if_env:
       MLC_MLPERF_DEVICE:
-      - cpu
-      - rocm
+        - gpu
 
   ## Pytorch (CUDA)
   - tags: get,generic-python-lib,_torch_cuda
     names:
     - ml-engine-pytorch
     - pytorch
-    enable_if_env:
-      MLC_MLPERF_BACKEND:
-      - pytorch
-      - tvm-pytorch
-      - ray
+    skip_if_env:
       MLC_MLPERF_DEVICE:
-      - gpu
+      - cpu
+      - rocm
 
   ## Torchvision (CPU)
   - tags: get,generic-python-lib,_torchvision
@@ -259,7 +256,7 @@ deps:
 
 
   # Creates user conf for given SUT
-  - tags: generate,user-conf,mlperf,inference
+  - tags: generate,user-conf,mlperf,inference,_automotive
     names:
     - user-conf-generator
 
@@ -273,7 +270,7 @@ deps:
     - loadgen
     - mlperf-inference-loadgen
 
-  - tags: get,loadgen
+  - tags: get,loadgen,_automotive
     enable_if_any_env:
       MLC_MLPERF_LOADGEN_BUILD_FROM_SRC:
         - "on"
@@ -340,6 +337,13 @@ variations:
     group: framework
     env:
       MLC_MLPERF_BACKEND: onnxruntime
+    add_deps_recursive:
+      ml-model-bevformer:
+        tags: _onnx
+      ml-model-ssd:
+        tags: _onnx
+      ml-model-deeplabv3-plus:
+        tags: _onnx
 
   onnxruntime,cpu:
     env:
@@ -361,10 +365,27 @@ variations:
         tags: _NCHW
       ml-model:
         tags: raw,_pytorch
+      ml-model-bevformer:
+        tags: _pytorch
+      ml-model-ssd:
+        tags: _pytorch
+      ml-model-deeplabv3-plus:
+        tags: _pytorch
     env:
       MLC_MLPERF_BACKEND: pytorch
       MLC_MLPERF_BACKEND_VERSION: <<<MLC_TORCH_VERSION>>>
-
+  
+  pytorch,cpu:
+    add_deps_recursive:
+      pytorch:
+        env:
+          MLC_GENERIC_PYTHON_PIP_EXTRA_INDEX_URL: https://download.pytorch.org/whl/cpu/torch_stable.html
+      ml-engine-torchvision:
+        env:
+          MLC_GENERIC_PYTHON_PIP_EXTRA_INDEX_URL: https://download.pytorch.org/whl/cpu/torch_stable.html
+      torchaudio:
+        env:
+          MLC_GENERIC_PYTHON_PIP_EXTRA_INDEX_URL: https://download.pytorch.org/whl/cpu/torch_stable.html
 
 
 
@@ -383,6 +404,9 @@ variations:
 
   abtf-demo-model:
     group: models
+    add_deps_recursive:
+      automotive-src:
+        tags: _sha.ee526dc63d9ca2636000343c5d2d16132145719e
     deps:
       - tags: get,generic-python-lib,_opencv-python
       - tags: get,generic-python-lib,_numpy
@@ -399,13 +423,15 @@ variations:
       - tags: get,ml-model,abtf-ssd-pytorch,_abtf-mvp
         names:
         - ml-model-abtf
-
     env:
       MLC_MODEL: retinanet
 
   abtf-poc-model:
     group: models
     default: true
+    add_deps_recursive:
+      automotive-src:
+        tags: _sha.ee526dc63d9ca2636000343c5d2d16132145719e
     deps:
       - tags: get,generic-python-lib,_opencv-python
       - tags: get,generic-python-lib,_numpy
@@ -427,10 +453,130 @@ variations:
       - tags: get,ml-model,abtf-ssd-pytorch,_abtf-poc
         names:
         - ml-model-abtf
-
     env:
       MLC_MODEL: retinanet
 
+  bevformer:
+    group: models
+    default_env:
+      MLC_MLPERF_SINGLESTREAM_TARGET_LATENCY_PERCENTILE: "99.9"
+      MLC_MLPERF_DEFAULT_MAX_QUERY_COUNT: 6636
+    add_deps_recursive:
+      pytorch:
+        version_max: "2.5.1"
+        version_max_usable: "2.5.1"
+      ml-engine-torchvision:
+        version_max: "0.20.1"
+        version_max_usable": "0.20.1"
+      torchaudio:
+        version_max: "2.5.1"
+        version_max_usable": "2.5.1"
+    deps:
+      - tags: get,generic-python-lib,_package.opencv-python
+      - tags: get,generic-python-lib,_package.numpy
+        version_max: "1.26.4"
+        version_max_usable: "1.26.4"
+      - tags: get,generic-python-lib,_package.onnx
+      - tags: get,generic-python-lib,_package.pillow
+      - tags: get,generic-python-lib,_package.pyquaternion
+      - tags: get,generic-python-lib,_package.tqdm
+      - tags: get,generic-python-lib,_package.nuscenes-devkit
+      - tags: get,preprocessed,dataset,nuscenes,_mlc,_validation
+        skip_if_env:
+          MLC_RUN_STATE_DOCKER:
+            - "yes"
+        names:
+          - preprocessed-dataset-mlcommons-nuscenes
+      - tags: get,ml-model,bevformer,_mlc,_rclone
+        skip_if_env:
+          MLC_RUN_STATE_DOCKER:
+            - "yes"
+        names:
+          - ml-model-bevformer
+
+  ssd:
+    group: models
+    default_env:
+      MLC_MLPERF_SINGLESTREAM_TARGET_LATENCY_PERCENTILE: "99.9"
+      MLC_MLPERF_DEFAULT_MAX_QUERY_COUNT: 6636
+    add_deps_recursive:
+      pytorch:
+        version_max: "2.3.1"
+        version_max_usable: "2.3.1"
+      ml-engine-torchvision:
+        version_max: "0.18.1"
+        version_max_usable": "0.18.1"
+      torchaudio:
+        version_max: "2.3.1"
+        version_max_usable": "2.3.1"
+    deps:
+      - tags: get,generic-python-lib,_package.Cython
+      - tags: get,generic-python-lib,_package.scikit-image
+      - tags: get,generic-python-lib,_package.faster-coco-eval
+      - tags: get,generic-python-lib,_torchvision
+        names:
+          - ml-engine-torchvision
+      - tags: get,generic-python-lib,_package.torchinfo
+      - tags: get,generic-python-lib,_package.torchmetrics
+      - tags: get,generic-sys-util,_libgl1-mesa-glx
+      - tags: get,generic-python-lib,_package.onnx
+      - tags: get,generic-python-lib,_package.onnxruntime
+      - tags: get,generic-python-lib,_package.tqdm
+      - tags: get,preprocessed,dataset,cognata,_mlc,_2d_obj_det,_validation
+        skip_if_env:
+          MLC_RUN_STATE_DOCKER:
+            - "yes"
+        names:
+          - preprocessed-dataset-mlcommons-cognata-ssd
+      - tags: get,ml-model,ssd,resnet50,_mlc,_rclone
+        skip_if_any_env:
+          MLC_RUN_STATE_DOCKER:
+            - "yes"
+        names:
+          - ml-model-ssd
+
+  deeplabv3plus:
+    group: models
+    default_env:
+      MLC_MLPERF_SINGLESTREAM_TARGET_LATENCY_PERCENTILE: "99.9"
+      MLC_MLPERF_DEFAULT_MAX_QUERY_COUNT: 6636
+    add_deps_recursive:
+      pytorch:
+        version_max: "2.3.1"
+        version_max_usable: "2.3.1"
+      ml-engine-torchvision:
+        version_max: "0.18.1"
+        version_max_usable": "0.18.1"
+      torchaudio:
+        version_max: "2.3.1"
+        version_max_usable": "2.3.1"
+    deps:
+      - tags: get,generic-python-lib,_package.Cython
+      - tags: get,generic-python-lib,_package.scikit-image
+      - tags: get,generic-python-lib,_package.scikit-learn
+      - tags: get,generic-python-lib,_torchvision
+        names:
+          - ml-engine-torchvision
+      - tags: get,generic-python-lib,_package.torchinfo
+      - tags: get,generic-python-lib,_package.torchmetrics
+      - tags: get,generic-sys-util,_libgl1-mesa-glx
+      - tags: get,generic-python-lib,_package.onnx
+      - tags: get,generic-python-lib,_package.onnxruntime
+      - tags: get,generic-python-lib,_package.tqdm
+      - tags: get,generic-python-lib,_package.ijson
+      - tags: get,preprocessed,dataset,cognata,_mlc,_segmentation,_validation
+        skip_if_env:
+          MLC_RUN_STATE_DOCKER:
+            - "yes"
+        names:
+          - preprocessed-dataset-mlcommons-cognata-deeplabv3-plus
+      - tags: get,ml-model,deeplabv3-plus,_mlc,_rclone
+        skip_if_env:
+          MLC_RUN_STATE_DOCKER:
+            - "yes"
+        names:
+          - ml-model-deeplabv3-plus
+
   # Target devices
   cpu:
     group: device
@@ -460,10 +606,19 @@ variations:
   singlestream:
     env:
       MLC_MLPERF_LOADGEN_SCENARIO: SingleStream
-      MLC_MLPERF_LOADGEN_MAX_BATCHSIZE: 1
+    default_variations:
+      batch-size: batch_size.1
   server:
     env:
       MLC_MLPERF_LOADGEN_SCENARIO: Server
+  constantstream:
+    env:
+      MLC_MLPERF_LOADGEN_SCENARIO: ConstantStream
 
   mvp_demo:
     env:
+
+  batch_size.#:
+    group: batch-size
+    env:
+      MLC_MLPERF_LOADGEN_MAX_BATCHSIZE: "#"
diff --git a/script/app-mlperf-automotive-mlcommons-python/ref/python/main.py b/script/app-mlperf-automotive-mlcommons-python/ref/python/main.py
index 255554f82..5f509f72f 100644
--- a/script/app-mlperf-automotive-mlcommons-python/ref/python/main.py
+++ b/script/app-mlperf-automotive-mlcommons-python/ref/python/main.py
@@ -148,11 +148,6 @@ def get_args():
         action="store_true",
         help="debug, turn traces on")
 
-    # file to use mlperf rules compliant parameters
-    parser.add_argument(
-        "--mlperf_conf",
-        default="../../mlperf.conf",
-        help="mlperf rules config")
     # file for user LoadGen settings such as target QPS
     parser.add_argument(
         "--user_conf",
@@ -466,11 +461,6 @@ def main():
         "cmdline": str(args),
     }
 
-    mlperf_conf = os.path.abspath(args.mlperf_conf)
-    if not os.path.exists(mlperf_conf):
-        log.error("{} not found".format(mlperf_conf))
-        sys.exit(1)
-
     user_conf = os.path.abspath(args.user_conf)
     if not os.path.exists(user_conf):
         log.error("{} not found".format(user_conf))
@@ -526,7 +516,6 @@ def flush_queries():
     log_settings.log_output = log_output_settings
 
     settings = lg.TestSettings()
-    settings.FromConfig(mlperf_conf, args.model_name, args.scenario)
     settings.FromConfig(user_conf, args.model_name, args.scenario)
     settings.scenario = scenario
     settings.mode = lg.TestMode.PerformanceOnly
diff --git a/script/app-mlperf-automotive/customize.py b/script/app-mlperf-automotive/customize.py
index 1333e0719..f1c0f5958 100644
--- a/script/app-mlperf-automotive/customize.py
+++ b/script/app-mlperf-automotive/customize.py
@@ -1,103 +1,421 @@
-from mlc import utils
-import os
-import json
-import shutil
-import subprocess
-import mlperf_utils
-from log_parser import MLPerfLog
-
-
-def preprocess(i):
-
-    os_info = i['os_info']
-    env = i['env']
-    state = i['state']
-    script_path = i['run_script_input']['path']
-
-    if 'cmd' in i['input']:
-        state['mlperf_inference_run_cmd'] = "mlcr " + \
-            " ".join(i['input']['cmd'])
-
-    state['mlperf-inference-implementation'] = {}
-
-    run_state = i['run_script_input']['run_state']
-    state['mlperf-inference-implementation']['script_id'] = run_state['script_id'] + \
-        ":" + ",".join(run_state['script_variation_tags'])
-
-    return {'return': 0}
-
-
-def postprocess(i):
-
-    env = i['env']
-    state = i['state']
-
-    inp = i['input']
-    os_info = i['os_info']
-
-    xsep = '^' if os_info['platform'] == 'windows' else '\\'
-
-    env['CMD'] = ''
-
-    # if env.get('MLC_MLPERF_USER_CONF', '') == '':
-    #    return {'return': 0}
-
-    output_dir = env['MLC_MLPERF_OUTPUT_DIR']
-    mode = env['MLC_MLPERF_LOADGEN_MODE']
-
-    model = env['MLC_MODEL']
-    model_full_name = env.get('MLC_ML_MODEL_FULL_NAME', model)
-
-    scenario = env['MLC_MLPERF_LOADGEN_SCENARIO']
-
-    if not os.path.exists(output_dir) or not os.path.exists(
-            os.path.join(output_dir, "mlperf_log_summary.txt")):
-        # No output, fake_run?
-        return {'return': 0}
-
-    mlperf_log = MLPerfLog(os.path.join(output_dir, "mlperf_log_detail.txt"))
-    if mode == "performance":
-        result = mlperf_log['result_mean_latency_ns'] / 1000000
-    elif mode == "accuracy":
-        if not env.get(
-                'MLC_COGNATA_ACCURACY_DUMP_FILE'):  # can happen while reusing old runs
-            env['MLC_COGNATA_ACCURACY_DUMP_FILE'] = os.path.join(
-                output_dir, "accuracy.txt")
-        acc = ""
-        if os.path.exists(env['MLC_COGNATA_ACCURACY_DUMP_FILE']):
-            with open(env['MLC_COGNATA_ACCURACY_DUMP_FILE'], "r") as f:
-                acc = f.readline()
-        result = acc
-    else:
-        return {'return': 1, 'error': f"Unknown mode {mode}"}
-
-    valid = {'performance': True, 'accuracy': True}  # its POC
-    power_result = None  # No power measurement in POC
-
-    # result, valid, power_result = mlperf_utils.get_result_from_log(env['MLC_MLPERF_LAST_RELEASE'], model, scenario, output_dir, mode)
-
-    if not state.get('mlc-mlperf-inference-results'):
-        state['mlc-mlperf-inference-results'] = {}
-    if not state.get('mlc-mlperf-inference-results-last'):
-        state['mlc-mlperf-inference-results-last'] = {}
-    if not state['mlc-mlperf-inference-results'].get(
-            state['MLC_SUT_CONFIG_NAME']):
-        state['mlc-mlperf-inference-results'][state['MLC_SUT_CONFIG_NAME']] = {}
-    if not state['mlc-mlperf-inference-results'][state['MLC_SUT_CONFIG_NAME']
-                                                 ].get(model):
-        state['mlc-mlperf-inference-results'][state['MLC_SUT_CONFIG_NAME']][model] = {}
-    if not state['mlc-mlperf-inference-results'][state['MLC_SUT_CONFIG_NAME']
-                                                 ][model].get(scenario):
-        state['mlc-mlperf-inference-results'][state['MLC_SUT_CONFIG_NAME']
-                                              ][model][scenario] = {}
-
-    state['mlc-mlperf-inference-results'][state['MLC_SUT_CONFIG_NAME']
-                                          ][model][scenario][mode] = result
-    state['mlc-mlperf-inference-results'][state['MLC_SUT_CONFIG_NAME']
-                                          ][model][scenario][mode + '_valid'] = valid.get(mode, False)
-
-    state['mlc-mlperf-inference-results-last'][mode] = result
-    state['mlc-mlperf-inference-results-last'][mode +
-                                               '_valid'] = valid.get(mode, False)
-
-    return {'return': 0}
+from mlc import utils
+import os
+import json
+import shutil
+import subprocess
+import mlperf_utils
+from log_parser import MLPerfLog
+from utils import *
+import copy
+import platform
+import sys
+
+
+def preprocess(i):
+
+    os_info = i['os_info']
+    env = i['env']
+    state = i['state']
+    script_path = i['run_script_input']['path']
+
+    if 'cmd' in i['input']:
+        state['mlperf_inference_run_cmd'] = "mlcr " + \
+            " ".join(i['input']['cmd'])
+
+    state['abtf-inference-implementation'] = {}
+
+    run_state = i['run_script_input']['run_state']
+    state['abtf-inference-implementation']['script_id'] = run_state['script_id'] + \
+        ":" + ",".join(run_state['script_variation_tags'])
+
+    return {'return': 0}
+
+
+def postprocess(i):
+
+    env = i['env']
+    state = i['state']
+
+    inp = i['input']
+    os_info = i['os_info']
+
+    xsep = '^' if os_info['platform'] == 'windows' else '\\'
+    q = '"' if os_info['platform'] == 'windows' else "'"
+
+    logger = i['automation'].logger
+
+    env['CMD'] = ''
+
+    # if env.get('MLC_MLPERF_USER_CONF', '') == '':
+    #    return {'return': 0}
+
+    output_dir = env['MLC_MLPERF_OUTPUT_DIR']
+    mode = env['MLC_MLPERF_LOADGEN_MODE']
+
+    mlc = i['automation'].action_object
+
+    result_sut_folder_path = env['MLC_MLPERF_INFERENCE_RESULTS_SUT_PATH']
+
+    model = env['MLC_MODEL']
+    model_full_name = env.get('MLC_ML_MODEL_FULL_NAME', model)
+
+    scenario = env['MLC_MLPERF_LOADGEN_SCENARIO']
+
+    if not os.path.exists(output_dir) or not os.path.exists(
+            os.path.join(output_dir, "mlperf_log_summary.txt")):
+        # No output, fake_run?
+        return {'return': 0}
+
+    mlperf_log = MLPerfLog(os.path.join(output_dir, "mlperf_log_detail.txt"))
+    if mode == "performance":
+        if scenario in ["Offline", "Server", "ConstantStream"]:
+            metric = "target_qps"
+            result = mlperf_log['result_mean_latency_ns'] / 1000000
+        elif scenario.endswith("Stream"):
+            metric = "target_latency"
+            result = mlperf_log['result_mean_latency_ns']
+        else:
+            return {'return': 1,
+                    'error': 'Unsupported scenario: {}'.format(scenario)}
+        import yaml
+        sut_name = state['MLC_SUT_CONFIG_NAME']
+        sut_config = state['MLC_SUT_CONFIG'][sut_name]
+        sut_config_path = state['MLC_SUT_CONFIG_PATH'][sut_name]
+        if scenario not in sut_config[model_full_name]:
+            sut_config[model_full_name][scenario] = {}
+        sut_config[model_full_name][scenario][metric] = result
+
+        print(
+            f"SUT: {sut_name}, model: {model_full_name}, scenario: {scenario}, {metric} (mean value) updated as {result}")
+        with open(sut_config_path, "w") as f:
+            yaml.dump(sut_config, f)
+        logger.info(f"New config stored in {sut_config_path}")
+    elif mode == "accuracy":
+        acc = ""
+        if env.get('MLC_MLPERF_INFERENCE_VERSION', '') == "mvp-demo" and env.get(
+                'MLC_MLPERF_INFERENCE_VERSION') == "poc-demo":
+            if not env.get(
+                    'MLC_COGNATA_ACCURACY_DUMP_FILE'):  # can happen while reusing old runs
+                env['MLC_COGNATA_ACCURACY_DUMP_FILE'] = os.path.join(
+                    output_dir, "accuracy.txt")
+            if os.path.exists(env['MLC_COGNATA_ACCURACY_DUMP_FILE']):
+                with open(env['MLC_COGNATA_ACCURACY_DUMP_FILE'], "r") as f:
+                    acc = f.readline()
+        result = acc
+    else:
+        return {'return': 1, 'error': f"Unknown mode {mode}"}
+
+    valid = {'performance': True, 'accuracy': True}  # its POC
+    power_result = None  # No power measurement in POC
+
+    # result, valid, power_result = mlperf_utils.get_result_from_log(env['MLC_MLPERF_LAST_RELEASE'], model, scenario, output_dir, mode)
+
+    if not state.get('mlc-mlperf-inference-results'):
+        state['mlc-mlperf-inference-results'] = {}
+    if not state.get('mlc-mlperf-inference-results-last'):
+        state['mlc-mlperf-inference-results-last'] = {}
+    if not state['mlc-mlperf-inference-results'].get(
+            state['MLC_SUT_CONFIG_NAME']):
+        state['mlc-mlperf-inference-results'][state['MLC_SUT_CONFIG_NAME']] = {}
+    if not state['mlc-mlperf-inference-results'][state['MLC_SUT_CONFIG_NAME']
+                                                 ].get(model):
+        state['mlc-mlperf-inference-results'][state['MLC_SUT_CONFIG_NAME']][model] = {}
+    if not state['mlc-mlperf-inference-results'][state['MLC_SUT_CONFIG_NAME']
+                                                 ][model].get(scenario):
+        state['mlc-mlperf-inference-results'][state['MLC_SUT_CONFIG_NAME']
+                                              ][model][scenario] = {}
+
+    state['mlc-mlperf-inference-results'][state['MLC_SUT_CONFIG_NAME']
+                                          ][model][scenario][mode] = result
+    state['mlc-mlperf-inference-results'][state['MLC_SUT_CONFIG_NAME']
+                                          ][model][scenario][mode + '_valid'] = valid.get(mode, False)
+
+    state['mlc-mlperf-inference-results-last'][mode] = result
+    state['mlc-mlperf-inference-results-last'][mode +
+                                               '_valid'] = valid.get(mode, False)
+
+    if mode in ["performance", "accuracy"] and env.get(
+            'MLC_MLPERF_INFERENCE_VERSION', '') not in ["", "mvp-demo", "poc-demo"]:
+        # if measurements file exist read it
+        if os.path.exists("measurements.json"):
+            with open("measurements.json", "r") as file:
+                measurements = json.load(file)  # Load JSON data from the file
+        else:
+            measurements = {}
+        measurements['starting_weights_filename'] = env.get(
+            'MLC_ML_MODEL_STARTING_WEIGHTS_FILENAME', env.get(
+                'MLC_ML_MODEL_FILE', measurements.get(
+                    'starting_weights_filename', 'TBD')))
+        measurements['retraining'] = env.get(
+            'MLC_ML_MODEL_RETRAINING', measurements.get(
+                'retraining', 'no'))
+        measurements['input_data_types'] = env.get(
+            'MLC_ML_MODEL_INPUTS_DATA_TYPE', measurements.get(
+                'input_data_types', 'fp32'))
+        measurements['weight_data_types'] = env.get(
+            'MLC_ML_MODEL_WEIGHTS_DATA_TYPE', measurements.get(
+                'weight_data_types', 'fp32'))
+        measurements['weight_transformations'] = env.get(
+            'MLC_ML_MODEL_WEIGHT_TRANSFORMATIONS', measurements.get(
+                'weight_transformations', 'none'))
+
+        os.chdir(output_dir)
+
+        if not os.path.exists("mlperf_log_summary.txt"):
+            return {'return': 0}
+
+        mlperf_log_summary = ''
+        if os.path.isfile("mlperf_log_summary.txt"):
+            with open("mlperf_log_summary.txt", "r") as fp:
+                mlperf_log_summary = fp.read()
+
+        if mlperf_log_summary != '':
+            state['app_mlperf_inference_log_summary'] = {}
+            for x in mlperf_log_summary.split('\n'):
+                y = x.split(': ')
+                if len(y) == 2:
+                    state['app_mlperf_inference_log_summary'][y[0].strip().lower()
+                                                              ] = y[1].strip()
+
+        if not is_false(env.get("MLC_MLPERF_PRINT_SUMMARY", "")):
+            logger.info("\n")
+            logger.info(mlperf_log_summary)
+
+        with open("measurements.json", "w") as fp:
+            json.dump(measurements, fp, indent=2)
+
+        mlc_sut_info = {}
+        mlc_sut_info['system_name'] = state['MLC_SUT_META']['system_name']
+        mlc_sut_info['implementation'] = env['MLC_MLPERF_IMPLEMENTATION']
+        mlc_sut_info['device'] = env['MLC_MLPERF_DEVICE']
+        mlc_sut_info['framework'] = state['MLC_SUT_META']['framework']
+        mlc_sut_info['run_config'] = env['MLC_MLPERF_INFERENCE_SUT_RUN_CONFIG']
+        with open(os.path.join(result_sut_folder_path, "mlc-sut-info.json"), "w") as fp:
+            json.dump(mlc_sut_info, fp, indent=2)
+
+        system_meta = state['MLC_SUT_META']
+        with open("system_meta.json", "w") as fp:
+            json.dump(system_meta, fp, indent=2)
+
+        # map the custom model for inference result to the official model
+        # if custom model name is not set, the official model name will be
+        # mapped to itself
+        official_model_name = model
+        if "efficientnet" in official_model_name or "mobilenet" in official_model_name:
+            official_model_name = "resnet"
+        model_mapping = {model_full_name: official_model_name}
+        with open("model_mapping.json", "w") as fp:
+            json.dump(model_mapping, fp, indent=2)
+
+        # Add to the state
+        state['app_mlperf_inference_measurements'] = copy.deepcopy(
+            measurements)
+
+        if os.path.exists(env['MLC_MLPERF_CONF']):
+            shutil.copy(env['MLC_MLPERF_CONF'], 'mlperf.conf')
+
+        if os.path.exists(env['MLC_MLPERF_USER_CONF']):
+            shutil.copy(env['MLC_MLPERF_USER_CONF'], 'user.conf')
+
+        result, valid, power_result = mlperf_utils.get_result_from_log(
+            env['MLC_MLPERF_LAST_RELEASE'], model, scenario, output_dir, mode, env.get('MLC_MLPERF_INFERENCE_SOURCE_VERSION'))
+
+        state['mlc-mlperf-inference-results'][state['MLC_SUT_CONFIG_NAME']
+                                              ][model][scenario][mode] = result
+        state['mlc-mlperf-inference-results'][state['MLC_SUT_CONFIG_NAME']
+                                              ][model][scenario][mode + '_valid'] = valid.get(mode, False)
+
+        state['mlc-mlperf-inference-results-last'][mode] = result
+        state['mlc-mlperf-inference-results-last'][mode +
+                                                   '_valid'] = valid.get(mode, False)
+
+        # Power not included in v0.5, code should be added in future
+
+        # Record basic host info
+        host_info = {
+            "os_version": platform.platform(),
+            "cpu_version": platform.processor(),
+            "python_version": sys.version,
+        }
+        try:
+            import importlib.metadata
+            mlc_version = importlib.metadata.version("mlc")
+            host_info["mlc_version"] = mlc_version
+        except Exception as e:
+            error = format(e)
+            mlc_version = "unknown"
+
+        x = ''
+        if env.get('MLC_HOST_OS_FLAVOR', '') != '':
+            x += env['MLC_HOST_OS_FLAVOR']
+        if env.get('MLC_HOST_OS_VERSION', '') != '':
+            x += ' ' + env['MLC_HOST_OS_VERSION']
+        if x != '':
+            host_info['os_version_sys'] = x
+
+        if env.get('MLC_HOST_SYSTEM_NAME', '') != '':
+            host_info['system_name'] = env['MLC_HOST_SYSTEM_NAME']
+
+        # Check CM automation repository
+        repo_name = 'mlcommons@mlperf-automations'
+        repo_hash = ''
+        r = mlc.access({'action': 'find', 'automation': 'repo',
+                       'item': 'mlcommons@mlperf-automations,9e97bb72b0474657'})
+        if r['return'] == 0 and len(r['list']) == 1:
+            repo_path = r['list'][0].path
+            if os.path.isdir(repo_path):
+                repo_name = os.path.basename(repo_path)
+
+                # Check dev
+                # if repo_name == 'cm4mlops': repo_name = 'mlcommons@cm4mlops'
+
+                r = utils.run_system_cmd({
+                    'path': repo_path,
+                    'cmd': 'git rev-parse HEAD'})
+                if r['return'] == 0:
+                    repo_hash = r['output']
+
+                    host_info['mlc_repo_name'] = repo_name
+                    host_info['mlc_repo_git_hash'] = repo_hash
+
+        with open("mlc-host-info.json", "w") as fp:
+            fp.write(json.dumps(host_info, indent=2) + '\n')
+
+        # Prepare README
+        if "cmd" in inp:
+            cmd = "mlc run script \\\n\t" + " \\\n\t".join(inp['cmd'])
+            xcmd = "mlc run script " + xsep + "\n\t" + \
+                (" " + xsep + "\n\t").join(inp['cmd'])
+        else:
+            cmd = ""
+            xcmd = ""
+
+        readme_init = "*Check [MLC MLPerf docs](https://docs.mlcommons.org/automotive) for more details.*\n\n"
+
+        readme_body = "## Host platform\n\n* OS version: {}\n* CPU version: {}\n* Python version: {}\n* MLC version: {}\n\n".format(platform.platform(),
+                                                                                                                                    platform.processor(), sys.version, mlc_version)
+
+        x = repo_name
+        if repo_hash != '':
+            x += ' --checkout=' + str(repo_hash)
+
+        readme_body += "## MLC Run Command\n\nSee [MLC installation guide](https://docs.mlcommons.org/mlcflow/install/).\n\n" + \
+            "```bash\npip install -U mlcflow\n\nmlc rm cache -f\n\nmlc pull repo {}\n\n{}\n```".format(
+                x, xcmd)
+
+        readme_body += "\n*Note that if you want to use the [latest automation recipes](https://docs.mlcommons.org/inference) for MLPerf,\n" + \
+                       " you should simply reload {} without checkout and clean MLC cache as follows:*\n\n".format(repo_name) + \
+                       "```bash\nmlc rm repo {}\nmlc pull repo {}\nmlc rm cache -f\n\n```".format(
+                           repo_name, repo_name)
+
+        extra_readme_init = ''
+        extra_readme_body = ''
+        if env.get('MLC_MLPERF_README', '') == "yes":
+            extra_readme_body += "\n## Dependent MLPerf Automation scripts\n\n"
+
+            script_tags = inp['tags']
+            script_adr = inp.get('adr', {})
+
+            mlc_input = {'action': 'run',
+                         'automation': 'script',
+                         'tags': script_tags,
+                         'adr': script_adr,
+                         'print_deps': True,
+                         'env': env,
+                         'quiet': True,
+                         'silent': True,
+                         'fake_run': True
+                         }
+            r = mlc.access(mlc_input)
+            if r['return'] > 0:
+                return r
+
+            print_deps = r['new_state']['print_deps']
+            count = 1
+            for dep in print_deps:
+                extra_readme_body += "\n\n" + str(count) + ".  `" + dep + "`\n"
+                count = count + 1
+
+            if state.get(
+                    'abtfabtf-inference-implementation') and state['abtfabtf-inference-implementation'].get('print_deps'):
+
+                extra_readme_body += "\n## Dependent automation scripts for the MLPerf Automotive Implementation\n"
+
+                print_deps = state['abtfabtf-inference-implementation']['print_deps']
+                count = 1
+                for dep in print_deps:
+                    extra_readme_body += "\n\n" + \
+                        str(count) + ". `" + dep + "`\n"
+                    count = count + 1
+
+        readme = readme_init + readme_body
+        extra_readme = extra_readme_init + extra_readme_body
+
+        with open("README.md", "w") as fp:
+            fp.write(readme)
+        if extra_readme:
+            with open("README-extra.md", "w") as fp:
+                fp.write(extra_readme)
+
+    if state.get(
+            'abtf-inference-implementation') and state['abtf-inference-implementation'].get('version_info'):
+        env['MLC_MLPERF_RUN_JSON_VERSION_INFO_FILE'] = os.path.join(
+            output_dir, "mlc-version-info.json")
+        env['MLC_MLPERF_RUN_DEPS_GRAPH'] = os.path.join(
+            output_dir, "mlc-deps.png")
+        env['MLC_MLPERF_RUN_DEPS_MERMAID'] = os.path.join(
+            output_dir, "mlc-deps.mmd")
+        with open(os.path.join(output_dir, "mlc-version-info.json"), "w") as f:
+            f.write(
+                json.dumps(
+                    state['abtf-inference-implementation']['version_info'],
+                    indent=2))
+
+    if env.get('MLC_DUMP_SYSTEM_INFO', True):
+        dump_script_output(
+            "detect,os",
+            env,
+            state,
+            'new_env',
+            os.path.join(
+                output_dir,
+                "os_info.json"), mlc)
+        dump_script_output(
+            "detect,cpu",
+            env,
+            state,
+            'new_env',
+            os.path.join(
+                output_dir,
+                "cpu_info.json"), mlc)
+        env['MLC_DUMP_RAW_PIP_FREEZE_FILE_PATH'] = os.path.join(
+            env['MLC_MLPERF_OUTPUT_DIR'], "pip_freeze.raw")
+        dump_script_output(
+            "dump,pip,freeze",
+            env,
+            state,
+            'new_state',
+            os.path.join(
+                output_dir,
+                "pip_freeze.json"), mlc)
+
+    return {'return': 0}
+
+
+def dump_script_output(script_tags, env, state, output_key, dump_file, mlc):
+
+    mlc_input = {'action': 'run',
+                 'automation': 'script',
+                 'tags': script_tags,
+                 'env': env,
+                 'state': state,
+                 'quiet': True,
+                 'silent': True,
+                 }
+    r = mlc.access(mlc_input)
+    if r['return'] > 0:
+        return r
+    with open(dump_file, "w") as f:
+        f.write(json.dumps(r[output_key], indent=2))
+
+    return {'return': 0}
diff --git a/script/app-mlperf-automotive/meta.yaml b/script/app-mlperf-automotive/meta.yaml
index 896008c39..ebe23d75d 100644
--- a/script/app-mlperf-automotive/meta.yaml
+++ b/script/app-mlperf-automotive/meta.yaml
@@ -4,14 +4,16 @@ uid: f7488ce376484fd2
 automation_alias: script
 automation_uid: 5b4e0237da074764
 
-category: "Modular MLPerf inference benchmark pipeline for ABTF model"
+category: "Modular MLPerf automotive benchmark pipeline for ABTF models"
 
 
 # User-friendly tags to find this CM script
 tags:
 - app
 - app-mlperf-inference
+- app-mlperf-inference-automotive
 - mlperf-inference
+- mlperf-inference-automotive
 - abtf-inference
 
 predeps: no
@@ -57,6 +59,7 @@ input_mapping:
   target_latency: MLC_MLPERF_LOADGEN_TARGET_LATENCY
   offline_target_qps: MLC_MLPERF_LOADGEN_OFFLINE_TARGET_QPS
   server_target_qps: MLC_MLPERF_LOADGEN_SERVER_TARGET_QPS
+  constantstream_target_qps: MLC_MLPERF_LOADGEN_CONSTANTSTREAM_TARGET_QPS
   singlestream_target_latency: MLC_MLPERF_LOADGEN_SINGLESTREAM_TARGET_LATENCY
   multistream_target_latency: MLC_MLPERF_LOADGEN_MULTISTREAM_TARGET_LATENCY
   output: MLC_MLPERF_OUTPUT_DIR
@@ -90,26 +93,55 @@ deps:
   # Use mlc inside scripts
   #- tags: get,generic-python-lib,_package.mlcflow
 
-  - tags: get,mlperf,inference,utils
+  - tags: get,mlperf,automotive,utils
+
+posthook_deps:
+  - tags: get,mlperf,sut,description #populate system meta information like framework
+  - tags: get,platform,details
+    enable_if_env:
+      MLC_GET_PLATFORM_DETAILS:
+        - yes
+    skip_if_env:
+      MLC_MLPERF_LOADGEN_MODE:
+      - accuracy
+    env: 
+      MLC_PLATFORM_DETAILS_FILE_PATH: '<<<MLC_MLPERF_OUTPUT_DIR>>>/system_info.txt'
+
+post_deps:
+  - tags: draw,graph,from-json
+    enable_if_env:
+      MLC_MLPERF_RUN_JSON_VERSION_INFO_FILE:
+        - on
+    env:
+      MLC_JSON_INPUT_FILE: <<<MLC_MLPERF_RUN_JSON_VERSION_INFO_FILE>>>
+      MLC_OUTPUT_IMAGE_PATH: <<<MLC_MLPERF_RUN_DEPS_GRAPH>>>
+      MLC_OUTPUT_MERMAID_PATH: <<<MLC_MLPERF_RUN_DEPS_MERMAID>>>
 
 
 docker:
-  mlc_repo: gateoverflow@mlperf-automations
+  mlc_repo: mlcommons@mlperf-automations
   mlc_repo_branch: dev
   use_host_group_id: True
   use_host_user_id: True
   real_run: false
+  user: mlcuser
   interactive: True
   mlc_repos_off: 'mlc pull repo mlcommons@cm4abtf --branch=poc'
+  pre_run_cmds:
+    - mlc pull repo
   deps:
     - tags: get,abtf,scratch,space
   mounts:
     - "${{ MLC_ABTF_SCRATCH_PATH_DATASETS }}:${{ MLC_ABTF_SCRATCH_PATH_DATASETS }}"
+    - "${{ MLC_ML_MODEL_FILE_WITH_PATH }}:${{ MLC_ML_MODEL_FILE_WITH_PATH }}"
 
 
 # Variations to customize dependencies
 variations:
 
+  reference:
+    alias: mlcommons-python
+
   # Implementation
   mlcommons-python:
     group: implementation
@@ -121,7 +153,7 @@ variations:
       - names:
          - python-reference-abtf-inference
          - abtf-inference-implementation
-        tags: run-mlperf-inference,demo,abtf-model
+        tags: run-mlperf-inference,abtf-model
         skip_if_env:
           MLC_SKIP_RUN:
             - yes
@@ -157,7 +189,19 @@ variations:
     add_deps_recursive:
       abtf-inference-implementation:
         tags: _onnxruntime
-
+      ml-model-bevformer:
+        tags: _onnx
+      ml-model-ssd:
+        tags: _onnx
+      ml-model-deeplabv3plus:
+        tags: _onnx
+
+  onnx_dynamic:
+    base:
+      - onnxruntime
+    add_deps_recursive:
+      ml-model-deeplabv3plus:
+        tags: _onnx_dynamic
 
   onnxruntime,cpu:
     env:
@@ -178,6 +222,12 @@ variations:
     add_deps_recursive:
       abtf-inference-implementation:
         tags: _pytorch
+      ml-model-bevformer:
+        tags: _pytorch
+      ml-model-ssd:
+        tags: _pytorch
+      ml-model-deeplabv3plus:
+        tags: _pytorch
 
 
   abtf-demo-model:
@@ -204,10 +254,120 @@ variations:
           enable_if_env:
             MLC_DATASET_MLCOMMONS_COGNATA_DOWNLOAD_IN_HOST:
               - yes
-
       mounts:
         - "${{ MLC_DATASET_MLCOMMONS_COGNATA_PATH }}:${{ MLC_DATASET_MLCOMMONS_COGNATA_PATH }}"
-
+  
+  bevformer:
+    group:
+      models
+    default_env:
+      MLC_USE_DATASET_FROM_HOST: yes
+    env:
+      MLC_MODEL: bevformer
+    docker:
+      deps:
+        - tags: get,preprocessed,dataset,nuscenes,_mlc,_validation
+          enable_if_env:
+            MLC_USE_DATASET_FROM_HOST:
+              - "yes"
+        - tags: get,ml-model,bevformer,_mlc,_rclone
+          enable_if_env:
+            MLC_USE_MODEL_FROM_HOST:
+              - "yes"
+          names:
+            - ml-model-bevformer
+      mounts:
+        - "${{ MLC_PREPROCESSED_DATASET_NUSCENES_PATH }}:${{ MLC_PREPROCESSED_DATASET_NUSCENES_PATH }}"
+        - "${{ MLC_ML_MODEL_BEVFORMER_PATH }}:${{ MLC_ML_MODEL_BEVFORMER_PATH }}"
+        - "${{ MLC_PREPROCESSED_DATASET_NUSCENES_ACC_CHECKER_MIN_FILES_PATH }}:${{ MLC_PREPROCESSED_DATASET_NUSCENES_ACC_CHECKER_MIN_FILES_PATH }}"
+    add_deps_recursive:
+      abtf-inference-implementation:
+        tags: _bevformer
+    posthook_deps:
+    - enable_if_env:
+        MLC_MLPERF_LOADGEN_MODE:
+        - accuracy
+        - all
+        MLC_MLPERF_ACCURACY_RESULTS_DIR:
+        - 'on'
+      names:
+      - mlperf-accuracy-script
+      - nuscenes-accuracy-script
+      tags: run,accuracy,mlperf,_nuscenes
+  
+  ssd:
+    group:
+      models
+    default_env:
+      MLC_USE_DATASET_FROM_HOST: yes
+    env:
+      MLC_MODEL: ssd
+    docker:
+      deps:
+        - tags: get,preprocessed,dataset,cognata,_mlc,_2d_obj_det,_validation
+          enable_if_env:
+            MLC_USE_DATASET_FROM_HOST:
+              - "yes"
+        - tags: get,ml-model,ssd,resnet50,_mlc,_rclone
+          enable_if_env:
+            MLC_USE_MODEL_FROM_HOST:
+              - "yes"
+          names:
+            - ml-model-ssd
+      mounts:
+        - "${{ MLC_PREPROCESSED_DATASET_COGNATA_PATH }}:${{ MLC_PREPROCESSED_DATASET_COGNATA_PATH }}"
+        - "${{ MLC_ML_MODEL_SSD_PATH }}:${{ MLC_ML_MODEL_SSD_PATH }}"
+    add_deps_recursive:
+      abtf-inference-implementation:
+        tags: _ssd
+    posthook_deps:
+    - enable_if_env:
+        MLC_MLPERF_LOADGEN_MODE:
+        - accuracy
+        - all
+        MLC_MLPERF_ACCURACY_RESULTS_DIR:
+        - 'on'
+      names:
+      - mlperf-accuracy-script
+      - cognata-ssd-accuracy-script
+      tags: run,accuracy,mlperf,_cognata_ssd
+  
+  deeplabv3plus:
+    group:
+      models
+    default_env:
+      MLC_USE_DATASET_FROM_HOST: yes
+    env:
+      MLC_MODEL: deeplabv3plus
+    docker:
+      deps:
+        - tags: get,preprocessed,dataset,cognata,_mlc,_segmentation,_validation
+          enable_if_env:
+            MLC_USE_DATASET_FROM_HOST:
+              - "yes"
+        - tags:  get,ml-model,deeplabv3-plus,_mlc,_rclone
+          enable_if_env:
+            MLC_USE_MODEL_FROM_HOST:
+              - "yes"
+          names:
+            - ml-model-deeplabv3plus
+      mounts:
+        - "${{ MLC_PREPROCESSED_DATASET_COGNATA_PATH }}:${{ MLC_PREPROCESSED_DATASET_COGNATA_PATH }}"
+        - "${{ MLC_ML_MODEL_DEEPLABV3_PLUS_PATH }}:${{ MLC_ML_MODEL_DEEPLABV3_PLUS_PATH }}"
+    add_deps_recursive:
+      abtf-inference-implementation:
+        tags: _deeplabv3plus
+    posthook_deps:
+    - enable_if_env:
+        MLC_MLPERF_LOADGEN_MODE:
+        - accuracy
+        - all
+        MLC_MLPERF_ACCURACY_RESULTS_DIR:
+        - 'on'
+      names:
+      - mlperf-accuracy-script
+      - cognata-deeplab-accuracy-script
+      tags: run,accuracy,mlperf,_cognata_deeplab
 
   # Target devices
   cpu:
@@ -222,6 +382,9 @@ variations:
       abtf-inference-implementation:
         tags: _cpu
 
+  gpu:
+    alias: cuda
+
   cuda:
     group: device
     env:
@@ -234,8 +397,18 @@ variations:
     docker:
       all_gpus: 'yes'
       base_image: nvcr.io/nvidia/pytorch:24.03-py3
+      os_version: 22.04
+
+  v0.5: {}
 
+  mvp-demo: {}
 
+  poc-demo: {}
+
+  v0.5,mlcommons-python,cpu:
+    docker:
+      base_image: ubuntu:22.04
+      os_version: 22.04
 
   # Loadgen scenarios
   offline:
@@ -244,12 +417,14 @@ variations:
     add_deps_recursive:
       abtf-inference-implementation:
         tags: _offline
+
   multistream:
     env:
       MLC_MLPERF_LOADGEN_SCENARIO: MultiStream
     add_deps_recursive:
       abtf-inference-implementation:
         tags: _multistream
+
   singlestream:
     group: loadgen-scenario
     default: true
@@ -258,6 +433,14 @@ variations:
     add_deps_recursive:
       abtf-inference-implementation:
         tags: _singlestream
+
+  constantstream:
+    env:
+      MLC_MLPERF_LOADGEN_SCENARIO: ConstantStream
+    add_deps_recursive:
+      abtf-inference-implementation:
+        tags: _constantstream
+
   server:
     env:
       MLC_MLPERF_LOADGEN_SCENARIO: Server
@@ -286,3 +469,11 @@ variations:
       MLC_DATASET_MLCOMMONS_COGNATA_GROUP_NAMES: Cognata_Camera_01_8M
       MLC_ABTF_ML_MODEL_TRAINING_FORCE_COGNATA_LABELS: 'yes'
       MLC_ABTF_ML_MODEL_SKIP_WARMUP: 'yes'
+
+  batch_size.#:
+    group: batch_size
+    env:
+      MLC_MLPERF_LOADGEN_MAX_BATCHSIZE: '#'
+    add_deps_recursive:
+      abtf-inference-implementation:
+        tags: _batch_size.#
diff --git a/script/app-mlperf-inference-amd/meta.yaml b/script/app-mlperf-inference-amd/meta.yaml
index 2c3b6d063..1481362be 100644
--- a/script/app-mlperf-inference-amd/meta.yaml
+++ b/script/app-mlperf-inference-amd/meta.yaml
@@ -91,12 +91,12 @@ deps:
     - inference-src
 
   # Download MLPerf inference loadgen
-  - tags: get,mlcommons,inference,loadgen
+  - tags: get,mlcommons,inference,loadgen,_inference
     names:
     - inference-loadgen
 
   # Creates user conf for given SUT
-  - tags: generate,user-conf,mlperf,inference
+  - tags: generate,user-conf,mlperf,inference,_inference
     names:
     - user-conf-generator
 
diff --git a/script/app-mlperf-inference-ctuning-cpp-tflite/meta.yaml b/script/app-mlperf-inference-ctuning-cpp-tflite/meta.yaml
index 815a2a152..0ffa1e9d2 100644
--- a/script/app-mlperf-inference-ctuning-cpp-tflite/meta.yaml
+++ b/script/app-mlperf-inference-ctuning-cpp-tflite/meta.yaml
@@ -28,7 +28,7 @@ deps:
   tags: get,cuda
 - names:
   - loadgen
-  tags: get,loadgen
+  tags: get,loadgen,_inference
 - names:
   - inference-src
   tags: get,mlcommons,inference,src
@@ -121,7 +121,7 @@ post_deps:
 prehook_deps:
 - names:
   - user-conf-generator
-  tags: generate,user-conf,mlperf,inference
+  tags: generate,user-conf,mlperf,inference,_inference
 - enable_if_env:
     MLC_MLPERF_SKIP_RUN:
     - 'no'
diff --git a/script/app-mlperf-inference-dummy/meta.yaml b/script/app-mlperf-inference-dummy/meta.yaml
index f8876eb81..e488d679e 100644
--- a/script/app-mlperf-inference-dummy/meta.yaml
+++ b/script/app-mlperf-inference-dummy/meta.yaml
@@ -91,12 +91,12 @@ deps:
     - inference-src
 
   # Download MLPerf inference loadgen
-  - tags: get,mlcommons,inference,loadgen
+  - tags: get,mlcommons,inference,loadgen,_inference
     names:
     - inference-loadgen
 
   # Creates user conf for given SUT
-  - tags: generate,user-conf,mlperf,inference
+  - tags: generate,user-conf,mlperf,inference,_inference
     names:
     - user-conf-generator
 
diff --git a/script/app-mlperf-inference-intel/meta.yaml b/script/app-mlperf-inference-intel/meta.yaml
index 86a2806eb..3470e6712 100644
--- a/script/app-mlperf-inference-intel/meta.yaml
+++ b/script/app-mlperf-inference-intel/meta.yaml
@@ -392,7 +392,7 @@ variations:
       - tags: get,mlcommons,inference,src
         names:
         - inference-src
-      - tags: get,mlcommons,inference,loadgen,_custom-python,_keep-build
+      - tags: get,mlcommons,inference,loadgen,_custom-python,_keep-build,_inference
         names:
         - inference-loadgen
 
@@ -510,7 +510,7 @@ variations:
       - tags: get,mlcommons,inference,src
         names:
         - inference-src
-      - tags: get,mlcommons,inference,loadgen,_custom-python,_keep-build
+      - tags: get,mlcommons,inference,loadgen,_custom-python,_keep-build,_inference
         names:
         - inference-loadgen
  
@@ -627,7 +627,7 @@ variations:
       - tags: get,mlcommons,inference,src
         names:
         - inference-src
-      - tags: get,mlcommons,inference,loadgen,_custom-python,_keep-build
+      - tags: get,mlcommons,inference,loadgen,_custom-python,_keep-build,_inference
         names:
         - inference-loadgen
  
@@ -699,7 +699,7 @@ variations:
       - tags: get,mlcommons,inference,src
         names:
         - inference-src
-      - tags: get,mlcommons,inference,loadgen,_custom-python,_keep-build
+      - tags: get,mlcommons,inference,loadgen,_custom-python,_keep-build,_inference
         names:
         - inference-loadgen
  
@@ -924,7 +924,7 @@ variations:
       - tags: get,mlcommons,inference,src
         names:
         - inference-src
-      - tags: get,mlcommons,inference,loadgen,_custom-python
+      - tags: get,mlcommons,inference,loadgen,_custom-python,_inference
         names:
         - inference-loadgen
       - tags: get,ml-model,dlrm,_pytorch
@@ -1074,7 +1074,7 @@ variations:
         - inference-src
 
       # Creates user conf for given SUT
-      - tags: generate,user-conf,mlperf,inference
+      - tags: generate,user-conf,mlperf,inference,_inference
         names:
         - user-conf-generator
       - tags: get,generic-sys-util,_rsync
diff --git a/script/app-mlperf-inference-mlcommons-cpp/meta.yaml b/script/app-mlperf-inference-mlcommons-cpp/meta.yaml
index dda32e172..06af3ddba 100644
--- a/script/app-mlperf-inference-mlcommons-cpp/meta.yaml
+++ b/script/app-mlperf-inference-mlcommons-cpp/meta.yaml
@@ -71,7 +71,7 @@ deps:
   # Install MLPerf inference dependencies
   
   # Install MLPerf loadgen
-  - tags: get,loadgen
+  - tags: get,loadgen,_inference
     names:
     - loadgen
     
@@ -129,7 +129,7 @@ deps:
     tags: get,ml-model,retinanet,_onnx,_fp32
 
   # Creates user conf for given SUT
-  - tags: generate,user-conf,mlperf,inference
+  - tags: generate,user-conf,mlperf,inference,_inference
     names:
     - user-conf-generator
   
diff --git a/script/app-mlperf-inference-mlcommons-python/meta.yaml b/script/app-mlperf-inference-mlcommons-python/meta.yaml
index a0380fec2..b01c7d989 100644
--- a/script/app-mlperf-inference-mlcommons-python/meta.yaml
+++ b/script/app-mlperf-inference-mlcommons-python/meta.yaml
@@ -684,7 +684,7 @@ deps:
   # Install MLPerf inference dependencies
 
   # Creates user conf for given SUT
-  - tags: generate,user-conf,mlperf,inference
+  - tags: generate,user-conf,mlperf,inference,_inference
     names:
       - user-conf-generator
     skip_if_env:
@@ -692,7 +692,7 @@ deps:
         - "yes"
 
   # Install MLPerf loadgen
-  - tags: get,loadgen
+  - tags: get,loadgen,_inference
     names:
       - loadgen
       - mlperf-inference-loadgen
diff --git a/script/app-mlperf-inference-nvidia/customize.py b/script/app-mlperf-inference-nvidia/customize.py
index cc11ce229..5d56c7f96 100644
--- a/script/app-mlperf-inference-nvidia/customize.py
+++ b/script/app-mlperf-inference-nvidia/customize.py
@@ -705,7 +705,16 @@ def preprocess(i):
     env['MLC_RUN_CMD'] = run_cmd
     env['MLC_RUN_DIR'] = env['MLC_MLPERF_INFERENCE_NVIDIA_CODE_PATH']
 
-#    print(env)
+    if '+LD_LIBRARY_PATH' not in env:
+        env['+LD_LIBRARY_PATH'] = []
+
+    if os.path.exists("/opt/hpcx/ucx/lib"):
+        env['+LD_LIBRARY_PATH'].append("/opt/hpcx/ucx/lib")
+
+    if os.path.exists("/opt/hpcx/ucc/lib"):
+        env['+LD_LIBRARY_PATH'].append("/opt/hpcx/ucc/lib")
+
+    #    print(env)
 
     return {'return': 0}
 
diff --git a/script/app-mlperf-inference-nvidia/meta.yaml b/script/app-mlperf-inference-nvidia/meta.yaml
index 472eb9383..00aa41969 100644
--- a/script/app-mlperf-inference-nvidia/meta.yaml
+++ b/script/app-mlperf-inference-nvidia/meta.yaml
@@ -272,7 +272,8 @@ deps:
       - run_harness
 
   - tags: get,generic-python-lib,_package.pycuda
-    version: "2022.2.2"
+    names:
+    - pycuda
 
   - tags: get,generic-python-lib,_package.nvmitten
     update_tags_from_env_with_prefix:
@@ -281,11 +282,10 @@ deps:
     enable_if_env:
       MLC_RUN_STATE_DOCKER:
         - 'yes'
+      MLC_ENV_NVMITTEN_DOCKER_WHEEL_PATH:
+        - 'yes'
 
   - tags: get,nvidia,mitten
-    skip_if_env:
-      MLC_RUN_STATE_DOCKER:
-        - 'yes'
     enable_if_env:
       MLC_NVIDIA_MITTEN_FROM_SRC:
         - 'yes'
@@ -351,6 +351,20 @@ post_deps:
 # Variations to customize dependencies
 variations:
   # MLPerf inference version
+  v5.0:
+    group: version
+    env:
+      MLC_MLPERF_INFERENCE_CODE_VERSION: "v5.0"
+      MLC_MLPERF_GPTJ_MODEL_FP8_PATH_SUFFIX: GPTJ-FP8-quantized
+      MLC_NVIDIA_MITTEN_FROM_SRC: "yes"
+      MLC_GIT_CHECKOUT: "98bb85df8e936219ec7acd10ce1d702147fb1e21"
+    adr:
+      pytorch:
+        tags: _for-nvidia-mlperf-inference-v5.0
+      pycuda:
+        version: "2024.1"
+      nvidia-inference-server:
+        tags: _mlcommons,_v5.0
   v4.1:
     group: version
     env:
@@ -418,9 +432,19 @@ variations:
     deps:
     - tags: get,generic-python-lib,_onnx-graphsurgeon
       version: 0.3.27
+
+  resnet50,v4.0:
+    - tags: get,generic-python-lib,_package.onnx
+      version: 1.13.1
+
+  resnet50,v4.1:
     - tags: get,generic-python-lib,_package.onnx
       version: 1.13.1
 
+  resnet50,v5.0:
+    - tags: get,generic-python-lib,_package.onnx
+      version: 1.17.0
+      
   retinanet:
     group: model
     env:
@@ -435,9 +459,20 @@ variations:
     - tags: get,generic-python-lib,_numpy
     - tags: get,generic-python-lib,_pycocotools
     - tags: get,generic-python-lib,_onnx-graphsurgeon
+    - tags: get,generic,sys-util,_cmake
+    - tags: get,generic-python-lib,_package.cmake
+    - tags: get,generic-python-lib,_package.sympy
+
+  retinanet,v5.0:
+    deps:
+    - tags: get,generic-python-lib,_package.onnx
+      version: 1.17.0
+
+  retinanet,v4.0:
+    deps:
     - tags: get,generic-python-lib,_package.onnx
       version: 1.14.1
-    - tags: get,generic-python-lib,_package.sympy
+  
 
   sdxl:
     new_env_keys:                                                                      
@@ -481,8 +516,8 @@ variations:
         names:
           - nvtx
       - tags: get,generic-python-lib,_package.cuda-python
-        version_max: 12.6.2
-        version_max_usable: 12.6.2  
+        version_max: "12.6.2"
+        version_max_usable: "12.6.2"  
         names:
           - cuda-python
       - tags: get,generic-python-lib,_package.ninja
@@ -494,38 +529,78 @@ variations:
       - tags: get,generic-python-lib,_package.colored
         names:
           - colored
-      - tags: get,generic-python-lib,_package.nvidia-ammo
-        names:
-          - nvidia-ammo
-        version: 0.7.4
-        env:
-          MLC_GENERIC_PYTHON_PIP_EXTRA_INDEX_URL: "https://pypi.nvidia.com"
-          MLC_GENERIC_PYTHON_PIP_EXTRA: "--no-cache-dir"
       - tags: get,generic-python-lib,_package.optimum
         names:
           - optimum
-      - tags: get,generic-python-lib,_package.onnx
-        names:
-          - onnx
-        version: 1.14.0
       - tags: get,generic-python-lib,_package.scipy
         names:
           - scipy
-        version: 1.10.1
-      - tags: get,generic-python-lib,_package.numpy
-        names:
-          - numpy
-        version_max: 1.22.99
-        version_max_usable: "1.22"
 
+  sdxl,v4.0:
+    deps:
+    - tags: get,generic-python-lib,_package.onnx
+      names:
+        - onnx
+      version: "1.14.0"
+    - tags: get,generic-python-lib,_package.numpy
+      names:
+        - numpy
+      version_max: "1.22.99"
+      version_max_usable: "1.22"
+    - tags: get,generic-python-lib,_package.nvidia-ammo
+      names:
+        - nvidia-ammo
+      version: "0.7.4"
+      env:
+        MLC_GENERIC_PYTHON_PIP_EXTRA_INDEX_URL: "https://pypi.nvidia.com"
+        MLC_GENERIC_PYTHON_PIP_EXTRA: "--no-cache-dir"
+        
   sdxl,v4.1:
     deps:
     - tags: get,generic-python-lib,_package.torchrec
-      version: 0.4.0
+      version: "0.4.0"
     - tags: get,generic-python-lib,_package.torchmetrics
-      version: 1.0.3
+      version: "1.0.3"
     - tags: get,generic-python-lib,_package.typeguard
+    - tags: get,generic-python-lib,_package.onnx
+      names:
+        - onnx
+      version: "1.14.0"
+    - tags: get,generic-python-lib,_package.numpy
+      names:
+        - numpy
+      version_max: "1.22.99"
+      version_max_usable: "1.22"
+    - tags: get,generic-python-lib,_package.nvidia-ammo
+      names:
+        - nvidia-ammo
+      version: "0.7.4"
+      env:
+        MLC_GENERIC_PYTHON_PIP_EXTRA_INDEX_URL: "https://pypi.nvidia.com"
+        MLC_GENERIC_PYTHON_PIP_EXTRA: "--no-cache-dir"
+    - tags: get,generic-python-lib,_package.scipy
+      names:
+        - scipy
+      version: "1.10.1"
 
+  sdxl,v5.0: 
+    # nvidia-ammo is decommisioned and model-opt is being used which is built with TRTLLM
+    deps:
+    - tags: get,generic-python-lib,_package.torchrec
+      version: "0.6.0"
+    - tags: get,generic-python-lib,_package.torchmetrics
+      version: "1.0.3"
+    - tags: get,generic-python-lib,_package.typeguard
+    - tags: get,generic-python-lib,_package.onnx
+      names:
+        - onnx
+      version: "1.17.0"
+    - tags: get,generic-python-lib,_package.numpy
+      names:
+        - numpy
+      version_max: "1.26.99"
+      version_max_usable: "1.26.4"
+      
   bert_:
     deps:
     - tags: get,generic-python-lib,_transformers
diff --git a/script/app-mlperf-inference-qualcomm/meta.yaml b/script/app-mlperf-inference-qualcomm/meta.yaml
index 1e508e0e6..2e0193355 100644
--- a/script/app-mlperf-inference-qualcomm/meta.yaml
+++ b/script/app-mlperf-inference-qualcomm/meta.yaml
@@ -111,12 +111,12 @@ deps:
     - inference-src
 
   # Download MLPerf inference loadgen
-  - tags: get,mlcommons,inference,loadgen
+  - tags: get,mlcommons,inference,loadgen,_inference
     names:
     - inference-loadgen
 
   # Creates user conf for given SUT
-  - tags: generate,user-conf,mlperf,inference
+  - tags: generate,user-conf,mlperf,inference,_inference
     names:
     - user-conf-generator
 
diff --git a/script/app-mlperf-inference-redhat/meta.yaml b/script/app-mlperf-inference-redhat/meta.yaml
index 55af68d65..1d32af174 100644
--- a/script/app-mlperf-inference-redhat/meta.yaml
+++ b/script/app-mlperf-inference-redhat/meta.yaml
@@ -91,12 +91,12 @@ deps:
     - inference-src
 
   # Download MLPerf inference loadgen
-  - tags: get,mlcommons,inference,loadgen
+  - tags: get,mlcommons,inference,loadgen,_inference
     names:
     - inference-loadgen
 
   # Creates user conf for given SUT
-  - tags: generate,user-conf,mlperf,inference
+  - tags: generate,user-conf,mlperf,inference,_inference
     names:
     - user-conf-generator
 
diff --git a/script/app-mlperf-inference/meta.yaml b/script/app-mlperf-inference/meta.yaml
index 6a4b6cf3b..dcfea1431 100644
--- a/script/app-mlperf-inference/meta.yaml
+++ b/script/app-mlperf-inference/meta.yaml
@@ -382,6 +382,29 @@ variations:
         env:
             MLC_ENV_NVMITTEN_DOCKER_WHEEL_PATH: '/opt/nvmitten-0.1.3b0-cp310-cp310-linux_aarch64.whl'
 
+  nvidia-original,r5.0_default:
+    env:
+      MLC_NVIDIA_MITTEN_FROM_SRC: 'yes'
+    docker:
+      os_version: "24.04"
+      user: 'ubuntu'
+      build_deps:
+        - tags: detect,os
+      image_name: mlperf-inference-nvidia-v5.0-common
+      build_env:
+        ENV: release
+        
+    update_meta_if_env:
+      - enable_if_env:
+          MLC_HOST_PLATFORM_FLAVOR:
+            - x86_64
+        docker:
+          base_image: nvcr.io/nvidia/mlperf/mlperf-inference:mlpinf-v5.0-cuda12.8-pytorch25.01-ubuntu24.04-x86_64-release
+      - skip_if_env:
+          MLC_HOST_PLATFORM_FLAVOR:
+            - x86_64
+        docker:
+          base_image: nvcr.io/nvidia/mlperf/mlperf-inference:mlpinf-v5.0-cuda12.8-pytorch25.01-ubuntu24.04-aarch64-Grace-release
 
   nvidia-original,gptj_:
     env:
@@ -424,6 +447,14 @@ variations:
           update_tags_from_env_with_prefix:
             _tp-size.:
               - MLC_NVIDIA_TP_SIZE
+  
+  nvidia-original,r5.0_default,gptj_:
+    docker:
+      deps:
+        - tags: get,ml-model,gptj,_nvidia,_fp8
+          update_tags_from_env_with_prefix:
+            _tp-size.:
+              - MLC_NVIDIA_TP_SIZE
         
   
   nvidia-original,r4.1-dev_default,llama2-70b_:
@@ -446,6 +477,14 @@ variations:
               - MLC_NVIDIA_TP_SIZE
     env:
       BUILD_TRTLLM: 1
+  
+  nvidia-original,r5.0_default,llama2-70b_:
+    docker:
+      deps:
+        - tags: get,ml-model,llama2-70b,_nvidia,_fp8
+          update_tags_from_env_with_prefix:
+            _tp-size.:
+              - MLC_NVIDIA_TP_SIZE
 
   nvidia-original:
     docker:
@@ -1275,7 +1314,7 @@ variations:
       mounts:
         - "${{ MLC_ML_MODEL_FILE_WITH_PATH }}:${{ MLC_ML_MODEL_FILE_WITH_PATH }}"
         - "${{ DLRM_DATA_PATH }}:${{ DLRM_DATA_PATH }}"
-      dockerfile_env:
+      env:
         MLC_ML_MODEL_FILE_WITH_PATH: "on"
 
 
@@ -1781,6 +1820,8 @@ variations:
       nvidia-inference-server:
         version: r4.1
         tags: _go
+      nvidia-harness:   
+        tags: _v4.0
       intel-harness:
         tags: _v4.1
       nvidia-scratch-space:
@@ -1802,6 +1843,8 @@ variations:
       nvidia-inference-server:
         version: r4.0
         tags: _mlcommons
+      nvidia-harness:   
+        tags: _v4.0
       intel-harness:
         tags: _v4.1
       inference-src:
@@ -1813,6 +1856,30 @@ variations:
       MLC_REGENERATE_MEASURE_FILES: 'yes'
     env:
       MLC_ENV_NVMITTEN_DOCKER_WHEEL_PATH: '/opt/nvmitten-0.1.3b0-cp38-cp38-linux_x86_64.whl'
+  
+  r5.0_default:
+    group:
+      reproducibility
+    add_deps_recursive:
+      nvidia-inference-common-code:
+        tags: _mlcommons,_v5.0
+      nvidia-inference-server:
+        version: r5.0
+        tags: _mlcommons
+      nvidia-harness:   
+        tags: _v5.0
+      intel-harness:
+        tags: _v4.1
+      inference-src:
+         version: r5.0
+      nvidia-scratch-space:
+        tags: _version.5.0
+      pycuda:
+        version: "2024.1"
+    default_env:
+      MLC_SKIP_SYS_UTILS: 'yes'
+      MLC_REGENERATE_MEASURE_FILES: 'yes'
+      MLC_MLPERF_INFERENCE_VERSION: '5.0'
 
 
 invalid_variation_combinations:
diff --git a/script/build-dockerfile/customize.py b/script/build-dockerfile/customize.py
index a3d32b247..b240e4164 100644
--- a/script/build-dockerfile/customize.py
+++ b/script/build-dockerfile/customize.py
@@ -228,7 +228,7 @@ def preprocess(i):
         f.write('RUN ' + env['MLC_DOCKER_EXTRA_SYS_DEPS'] + EOL)
 
     if env['MLC_DOCKER_OS'] == "ubuntu":
-        if int(env['MLC_DOCKER_OS_VERSION'].split('.')[0]) >= 23:
+        if int(str(env['MLC_DOCKER_OS_VERSION']).split('.')[0]) >= 23:
             if "--break-system-packages" not in env.get(
                     'MLC_DOCKER_PIP_INSTALL_EXTRA_FLAGS', ''):
                 env['MLC_DOCKER_PIP_INSTALL_EXTRA_FLAGS'] = " --break-system-packages"
@@ -246,6 +246,12 @@ def preprocess(i):
 
     for key, value in config['ENV'].items():
         f.write('ENV ' + key + "=\"" + value + "\"" + EOL)
+
+    dockerfile_build_env = env.get('MLC_DOCKERFILE_BUILD_ENV', {})
+    for key in dockerfile_build_env:
+        value = dockerfile_build_env[key]
+        f.write('ENV ' + key + "=\"" + value + "\"" + EOL)
+
     for cmd in config['RUN_CMDS']:
         f.write('RUN ' + cmd + EOL)
 
@@ -257,7 +263,8 @@ def preprocess(i):
             'MLC_DOCKER_USE_DEFAULT_USER', '') == '':
         env['MLC_DOCKER_USE_DEFAULT_USER'] = 'yes'
 
-    if docker_user and not is_true(env.get('MLC_DOCKER_USE_DEFAULT_USER', '')):
+    if docker_user and not is_true(
+            env.get('MLC_DOCKER_USE_DEFAULT_USER', '') and docker_user != 'root'):
 
         f.write('RUN groupadd -g $GID -o ' + docker_group + EOL)
 
@@ -267,11 +274,15 @@ def preprocess(i):
         user_shell = json.loads(shell)
         f.write(f"""RUN (id -u {docker_user} > /dev/null 2>&1 && usermod -u $UID {docker_user}) || useradd """ + DOCKER_USER_ID + DOCKER_GROUP + ' --create-home --shell ' + user_shell[0] + ' '
                 + docker_user + EOL)
+        # f.write(f'RUN usermod -aG sudo {docker_user}' + EOL)
+
         f.write(
-            'RUN echo "' +
-            docker_user +
-            ' ALL=(ALL) NOPASSWD: ALL" >> /etc/sudoers' +
-            EOL)
+            # create the file with both lines and a trailing newline
+            f"RUN printf '{docker_user} ALL=(ALL) NOPASSWD: ALL\\n"
+            f"Defaults:{docker_user} !requiretty\\n' "
+            f">> /etc/sudoers " + EOL
+        )
+
         f.write('USER ' + docker_user + ":" + docker_group + EOL)
         f.write(f"""ENV HOME=/home/{docker_user}""" + EOL)
 
diff --git a/script/build-dockerfile/meta.yaml b/script/build-dockerfile/meta.yaml
index 68ea20689..6c91a29dd 100644
--- a/script/build-dockerfile/meta.yaml
+++ b/script/build-dockerfile/meta.yaml
@@ -37,6 +37,7 @@ input_mapping:
   docker_os: MLC_DOCKER_OS
   docker_os_version: MLC_DOCKER_OS_VERSION
   dockerfile_env: MLC_DOCKERFILE_ENV
+  dockerfile_build_env: MLC_DOCKERFILE_BUILD_ENV
   extra_sys_deps: MLC_DOCKER_EXTRA_SYS_DEPS
   fake_docker_deps: MLC_DOCKER_FAKE_DEPS
   fake_run_option: MLC_DOCKER_FAKE_RUN_OPTION
diff --git a/script/build-mlperf-inference-server-nvidia/meta.yaml b/script/build-mlperf-inference-server-nvidia/meta.yaml
index e8e49748b..fb345bc1f 100644
--- a/script/build-mlperf-inference-server-nvidia/meta.yaml
+++ b/script/build-mlperf-inference-server-nvidia/meta.yaml
@@ -111,18 +111,20 @@ deps:
 
   # Detect pycuda
   - tags: get,generic-python-lib,_pycuda
+    names:
+    - pycuda
     version: "2022.2.2"
     skip_if_env:
       MLC_RUN_STATE_DOCKER:
         - 'yes'
-        - True
-        - 'True'
 
   # Detect opencv-python
   - tags: get,generic-python-lib,_opencv-python
 
   # Detect nvidia-dali
   - tags: get,generic-python-lib,_nvidia-dali
+    version_max: 1.48
+    version_max_usable: 1.48
 
   # Get Nvidia scratch space where data and models get downloaded
   - tags: get,mlperf,inference,nvidia,scratch,space
@@ -224,6 +226,11 @@ variations:
             - x86_64
           MLC_PYTHON_MINOR_VERSION:
             - 8
+    
+  r5.0:
+    add_deps_recursive:
+      pycuda:
+        version: "2024.1"
 
 versions:
   r2.1: {}
@@ -333,7 +340,7 @@ versions:
   r4.1:
     default_env:
       BUILD_TRTLLM: 1
-
+  
 docker:
   skip_run_cmd: 'no'
   all_gpus: 'yes'
diff --git a/script/build-mlperf-inference-server-nvidia/run.sh b/script/build-mlperf-inference-server-nvidia/run.sh
index ac990aa62..c5f4e1a8a 100644
--- a/script/build-mlperf-inference-server-nvidia/run.sh
+++ b/script/build-mlperf-inference-server-nvidia/run.sh
@@ -8,9 +8,17 @@ if [[ ${MLC_MAKE_CLEAN} == "yes" ]]; then
 fi
 
 if [[ ${MLC_MLPERF_DEVICE} == "inferentia" ]]; then
+ echo "inferencia"
  make prebuild
 fi
 
+# Perform sed replacement only if version is 5.0
+if [[ "${MLC_MLPERF_INFERENCE_VERSION}" == "5.0" ]]; then
+  echo "Replacing /work/ with ${MLC_MLPERF_INFERENCE_NVIDIA_CODE_PATH} in all files..."
+  find . -type f -exec sed -i "s|/work/|${MLC_MLPERF_INFERENCE_NVIDIA_CODE_PATH}/|g" {} +
+fi
+
+echo ${MLC_MAKE_BUILD_COMMAND}
 SKIP_DRIVER_CHECK=1 make ${MLC_MAKE_BUILD_COMMAND}
 
 test $? -eq 0 || exit $?
diff --git a/script/detect-sudo/customize.py b/script/detect-sudo/customize.py
index a749acd2a..104d8b781 100644
--- a/script/detect-sudo/customize.py
+++ b/script/detect-sudo/customize.py
@@ -27,8 +27,8 @@ def preprocess(i):
         env['MLC_SUDO'] = ''  # root user does not need sudo
         env['MLC_SUDO_USER'] = "yes"
     else:
-        if can_execute_sudo_without_password(
-                logger) or prompt_sudo(logger) == 0:
+        if not is_true(env.get('MLC_SKIP_SUDO')) and (can_execute_sudo_without_password(
+                logger) or prompt_sudo(logger) == 0):
             env['MLC_SUDO_USER'] = "yes"
             env['MLC_SUDO'] = 'sudo'
 
@@ -129,8 +129,7 @@ def get_input():
 
 
 def prompt_sudo(logger):
-    if os.geteuid() != 0 and not is_user_in_sudo_group(
-            logger):  # No sudo required for root user
+    if os.geteuid() != 0:  # No sudo required for root user
 
         # Prompt for the password
 
@@ -171,10 +170,11 @@ def prompt_sudo(logger):
         except subprocess.TimeoutExpired:
             logger.info("Timedout")
             reset_terminal()  # Reset terminal to sane state
-            if not prompt_retry():  # If the user chooses not to retry or times out
+            if not prompt_retry(
+                    logger):  # If the user chooses not to retry or times out
                 return -1
         except subprocess.CalledProcessError as e:
-            logger.error(f"Command failed: {e.output.decode('utf-8')}")
+            logger.error(f"Command failed: {e.output}")
             reset_terminal()  # Reset terminal in case of failure
             return -1
         except Exception as e:
diff --git a/script/download-and-extract/meta.yaml b/script/download-and-extract/meta.yaml
index d2137d71c..96ff8c6a8 100644
--- a/script/download-and-extract/meta.yaml
+++ b/script/download-and-extract/meta.yaml
@@ -85,11 +85,19 @@ variations:
     default: 'true'
     env:
       MLC_EXTRACT_REMOVE_EXTRACTED: 'no'
+    adr:
+      extract-script:
+        tags:
+          _keep
     group: keep
-  no-remove-extracted:
+  remove-extracted:
     env:
-      MLC_EXTRACT_REMOVE_EXTRACTED: 'no'
+      MLC_EXTRACT_REMOVE_EXTRACTED: 'yes'
     group: keep
+    adr:
+      extract-script:
+        tags:
+          _remove-extracted
   rclone:
     add_deps:
       download-script:
diff --git a/script/extract-file/meta.yaml b/script/extract-file/meta.yaml
index 79f1538c3..b4cbc9131 100644
--- a/script/extract-file/meta.yaml
+++ b/script/extract-file/meta.yaml
@@ -41,10 +41,10 @@ variations:
     default: true
     env:
       MLC_EXTRACT_REMOVE_EXTRACTED: 'no'
-  no-remove-extracted:
+  remove-extracted:
     group: keep
     env:
-      MLC_EXTRACT_REMOVE_EXTRACTED: 'no'
+      MLC_EXTRACT_REMOVE_EXTRACTED: 'yes'
   path.#:
     env:
       MLC_EXTRACT_FILEPATH: '#'
diff --git a/script/gemini_call/customize.py b/script/gemini_call/customize.py
new file mode 100644
index 000000000..592ff9fa0
--- /dev/null
+++ b/script/gemini_call/customize.py
@@ -0,0 +1,63 @@
+from mlc import utils
+import os
+import json
+import yaml
+
+
+def write_gemini_yaml(model, system_prompt, user_prompt,
+                      filename='gemini-prompt.yaml'):
+    data = {
+        'model': model,
+        'contents': [
+            {
+                'role': 'user',
+                'parts': [
+                    {'text': f"{system_prompt}\n\n{user_prompt}"}
+                ]
+            }
+        ],
+        'generationConfig': {
+            'temperature': 0.7,
+            'maxOutputTokens': 200
+        }
+    }
+
+    with open(filename, 'w', encoding='utf-8') as f:
+        yaml.dump(data, f, sort_keys=False, allow_unicode=True)
+
+
+def preprocess(i):
+    env = i['env']
+    state = i['state']
+
+    if 'MLC_GEMINI_CONFIG_PATH' not in env or not os.path.exists(
+            env['MLC_GEMINI_CONFIG_PATH']):
+        if 'user_prompt' in state:
+            model = env.get('MLC_GEMINI_MODEL', 'gemini-2.0-flash')
+            user_prompt = state['user_prompt']
+            system_prompt = state.get(
+                'system_prompt',
+                'You are an AI agent expected to answer questions correctly')
+            write_gemini_yaml(
+                model,
+                system_prompt,
+                user_prompt,
+                'tmp-gemini-prompt.yaml')
+            env['MLC_GEMINI_CONFIG_PATH'] = 'tmp-gemini-prompt.yaml'
+
+    env['MLC_RUN_CMD'] = f'{env["MLC_PYTHON_BIN_WITH_PATH"]} "{os.path.join(env["MLC_TMP_CURRENT_SCRIPT_PATH"], "gemini_call.py")}"'
+
+    return {'return': 0}
+
+
+def postprocess(i):
+    env = i['env']
+    state = i['state']
+
+    filename = 'tmp-gemini-results.json'
+    with open(filename, 'r', encoding='utf-8') as f:
+        data = json.load(f)
+
+    state['MLC_GEMINI_RESPONSE'] = data['content']
+    os_info = i['os_info']
+    return {'return': 0}
diff --git a/script/gemini_call/gemini_call.py b/script/gemini_call/gemini_call.py
new file mode 100644
index 000000000..1f4791b97
--- /dev/null
+++ b/script/gemini_call/gemini_call.py
@@ -0,0 +1,95 @@
+import requests
+import os
+import json
+import yaml
+
+import yaml
+
+
+def extract_prompts(yaml_path):
+    with open(yaml_path, 'r', encoding='utf-8') as f:
+        data = yaml.safe_load(f)
+
+    full_text = data['contents'][0]['parts'][0]['text']
+
+    # Split at "Question Text:"
+    if "Question Text:" not in full_text:
+        raise ValueError("Expected 'Question Text:' marker not found.")
+
+    system_prompt, question_part = full_text.split("Question Text:", 1)
+
+    # Trim whitespace
+    system_prompt = system_prompt.strip()
+    user_prompt = question_part.strip()
+
+    return system_prompt, user_prompt
+
+
+def gemini_call(message=None):
+    try:
+        api_key = os.environ['MLC_GEMINI_API_KEY']
+        url = f"https://generativelanguage.googleapis.com/v1beta/models/gemini-2.0-flash:generateContent?key={api_key}"
+        config_path = os.environ.get('MLC_GEMINI_CONFIG_PATH')
+        # Load config if it exists
+        if config_path and os.path.exists(config_path):
+            try:
+                with open(config_path, 'r', encoding="utf-8") as file:
+                    data = yaml.safe_load(file)
+            except Exception as e:
+                return {"error": f"Error reading config file: {str(e)}"}
+
+            if os.environ.get('MLC_GEMINI_CONFIG_MODIFY', '') == 'yes':
+                try:
+                    data['messages'][1]['content'] = data['messages'][1]['content'].replace(
+                        "{{ MESSAGE }}", message or "")
+                except Exception as e:
+                    return {"error": f"Config format issue: {str(e)}"}
+        # Load prompts
+        system_prompt, user_prompt = extract_prompts(config_path)
+        # Combine both in first message
+        full_prompt = f"{system_prompt}\n\n{user_prompt}"
+
+        data = {
+            "contents": [
+                {
+                    "role": "user",
+                    "parts": [
+                        {"text": full_prompt}
+                    ]
+                }
+            ]
+        }
+
+        headers = {
+            'Content-Type': 'application/json'
+        }
+
+        response = requests.post(url, json=data, headers=headers)
+        response.raise_for_status()
+        result = response.json()
+
+        content = result['candidates'][0]['content']['parts'][0]['text']
+
+        with open('tmp-gemini-results.json', 'w', encoding='utf-8') as f:
+            json.dump({'content': content}, f, ensure_ascii=False, indent=2)
+
+        return {"content": content}
+
+    except requests.exceptions.RequestException as e:
+        return {"error": f"Request error: {str(e)}"}
+
+    except KeyError as e:
+        return {"error": f"Missing key in response: {str(e)}"}
+
+    except Exception as e:
+        return {"error": f"Unexpected error: {str(e)}"}
+
+
+def main():
+    result = gemini_call()
+    if 'error' in result:
+        raise Exception(result['error'])
+
+
+if __name__ == '__main__':
+    main()
diff --git a/script/gemini_call/meta.yaml b/script/gemini_call/meta.yaml
new file mode 100644
index 000000000..e663a65c0
--- /dev/null
+++ b/script/gemini_call/meta.yaml
@@ -0,0 +1,36 @@
+alias: gemini_call
+automation_alias: script
+automation_uid: 5b4e0237da074764
+category: MLC Script Template
+deps:
+  - tags: get,python3
+    names:
+    - python
+    - python3
+new_env_keys: []
+new_state_keys:
+- MLC_GEMINI_RESPONSE
+post_deps: []
+posthook_deps: []
+prehook_deps: []
+tags:
+- gemini-call
+- query
+input_mapping:
+  api_key: MLC_GEMINI_API_KEY
+  config_path: MLC_GEMINI_CONFIG_PATH
+  system_prompt: MLC_GEMINI_SYSTEM_PROMPT
+  user_prompt: MLC_GEMINI_USER_PROMPT
+  model: MLC_GEMINI_MODEL
+tests:
+  run_inputs: []
+uid: 1cfe3d0658364a2b
+variations:
+  gemini:
+    group: api_provider
+    default: true
+    env:
+      MLC_GEMINI_API_URL: 'https://generativelanguage.googleapis.com/v1beta/models/gemini-2.0-flash:generateContent?key='
+
+
+
diff --git a/script/gemini_call/run.bat b/script/gemini_call/run.bat
new file mode 100644
index 000000000..4509961ce
--- /dev/null
+++ b/script/gemini_call/run.bat
@@ -0,0 +1 @@
+%MLC_RUN_CMD%
\ No newline at end of file
diff --git a/script/gemini_call/run.sh b/script/gemini_call/run.sh
new file mode 100644
index 000000000..fa21de70c
--- /dev/null
+++ b/script/gemini_call/run.sh
@@ -0,0 +1,17 @@
+#!/bin/bash
+function exit_if_error() {
+  test $? -eq 0 || exit $?
+}
+
+function run() {
+  echo "Running: "
+  echo "$1"
+  echo ""
+  if [[ ${MLC_FAKE_RUN} != 'yes' ]]; then
+    eval "$1"
+    exit_if_error
+  fi
+}
+
+#Add your run commands here...
+# run "$MLC_RUN_CMD"
diff --git a/script/generate-mlperf-inference-submission/meta.yaml b/script/generate-mlperf-inference-submission/meta.yaml
index c68bc5a37..480fbd008 100644
--- a/script/generate-mlperf-inference-submission/meta.yaml
+++ b/script/generate-mlperf-inference-submission/meta.yaml
@@ -13,12 +13,8 @@ deps:
   - python
   - python3
   tags: get,python3
-- names:
-  - inference-src
-  tags: mlcommons,inference,src
 - tags: get,sut,system-description
 - tags: install,pip-package,for-mlc-python,_package.tabulate
-- tags: get,mlperf,inference,utils
 - names:
   - get-mlperf-results-dir
   skip_if_env:
@@ -97,18 +93,51 @@ post_deps:
   skip_if_env:
     MLC_SKIP_TRUNCATE_ACCURACY:
     - 'yes'
+  names:
+    - truncate-mlperf-accuracy-log
   tags: accuracy,truncate,mlc
 - enable_if_env:
     MLC_RUN_MLPERF_SUBMISSION_PREPROCESSOR:
     - 'yes'
+  names:
+    - preprocess-mlperf-submission
   tags: preprocess,mlperf,submission
 - skip_if_env:
     MLC_RUN_SUBMISSION_CHECKER:
     - 'no'
   names:
   - mlperf-inference-submission-checker
+  - mlperf-submission-checker
   - submission-checker
   tags: submission,inference,checker,mlc
+variations:
+  inference:
+    default: true
+    add_deps_recursive:
+      truncate-mlperf-accuracy-log:
+        tags: _inference
+      preprocess-mlperf-submission:
+        tags: _inference
+      mlperf-inference-submission-checker:
+        tags: _inference
+    deps:
+      - names:
+        - inference-src
+        tags: mlcommons,inference,src
+      - tags: get,mlperf,inference,utils
+  automotive:
+    add_deps_recursive:
+      truncate-mlperf-accuracy-log:
+        tags: _automotive
+      preprocess-mlperf-submission:
+        tags: _automotive
+      mlperf-inference-submission-checker:
+        tags: _automotive
+    deps:
+      - names:
+        - automotive-src
+        tags: mlcommons,automotive,src
+      - tags: get,mlperf,automotive,utils
 tags:
 - generate
 - submission
diff --git a/script/generate-mlperf-inference-user-conf/customize.py b/script/generate-mlperf-inference-user-conf/customize.py
index b08f0b0fb..2c93af586 100644
--- a/script/generate-mlperf-inference-user-conf/customize.py
+++ b/script/generate-mlperf-inference-user-conf/customize.py
@@ -100,7 +100,7 @@ def preprocess(i):
     query_count = None
 
     value = None
-    if scenario in ['Offline', 'Server']:
+    if scenario in ['Offline', 'Server', 'ConstantStream']:
         metric = "target_qps"
         tolerance = 1.01
         # value = env.get('MLC_MLPERF_LOADGEN_SERVER_TARGET_QPS') if scenario == "Server" else env.get('MLC_MLPERF_LOADGEN_OFFLINE_TARGET_QPS')
@@ -343,7 +343,7 @@ def preprocess(i):
             ".sample_concatenate_permutation = 0" + "\n"
         max_duration_fast_s = int(env.get('MLC_MLPERF_MAX_DURATION_FAST', 120))
         max_duration_fast = str(max_duration_fast_s * 1000)  # in milliseconds
-        if scenario == "Server":
+        if scenario == "Server" or scenario == "ConstantStream":
             user_conf += ml_model_name + "." + scenario + \
                 f".max_duration = {max_duration_fast}" + "\n"
             target_qps = conf['target_qps']
@@ -368,9 +368,13 @@ def preprocess(i):
                 user_conf += ml_model_name + "." + scenario + ".min_duration = " + \
                     env['MLC_MLPERF_INFERENCE_MIN_DURATION'] + " \n"
             elif not is_false(env.get('MLC_MLPERF_USE_MAX_DURATION', 'yes')) and not is_true(env.get(
-                    'MLC_MLPERF_MODEL_EQUAL_ISSUE_MODE', 'no')):
+                    'MLC_MLPERF_MODEL_EQUAL_ISSUE_MODE', 'no')) and env.get('MLC_MLPERF_SINGLESTREAM_TARGET_LATENCY_PERCENTILE') != '99.9':
                 user_conf += ml_model_name + "." + scenario + \
                     f".max_duration = {max_duration_valid}" + "\n"
+            if scenario in ["SingleStream", "ConstantStream"] and env.get('MLC_MLPERF_SINGLESTREAM_TARGET_LATENCY_PERCENTILE') == '99.9' and env.get(
+                    'MLC_MLPERF_DEFAULT_MAX_QUERY_COUNT', '') != '' and env.get('MLC_MLPERF_TARGET_LATENCY', '') == '':
+                user_conf += ml_model_name + "." + scenario + \
+                    f".max_query_count = {env.get('MLC_MLPERF_DEFAULT_MAX_QUERY_COUNT')}" + "\n"
             if scenario == "MultiStream":
                 user_conf += ml_model_name + "." + scenario + ".min_query_count = " + \
                     env.get(
diff --git a/script/generate-mlperf-inference-user-conf/meta.yaml b/script/generate-mlperf-inference-user-conf/meta.yaml
index fbba97b33..18fbec442 100644
--- a/script/generate-mlperf-inference-user-conf/meta.yaml
+++ b/script/generate-mlperf-inference-user-conf/meta.yaml
@@ -47,6 +47,7 @@ input_mapping:
   target_latency: MLC_MLPERF_LOADGEN_TARGET_LATENCY
   offline_target_qps: MLC_MLPERF_LOADGEN_OFFLINE_TARGET_QPS
   server_target_qps: MLC_MLPERF_LOADGEN_SERVER_TARGET_QPS
+  constantstream_target_qps: MLC_MLPERF_LOADGEN_CONSTANTSTREAM_TARGET_QPS
   singlestream_target_latency: MLC_MLPERF_LOADGEN_SINGLESTREAM_TARGET_LATENCY
   multistream_target_latency: MLC_MLPERF_LOADGEN_MULTISTREAM_TARGET_LATENCY
   performance_sample_count: MLC_MLPERF_LOADGEN_PERFORMANCE_SAMPLE_COUNT
@@ -84,13 +85,24 @@ deps:
       OUTPUT_BASE_DIR:
         - "on"
 
-  ########################################################################
-  # Install MLPerf inference dependencies
-
-  # Download MLPerf inference source
-  - tags: get,mlcommons,inference,src
-    names:
-    - inference-src
-
   # Get SUT configs (System Under Test)
   - tags: get,sut,configs
+
+variations:
+  inference:
+    default: true
+    group: benchmark_wg
+    env:
+      MLC_BENCHMARK_GROUP: inference
+    deps:
+      - tags: get,mlcommons,inference,src
+        names:
+        - inference-src
+  automotive:
+    group: benchmark_wg
+    env:
+      MLC_BENCHMARK_GROUP: automotive
+    deps:
+      - tags: get,mlcommons,automotive,src
+        names:
+        - automotive-src
\ No newline at end of file
diff --git a/script/get-dataset-cognata-mlcommons/customize.py b/script/get-dataset-cognata-mlcommons/customize.py
index 1a070e0ab..64406d44e 100644
--- a/script/get-dataset-cognata-mlcommons/customize.py
+++ b/script/get-dataset-cognata-mlcommons/customize.py
@@ -8,6 +8,10 @@ def preprocess(i):
 
     env = i['env']
 
+    if env.get('MLC_COGNATA_DATASET_TYPE', '') == "release":
+        env['MLC_TMP_REQUIRE_DOWNLOAD'] = "yes"
+        return {'return': 0}
+
     mlc_cache_dataset_path = env.get(
         'MLC_CUSTOM_CACHE_ENTRY_DATASET_MLCOMMONS_COGNATA_PATH', '').strip()
 
@@ -28,11 +32,6 @@ def preprocess(i):
     env['MLC_DATASET_COGNATA_POC_TEXT_MD5_FILE_PATH'] = os.path.join(
         i['run_script_input']['path'], 'checksums', 'cognata_poc.txt')
 
-    # Check if user requests path not in CM cache
-    #
-    # --path (env MLC_TMP_PATH) shows where to store Cognata data set instead of CM cahe
-    # --import tells CM to import existing Cognata from a given path and skip further download/processing
-    #
     import_path = env.get(
         'MLC_DATASET_MLCOMMONS_COGNATA_IMPORT_PATH',
         '').strip()
@@ -66,6 +65,9 @@ def postprocess(i):
 
     logger = automation.logger
 
+    if env.get('MLC_COGNATA_DATASET_TYPE', '') == "release":
+        return {'return': 0}
+
     cur_dir = os.getcwd()
 
     quiet = is_true(env.get('MLC_QUIET', False))
@@ -75,7 +77,7 @@ def postprocess(i):
 
     if not os.path.isdir(mlc_cache_dataset_path):
         return {
-            'return': 1, 'error': 'Dataset corrupted - CM cache path not found: {}'.format(mlc_cache_dataset_path)}
+            'return': 1, 'error': 'Dataset corrupted - MLC cache path not found: {}'.format(mlc_cache_dataset_path)}
 
     if env.get('MLC_DATASET_MLCOMMONS_COGNATA_FILE_NAMES', '') == '':
         env['MLC_DATASET_MLCOMMONS_COGNATA_PATH'] = os.path.dirname(
diff --git a/script/get-dataset-cognata-mlcommons/meta.yaml b/script/get-dataset-cognata-mlcommons/meta.yaml
index 309b6ba90..ecb10799a 100644
--- a/script/get-dataset-cognata-mlcommons/meta.yaml
+++ b/script/get-dataset-cognata-mlcommons/meta.yaml
@@ -48,9 +48,11 @@ deps:
   - custom-cache-entry-mlcommons-cognata-dataset
   tags: create,custom,cache,entry
   extra_cache_tags: dataset,cognata,mlcommons-cognata
-  skip_if_env:
+  skip_if_any_env:
     MLC_DATASET_MLCOMMONS_COGNATA_FILE_NAMES:
     - 'off'
+    MLC_DOWNLOAD_SRC: 
+    - mlcommons
   env_key: DATASET_MLCOMMONS_COGNATA
   # this script will prepare env MLC_CUSTOM_CACHE_ENTRY_{env_key}_PATH
 
@@ -58,9 +60,11 @@ deps:
 prehook_deps:
 - names:
   - gdrive-downloader-cognata
-  skip_if_env:
+  skip_if_any_env:
     MLC_DATASET_MLCOMMONS_COGNATA_FILE_NAMES:
     - 'on'
+    MLC_DOWNLOAD_SRC: 
+    - mlcommons
   enable_if_env:
     MLC_DATASET_MLCOMMONS_COGNATA_IMPORTED:
     - 'no'
@@ -76,9 +80,11 @@ prehook_deps:
 
 - names:
   - rclone-downloader-cognata
-  skip_if_env:
+  skip_if_any_env:
     MLC_DATASET_MLCOMMONS_COGNATA_FILE_NAMES:
     - 'on'
+    MLC_DOWNLOAD_SRC: 
+    - mlcommons
   enable_if_env:
     MLC_DATASET_MLCOMMONS_COGNATA_IMPORTED:
     - 'no'
@@ -101,27 +107,33 @@ prehook_deps:
   - python
   - python3
   tags: get,python3
-  skip_if_env:
+  skip_if_any_env:
     MLC_DATASET_MLCOMMONS_COGNATA_IMPORTED:
     - 'yes'
+    MLC_DOWNLOAD_SRC: 
+    - mlcommons
   enable_if_env:
     MLC_DATASET_MLCOMMONS_COGNATA_FILE_NAMES:
       - 'on'
 
 # Python package to read/write Excel files
 - tags: get,generic-python-lib,_package.openpyxl
-  skip_if_env:
+  skip_if_any_env:
     MLC_DATASET_MLCOMMONS_COGNATA_IMPORTED:
     - 'yes'
+    MLC_DOWNLOAD_SRC: 
+    - mlcommons
   enable_if_env:
     MLC_DATASET_MLCOMMONS_COGNATA_FILE_NAMES:
       - 'on'
 
 # Tool to download large files
 - tags: get,aria2
-  skip_if_env:
+  skip_if_any_env:
     MLC_DATASET_MLCOMMONS_COGNATA_IMPORTED:
     - 'yes'
+    MLC_DOWNLOAD_SRC: 
+    - mlcommons
   enable_if_env:
     MLC_DATASET_MLCOMMONS_COGNATA_FILE_NAMES:
     - 'on'
@@ -143,6 +155,11 @@ variations:
       MLC_DATASET_MLCOMMONS_COGNATA_GROUP_NAMES: "Cognata_Camera_01_8M"
       MLC_DATASET_MLCOMMONS_COGNATA_FILE_NAMES: ""
 
+  release:
+    group: dataset-type
+    env:
+      MLC_COGNATA_DATASET_TYPE: "release"
+
   rclone:
     group: download-tool
     default: true
@@ -153,6 +170,57 @@ variations:
     group: download-tool
     env:
       MLC_DATASET_MLCOMMONS_COGNATA_DOWNLOAD_TOOL: gdrive
+  
+  mlc:
+    group: download-src
+    prehook_deps:
+      - tags: get,rclone
+        enable_if_env:
+          MLC_TMP_REQUIRE_DOWNLOAD:
+          - yes
+      - tags: get,rclone-config,_config-name.cognata
+        force_cache: true
+        enable_if_env:
+          MLC_TMP_REQUIRE_DOWNLOAD:
+          - yes
+        env:
+          MLC_RCLONE_DRIVE_FOLDER_ID: 1u5FDoeXHVtDrd4zClE47Gmyr7iLFidz1
+      - enable_if_env:
+          MLC_TMP_REQUIRE_DOWNLOAD:
+          - 'yes'
+        env:
+          MLC_DOWNLOAD_FINAL_ENV_NAME: MLC_DATASET_MLCOMMONS_COGNATA_PATH
+          MLC_EXTRACT_FINAL_ENV_NAME: MLC_DATASET_MLCOMMONS_COGNATA_PATH
+          MLC_DOWNLOAD_URL: 'mlc-cognata:mlc_cognata_dataset/unprocessed'
+        extra_cache_tags: dataset,cognata,release
+        force_cache: true
+        names:
+          - dae
+        tags: download-and-extract
+        force_env_keys:
+          - MLC_OUTDIRNAME  
+        update_tags_from_env_with_prefix:
+          _url.:
+            - MLC_DOWNLOAD_URL
+    env:
+      MLC_DOWNLOAD_SRC: mlcommons
+  
+  rclone,mlc:
+    add_deps_recursive:
+      dae:
+        tags: _rclone
+    env:
+      MLC_RCLONE_COPY_USING: sync
+
+  dry-run:
+    group: run-mode
+    env:
+      MLC_DOWNLOAD_MODE: dry
+
+  dry-run,rclone:
+    env:
+      MLC_DOWNLOAD_EXTRA_OPTIONS: --dry-run
+  
 
 new_env_keys:
 - MLC_DATASET_MLCOMMONS_COGNATA*
diff --git a/script/get-dataset-cognata-mlcommons/run.sh b/script/get-dataset-cognata-mlcommons/run.sh
new file mode 100644
index 000000000..5563a95da
--- /dev/null
+++ b/script/get-dataset-cognata-mlcommons/run.sh
@@ -0,0 +1,16 @@
+#!/bin/bash
+
+#CM Script location: ${MLC_TMP_CURRENT_SCRIPT_PATH}
+
+#To export any variable
+#echo "VARIABLE_NAME=VARIABLE_VALUE" >>tmp-run-env.out
+
+#${MLC_PYTHON_BIN_WITH_PATH} contains the path to python binary if "get,python" is added as a dependency
+
+if [[ "$MLC_DOWNLOAD_MODE" != "dry" && "$MLC_TMP_REQUIRE_DOWNLOAD" == "true" && "$MLC_COGNATA_DATASET_TYPE" == "release" ]]; then
+  cd "${MLC_DATASET_MLCOMMONS_COGNATA_PATH}" || exit
+  for f in *.tar.gz; do 
+    tar -xzvf "$f" || { echo "Failed to extract $f"; exit 1; }
+  done
+  cd - || exit
+fi
\ No newline at end of file
diff --git a/script/get-one-api/COPYRIGHT.md b/script/get-dataset-nuscenes/COPYRIGHT.md
similarity index 100%
rename from script/get-one-api/COPYRIGHT.md
rename to script/get-dataset-nuscenes/COPYRIGHT.md
diff --git a/script/get-dataset-nuscenes/customize.py b/script/get-dataset-nuscenes/customize.py
new file mode 100644
index 000000000..d4abad774
--- /dev/null
+++ b/script/get-dataset-nuscenes/customize.py
@@ -0,0 +1,23 @@
+from mlc import utils
+import os
+
+
+def preprocess(i):
+
+    os_info = i['os_info']
+
+    env = i['env']
+
+    if os_info['platform'] == "windows":
+        return {'return': 1, 'error': 'Script not supported in windows yet!'}
+
+    env['MLC_TMP_REQUIRE_DOWNLOAD'] = "yes"
+
+    return {'return': 0}
+
+
+def postprocess(i):
+
+    env = i['env']
+
+    return {'return': 0}
diff --git a/script/get-dataset-nuscenes/meta.yaml b/script/get-dataset-nuscenes/meta.yaml
new file mode 100644
index 000000000..e12787bdf
--- /dev/null
+++ b/script/get-dataset-nuscenes/meta.yaml
@@ -0,0 +1,57 @@
+alias: get-dataset-nuscenes
+automation_alias: script
+automation_uid: 5b4e0237da074764
+cache: true
+tags:
+- get
+- dataset
+- nuscenes
+uid: ec2a0842c9a644f5
+new_env_keys:
+  - MLC_DATASET_NUSCENES_PATH
+variations:
+  mlc:
+    group: download-src
+    default: true
+    prehook_deps:
+      - tags: get,rclone
+        enable_if_env:
+          MLC_TMP_REQUIRE_DOWNLOAD:
+          - yes
+      - tags: get,rclone-config,_waymo
+        force_cache: true
+        enable_if_env:
+          MLC_TMP_REQUIRE_DOWNLOAD:
+          - yes
+      - enable_if_env:
+          MLC_TMP_REQUIRE_DOWNLOAD:
+          - 'yes'
+        env:
+          MLC_DOWNLOAD_FINAL_ENV_NAME: MLC_DATASET_NUSCENES_PATH
+          MLC_EXTRACT_FINAL_ENV_NAME: MLC_DATASET_NUSCENES_PATH
+          MLC_DOWNLOAD_URL: mlc-nuscenes:nuscenes_dataset
+        extra_cache_tags: nuscenes,dataset
+        force_cache: true
+        names:
+          - dae
+        tags: download-and-extract
+        force_env_keys:
+          - MLC_OUTDIRNAME  
+        update_tags_from_env_with_prefix:
+          _url.:
+            - MLC_DOWNLOAD_URL
+    env:
+      MLC_DOWNLOAD_SRC: mlcommons
+  rclone:
+    group: download-tool
+    add_deps_recursive:
+      dae:
+        tags: _rclone
+    default: true
+  dry-run:
+    group: run-mode
+    env:
+      MLC_DOWNLOAD_MODE: dry
+  dry-run,rclone:
+    env:
+      MLC_DOWNLOAD_EXTRA_OPTIONS: --dry-run
diff --git a/script/get-dataset-nuscenes/run.sh b/script/get-dataset-nuscenes/run.sh
new file mode 100644
index 000000000..abe5a17c7
--- /dev/null
+++ b/script/get-dataset-nuscenes/run.sh
@@ -0,0 +1,20 @@
+#!/bin/bash
+
+#CM Script location: ${MLC_TMP_CURRENT_SCRIPT_PATH}
+
+#To export any variable
+#echo "VARIABLE_NAME=VARIABLE_VALUE" >>tmp-run-env.out
+
+#${MLC_PYTHON_BIN_WITH_PATH} contains the path to python binary if "get,python" is added as a dependency
+
+if [[ "$MLC_DOWNLOAD_MODE" != "dry" && "$MLC_TMP_REQUIRE_DOWNLOAD" = "true" ]]; then
+  cd "${MLC_DATASET_NUSCENES_PATH}" || exit
+  for f in *.tar.gz; do 
+    tar -xzvf "$f" || { echo "Failed to extract $f"; exit 1; }
+  done
+  cd "${MLC_DATASET_NUSCENES_PATH}/nuscenes" || exit
+  for f in *.tar.gz; do 
+    tar -xzvf "$f" || { echo "Failed to extract $f"; exit 1; }
+  done
+  cd - || exit
+fi
\ No newline at end of file
diff --git a/script/get-generic-sys-util/meta.yaml b/script/get-generic-sys-util/meta.yaml
index 8f75171de..01ffa7b9f 100644
--- a/script/get-generic-sys-util/meta.yaml
+++ b/script/get-generic-sys-util/meta.yaml
@@ -52,6 +52,20 @@ tests:
     docker_prune: 'yes'
 uid: bb0393afa8404a11
 variations:
+  autoconf:
+    env:
+      MLC_SYS_UTIL_NAME: autoconf
+      MLC_SYS_UTIL_VERSION_CMD: autoconf --version
+      MLC_SYS_UTIL_VERSION_RE: autoconf \(.*\) ([\d.]+)
+      MLC_TMP_VERSION_DETECT_GROUP_NUMBER: 1
+    new_env_keys:
+    - MLC_AUTOCONF_VERSION
+    state:
+      autoconf:
+        apt: autoconf
+        brew: autoconf
+        dnf: autoconf
+        yum: autoconf
   cmake:
     env:
       MLC_SYS_UTIL_NAME: cmake
@@ -97,6 +111,20 @@ variations:
         brew: ''
         dnf: dmidecode
         yum: dmidecode
+  flex:
+    env:
+      MLC_SYS_UTIL_NAME: flex
+      MLC_SYS_UTIL_VERSION_CMD: flex --version # tbd: regular expression for version
+      MLC_TMP_VERSION_DETECT_GROUP_NUMBER: 0
+    new_env_keys:
+    - MLC_FLEX_VERSION
+    state:
+      flex: # tbd: complete for other flavours of linux
+        apt: flex
+        brew: flex
+        dnf: flex
+        yum: flex
+  
   ffmpeg:
     env:
       MLC_SYS_UTIL_NAME: ffmpeg
@@ -111,6 +139,21 @@ variations:
         dnf: ''   
         yum: ''
   
+  ipmitool:
+    env:
+      MLC_SYS_UTIL_NAME: ipmitool
+      MLC_SYS_UTIL_VERSION_CMD: ipmitool -V
+      MLC_SYS_UTIL_VERSION_RE: 'ipmitool version ([\d.]+)'
+      MLC_TMP_VERSION_DETECT_GROUP_NUMBER: 0
+    new_env_keys:
+    - MLC_IPMITOOL_VERSION
+    state:
+      ipmitool: # tbd: complete for other flavours of linux
+        apt: ipmitool
+        brew: ''
+        dnf: ''   
+        yum: ''
+  
   libgl:
     env:
       MLC_SYS_UTIL_NAME: libgl # tbd: regular expression for version as well as whether its installed?
@@ -125,6 +168,20 @@ variations:
         brew: ''
         dnf: mesa-libGL   
         yum: mesa-libGL
+  libgl1-mesa-glx:
+    env:
+      MLC_SYS_UTIL_NAME: libgl1-mesa-glx # tbd: regular expression for version as well as whether its installed?
+      MLC_SYS_UTIL_CHECK_CMD: 'ldconfig -p | grep -i libGLX_mesa.so.*' 
+    default_env:
+      MLC_GENERIC_SYS_UTIL_IGNORE_MISSING_PACKAGE: yes
+    new_env_keys:
+    - MLC_LIBGLX_VERSION
+    state:
+      libgl1-mesa-glx: # tbd: complete for other flavours of linux
+        apt: libgl1-mesa-glx
+        brew: ''
+        dnf: ''
+        yum: ''
   libsm6:
     env:
       MLC_SYS_UTIL_NAME: libsm6 # tbd: regular expression for version as well as whether its installed?
@@ -605,6 +662,9 @@ variations:
   postfix:
     env:
       MLC_SYS_UTIL_NAME: postfix
+      MLC_SYS_UTIL_VERSION_CMD: postconf mail_version
+      MLC_SYS_UTIL_VERSION_RE: mail_version = \b(\d+\.\d+(?:\.\d+)?)\b
+      MLC_TMP_VERSION_DETECT_GROUP_NUMBER: 1
     new_env_keys:
     - MLC_POSTFIX_VERSION
     state:
diff --git a/script/get-git-repo/meta.yaml b/script/get-git-repo/meta.yaml
index 962b9281f..468468bb5 100644
--- a/script/get-git-repo/meta.yaml
+++ b/script/get-git-repo/meta.yaml
@@ -36,7 +36,7 @@ post_deps:
   - pull-git-repo
   tags: pull,git,repo
 print_env_at_the_end:
-  MLC_GIT_CHECKOUT_PATH: CM cache path to the Git repo
+  MLC_GIT_CHECKOUT_PATH: MLC cache path to the Git repo
 tags:
 - get
 - git
@@ -79,7 +79,7 @@ variations:
       git-history: full-history
     env:
       MLC_GIT_SHA: '#'
-    group: checkout
+    group: post-checkout
   short-history:
     default: true
     env:
diff --git a/script/get-lib-jemalloc/customize.py b/script/get-lib-jemalloc/customize.py
new file mode 100644
index 000000000..7cb73c6c9
--- /dev/null
+++ b/script/get-lib-jemalloc/customize.py
@@ -0,0 +1,30 @@
+from mlc import utils
+import os
+import subprocess
+
+
+def preprocess(i):
+
+    env = i['env']
+    state = i['state']
+
+    os_info = i['os_info']
+
+    return {'return': 0}
+
+
+def postprocess(i):
+
+    env = i['env']
+    state = i['state']
+
+    os_info = i['os_info']
+
+    lib_path = os.path.join(os.getcwd(), "obj", "lib")
+
+    env['+LD_LIBRARY_PATH'] = lib_path
+    env['MLC_JEMALLOC_PATH'] = os.path.dirname(lib_path)
+    env['MLC_JEMALLOC_LIB_PATH'] = lib_path
+    env['MLC_DEPENDENT_CACHED_PATH'] = os.path.join(lib_path, "libjemalloc.so")
+
+    return {'return': 0}
diff --git a/script/get-lib-jemalloc/meta.yaml b/script/get-lib-jemalloc/meta.yaml
new file mode 100644
index 000000000..8a42e9117
--- /dev/null
+++ b/script/get-lib-jemalloc/meta.yaml
@@ -0,0 +1,47 @@
+alias: get-lib-jemalloc
+automation_alias: script
+automation_uid: 5b4e0237da074764
+category: Detection or installation of tools and artifacts
+cache: true
+deps:
+  - tags: get,git,repo
+    env:
+      MLC_GIT_CHECKOUT_PATH_ENV_NAME: MLC_JEMALLOC_SRC_PATH
+    force_env_keys:
+      - MLC_GIT_*
+    update_tags_from_env_with_prefix:
+      _branch.:
+        - MLC_GIT_CHECKOUT
+      _repo.:
+        - MLC_GIT_URL
+      _sha.:
+        - MLC_GIT_SHA
+      _submodules.:
+        - MLC_GIT_SUBMODULES
+    names:
+      - jemalloc-repo
+    extra_cache_tags: jemalloc,repo,jemalloc-repo
+  - tags: get,generic-sys-util,_autoconf
+new_env_keys:
+  - MLC_JEMALLOC_PATH
+  - MLC_JEMALLOC_LIB_PATH
+  - +LD_LIBRARY_PATH
+new_state_keys: []
+post_deps: []
+posthook_deps: []
+prehook_deps: []
+tags:
+- get
+- lib
+- lib-jemalloc
+- jemalloc
+tests:
+  run_inputs:
+  - quiet: true
+uid: 406439a446e04fb7
+variations:
+  version.official:
+    group: version
+    default: true
+    env:
+      MLC_GIT_URL: https://github.com/jemalloc/jemalloc.git
diff --git a/script/get-lib-jemalloc/run.sh b/script/get-lib-jemalloc/run.sh
new file mode 100644
index 000000000..2d156cf42
--- /dev/null
+++ b/script/get-lib-jemalloc/run.sh
@@ -0,0 +1,13 @@
+#!/bin/bash
+
+set -e
+
+#Add your run commands here...
+# run "$MLC_RUN_CMD"
+cd ${MLC_JEMALLOC_SRC_PATH}
+autoconf
+cd - 
+mkdir -p obj
+cd obj
+${MLC_JEMALLOC_SRC_PATH}/configure --enable-autogen
+make
diff --git a/script/get-llvm/meta.yaml b/script/get-llvm/meta.yaml
index 8193227b7..abcebd854 100644
--- a/script/get-llvm/meta.yaml
+++ b/script/get-llvm/meta.yaml
@@ -27,6 +27,9 @@ prehook_deps:
     - 'yes'
   names: llvm-install
   reuse_version: true
+  inherit_variation_tags: true
+  skip_inherit_variation_groups:
+    - install-src
   tags: install,llvm
 sort: 100
 tags:
@@ -39,13 +42,24 @@ tags:
 uid: 99832a103ed04eb8
 variations:
   from-prebuilt:
+    group: install-src
+    default: true
     ad:
       llvm-install:
         tags: prebuilt
   from-src:
+    group: install-src
     ad:
       llvm-install:
         tags: src,_clang
   path.#:
     env:
       MLC_LLVM_DIR_PATH: '#'
+  release: {}
+  version.#: {}
+  branch.#: {}
+  runtimes.#: {}
+  flang: {}
+  sha.#: {}
+  tag.#: {}
+
diff --git a/script/get-ml-model-abtf-ssd-pytorch/customize.py b/script/get-ml-model-abtf-ssd-pytorch/customize.py
index a4fa7f16c..e63e92fff 100644
--- a/script/get-ml-model-abtf-ssd-pytorch/customize.py
+++ b/script/get-ml-model-abtf-ssd-pytorch/customize.py
@@ -26,6 +26,9 @@ def preprocess(i):
                     'error': 'ML model {} is not found'.format(ml_model)}
 
         env['MLC_ML_MODEL_FILE_WITH_PATH'] = ml_model
+    # handles download from mlcommons gdrive
+    elif env.get('MLC_DOWNLOAD_SRC', '') == "mlcommons" and env.get('MLC_ML_MODEL_SSD_PATH', '') == '':
+        env['MLC_TMP_REQUIRE_DOWNLOAD'] = 'yes'
 
     return {'return': 0}
 
@@ -35,7 +38,13 @@ def postprocess(i):
     env = i['env']
 
     if env.get('MLC_ML_MODEL_FILE_WITH_PATH', '') == '':
-        env['MLC_ML_MODEL_FILE_WITH_PATH'] = 'model-weights-skipped'
+        if env.get('MLC_ML_MODEL_SSD_PATH', '') == '':
+            env['MLC_ML_MODEL_FILE_WITH_PATH'] = 'model-weights-skipped'
+        else:
+            if is_true(env.get('MLC_TMP_REQUIRE_DOWNLOAD', '')):
+                env['MLC_ML_MODEL_SSD_PATH'] = os.path.join(
+                    env['MLC_ML_MODEL_SSD_PATH'], env['MLC_ML_MODEL_FILENAME'])
+            env['MLC_ML_MODEL_FILE_WITH_PATH'] = env['MLC_ML_MODEL_SSD_PATH']
 
     env['MLC_ML_MODEL_FILE'] = os.path.basename(
         env['MLC_ML_MODEL_FILE_WITH_PATH'])
diff --git a/script/get-ml-model-abtf-ssd-pytorch/meta.yaml b/script/get-ml-model-abtf-ssd-pytorch/meta.yaml
index b9f70ebc3..017acec37 100644
--- a/script/get-ml-model-abtf-ssd-pytorch/meta.yaml
+++ b/script/get-ml-model-abtf-ssd-pytorch/meta.yaml
@@ -17,6 +17,8 @@ tags:
 - get
 - ml-model
 - abtf-ssd-pytorch
+- ssd
+- resnet50
 - cmc
 
 
@@ -38,9 +40,11 @@ deps:
   names:
   - abtf-ssd-pytorch-git-repo
   - abtf-ml-model-code-git-repo
-  skip_if_env:
+  skip_if_any_env:
     MLC_SKIP_MODEL_CODE_DOWNLOAD:
     - 'yes'
+    MLC_DOWNLOAD_SRC: 
+    - 'mlcommons'
   env:
     MLC_GIT_AUTH: 'yes'
     MLC_GIT_CHECKOUT_PATH_ENV_NAME: MLC_ABTF_SSD_PYTORCH
@@ -62,9 +66,11 @@ deps:
   names:
   - abtf-ml-model-weights
   - abtf-ml-model-weights-download
-  skip_if_env:
+  skip_if_any_env:
     MLC_SKIP_MODEL_WEIGHTS_DOWNLOAD:
     - 'yes'
+    MLC_DOWNLOAD_SRC: 
+    - 'mlcommons'
   update_tags_from_env_with_prefix:
     _url.:
       - MLC_ML_MODEL_URL
@@ -77,6 +83,7 @@ new_env_keys:
 print_env_at_the_end:
   MLC_ML_MODEL_FILE_WITH_PATH: Path to the ML model weights
   MLC_ML_MODEL_CODE_WITH_PATH: Path to the ML model code
+  MLC_ML_MODEL_SSD_PATH: Path to ssd resnet50 model
 
 
 variations:
@@ -172,3 +179,81 @@ variations:
     adr:
       abtf-ml-model-weights-download:
         tags: _gdown
+
+  onnx:
+    group: model-format
+    default: true
+    env:
+      MLC_MODEL_FORMAT: onnx
+  
+  onnx,mlc:
+    env:
+      MLC_MODEL_RCLONE_FILEPATH: model_checkpoint_ssd/ssd_resnet50.onnx
+      MLC_ML_MODEL_FILENAME: ssd_resnet50.onnx
+  
+  pytorch:
+    group: model-format
+    env:
+      MLC_MODEL_FORMAT: pth
+  
+  pytorch,mlc:
+    env:
+      MLC_MODEL_RCLONE_FILEPATH: model_checkpoint_ssd/baseline_8MP_ss_scales_fm1_5x5_all_ep60.pth
+      MLC_ML_MODEL_FILENAME: baseline_8MP_ss_scales_fm1_5x5_all_ep60.pth
+  
+  rclone,mlc:
+    group: download-tool
+    add_deps_recursive:
+      dae:
+        tags: _rclone
+    env:
+      MLC_RCLONE_COPY_USING: sync
+  
+  dry-run:
+    group: run-mode
+    env:
+      MLC_DOWNLOAD_MODE: dry
+
+  dry-run,rclone:
+    env:
+      MLC_DOWNLOAD_EXTRA_OPTIONS: --dry-run
+  
+  mlc:
+    group: download-src
+    prehook_deps:
+      - tags: get,rclone
+        enable_if_env:
+          MLC_TMP_REQUIRE_DOWNLOAD:
+          - yes
+      - tags: get,rclone-config,_config-name.cognata
+        force_cache: true
+        enable_if_env:
+          MLC_TMP_REQUIRE_DOWNLOAD:
+          - yes
+        env:
+          MLC_RCLONE_DRIVE_FOLDER_ID: 1u5FDoeXHVtDrd4zClE47Gmyr7iLFidz1
+      - enable_if_env:
+          MLC_TMP_REQUIRE_DOWNLOAD:
+          - 'yes'
+        env:
+          MLC_DOWNLOAD_FINAL_ENV_NAME: MLC_ML_MODEL_SSD_PATH
+          MLC_EXTRACT_FINAL_ENV_NAME: MLC_MLC_MODEL_SSD_PATH
+          MLC_DOWNLOAD_URL: 'mlc-cognata:mlc_cognata_dataset/<<<MLC_MODEL_RCLONE_FILEPATH>>>'
+          MLC_DOWNLOAD_EXTRA_OPTIONS: ' --include '
+        extra_cache_tags: ml,model,ssd,resnet50
+        force_cache: true
+        names:
+          - dae
+        tags: download-and-extract
+        force_env_keys:
+          - MLC_OUTDIRNAME  
+        update_tags_from_env_with_prefix:
+          _url.:
+            - MLC_DOWNLOAD_URL
+    env:
+      MLC_DOWNLOAD_SRC: mlcommons
+tests:
+  run_inputs:
+  - variations_list:
+      - onnx,rclone,mlc,dry-run
+      - pytorch,rclone,mlc,dry-run
\ No newline at end of file
diff --git a/script/get-ml-model-bevformer/COPYRIGHT.md b/script/get-ml-model-bevformer/COPYRIGHT.md
new file mode 100644
index 000000000..d2ceead84
--- /dev/null
+++ b/script/get-ml-model-bevformer/COPYRIGHT.md
@@ -0,0 +1,9 @@
+# Copyright Notice
+
+© 2025-2026 MLCommons. All Rights Reserved.
+
+This file is licensed under the Apache License, Version 2.0 (the "License"). You may not use this file except in compliance with the License. A copy of the License can be obtained at:
+
+[Apache License, Version 2.0](http://www.apache.org/licenses/LICENSE-2.0)
+
+Unless required by applicable law or agreed to in writing, software distributed under the License is provided on an "AS IS" basis, without warranties or conditions of any kind, either express or implied. Please refer to the License for the specific language governing permissions and limitations under the License.
diff --git a/script/get-ml-model-bevformer/customize.py b/script/get-ml-model-bevformer/customize.py
new file mode 100644
index 000000000..9afc37740
--- /dev/null
+++ b/script/get-ml-model-bevformer/customize.py
@@ -0,0 +1,31 @@
+from mlc import utils
+from utils import is_true
+import os
+
+
+def preprocess(i):
+
+    os_info = i['os_info']
+
+    env = i['env']
+
+    if os_info['platform'] == "windows":
+        return {'return': 1, 'error': 'Script not supported in windows yet!'}
+
+    if env.get('MLC_ML_MODEL_BEVFORMER_PATH', '') == '':
+        env['MLC_TMP_REQUIRE_DOWNLOAD'] = "yes"
+
+    return {'return': 0}
+
+
+def postprocess(i):
+
+    env = i['env']
+
+    if is_true(env.get('MLC_TMP_REQUIRE_DOWNLOAD', '')):
+        env['MLC_ML_MODEL_BEVFORMER_PATH'] = os.path.join(
+            env['MLC_ML_MODEL_BEVFORMER_PATH'], env['MLC_ML_MODEL_FILENAME'])
+
+    env['MLC_ML_MODEL_FILE_WITH_PATH'] = env['MLC_ML_MODEL_BEVFORMER_PATH']
+
+    return {'return': 0}
diff --git a/script/get-ml-model-bevformer/meta.yaml b/script/get-ml-model-bevformer/meta.yaml
new file mode 100644
index 000000000..e4c156030
--- /dev/null
+++ b/script/get-ml-model-bevformer/meta.yaml
@@ -0,0 +1,81 @@
+alias: get-ml-model-bevformer
+automation_alias: script
+automation_uid: 5b4e0237da074764
+cache: true
+tags:
+- get
+- ml-model
+- bevformer
+uid: 438a053f666443bd
+new_env_keys:
+  - MLC_ML_MODEL_BEVFORMER_PATH
+  - MLC_ML_MODEL_FILE_WITH_PATH
+print_env_at_the_end:
+  MLC_ML_MODEL_BEVFORMER_PATH: BevFormer checkpoint path
+variations:
+  onnx:
+    group: model-format
+    default: true
+    env:
+      MLC_MODEL_FORMAT: onnx
+      MLC_MODEL_RCLONE_FILEPATH: model_checkpoint_bevformer/bevformer_tiny.onnx
+      MLC_ML_MODEL_FILENAME: bevformer_tiny.onnx
+  pytorch:
+    group: model-format
+    env:
+      MLC_MODEL_FORMAT: pth
+      MLC_MODEL_RCLONE_FILEPATH: model_checkpoint_bevformer/bevformer_tiny_epoch_24.pth
+      MLC_ML_MODEL_FILENAME: bevformer_tiny_epoch_24.onnx
+  mlc:
+    group: download-src
+    default: true
+    prehook_deps:
+      - tags: get,rclone
+        enable_if_env:
+          MLC_TMP_REQUIRE_DOWNLOAD:
+          - yes
+      - tags: get,rclone-config,_config-name.mlc-nuscenes
+        force_cache: true
+        enable_if_env:
+          MLC_TMP_REQUIRE_DOWNLOAD:
+          - yes
+        env:
+          MLC_RCLONE_DRIVE_FOLDER_ID: 17CpM5eU8tjrxh_LpH_BTNTeT37PhzcnC
+      - enable_if_env:
+          MLC_TMP_REQUIRE_DOWNLOAD:
+          - 'yes'
+        env:
+          MLC_DOWNLOAD_FINAL_ENV_NAME: MLC_ML_MODEL_BEVFORMER_PATH
+          MLC_EXTRACT_FINAL_ENV_NAME: MLC_ML_MODEL_BEVFORMER_PATH
+          MLC_DOWNLOAD_URL: 'mlc-nuscenes:<<<MLC_MODEL_RCLONE_FILEPATH>>>'
+          MLC_DOWNLOAD_EXTRA_OPTIONS: ' --include '
+        extra_cache_tags: ml,model,bevformer
+        force_cache: true
+        names:
+          - dae
+        tags: download-and-extract
+        force_env_keys:
+          - MLC_OUTDIRNAME  
+        update_tags_from_env_with_prefix:
+          _url.:
+            - MLC_DOWNLOAD_URL
+    env:
+      MLC_DOWNLOAD_SRC: mlcommons
+  rclone:
+    group: download-tool
+    add_deps_recursive:
+      dae:
+        tags: _rclone
+    default: true
+  dry-run:
+    group: run-mode
+    env:
+      MLC_DOWNLOAD_MODE: dry
+  dry-run,rclone:
+    env:
+      MLC_DOWNLOAD_EXTRA_OPTIONS: --dry-run
+tests:
+  run_inputs:
+  - variations_list:
+      - onnx,rclone,mlc,dry-run
+      - pytorch,rclone,mlc,dry-run
\ No newline at end of file
diff --git a/script/get-ml-model-bevformer/run.sh b/script/get-ml-model-bevformer/run.sh
new file mode 100644
index 000000000..a9bf588e2
--- /dev/null
+++ b/script/get-ml-model-bevformer/run.sh
@@ -0,0 +1 @@
+#!/bin/bash
diff --git a/script/get-ml-model-deeplabv3_plus/COPYRIGHT.md b/script/get-ml-model-deeplabv3_plus/COPYRIGHT.md
new file mode 100644
index 000000000..d2ceead84
--- /dev/null
+++ b/script/get-ml-model-deeplabv3_plus/COPYRIGHT.md
@@ -0,0 +1,9 @@
+# Copyright Notice
+
+© 2025-2026 MLCommons. All Rights Reserved.
+
+This file is licensed under the Apache License, Version 2.0 (the "License"). You may not use this file except in compliance with the License. A copy of the License can be obtained at:
+
+[Apache License, Version 2.0](http://www.apache.org/licenses/LICENSE-2.0)
+
+Unless required by applicable law or agreed to in writing, software distributed under the License is provided on an "AS IS" basis, without warranties or conditions of any kind, either express or implied. Please refer to the License for the specific language governing permissions and limitations under the License.
diff --git a/script/get-ml-model-deeplabv3_plus/customize.py b/script/get-ml-model-deeplabv3_plus/customize.py
new file mode 100644
index 000000000..2fff179b1
--- /dev/null
+++ b/script/get-ml-model-deeplabv3_plus/customize.py
@@ -0,0 +1,30 @@
+from mlc import utils
+import os
+from utils import is_true
+
+
+def preprocess(i):
+
+    os_info = i['os_info']
+
+    env = i['env']
+
+    if os_info['platform'] == "windows":
+        return {'return': 1, 'error': 'Script not supported in windows yet!'}
+
+    if env.get('MLC_ML_MODEL_DEEPLABV3_PLUS_PATH', '') == '':
+        env['MLC_TMP_REQUIRE_DOWNLOAD'] = "yes"
+
+    return {'return': 0}
+
+
+def postprocess(i):
+
+    env = i['env']
+
+    if is_true(env.get('MLC_TMP_REQUIRE_DOWNLOAD', '')):
+        env['MLC_ML_MODEL_DEEPLABV3_PLUS_PATH'] = os.path.join(
+            env['MLC_ML_MODEL_DEEPLABV3_PLUS_PATH'], env['MLC_ML_MODEL_FILENAME'])
+    env['MLC_ML_MODEL_FILE_WITH_PATH'] = env['MLC_ML_MODEL_DEEPLABV3_PLUS_PATH']
+
+    return {'return': 0}
diff --git a/script/get-ml-model-deeplabv3_plus/meta.yaml b/script/get-ml-model-deeplabv3_plus/meta.yaml
new file mode 100644
index 000000000..66215eb09
--- /dev/null
+++ b/script/get-ml-model-deeplabv3_plus/meta.yaml
@@ -0,0 +1,91 @@
+alias: get-ml-model-deeplabv3-plus
+automation_alias: script
+automation_uid: 5b4e0237da074764
+cache: true
+tags:
+- get
+- ml-model
+- deeplab
+- v3-plus
+- deeplabv3-plus
+uid: cfb2d53b9dbc4dc0
+new_env_keys:
+  - MLC_ML_MODEL_DEEPLABV3_PLUS_PATH
+  - MLC_ML_MODEL_FILE_WITH_PATH
+print_env_at_the_end:
+  MLC_ML_MODEL_DEEPLABV3_PLUS_PATH: DeepLabV3+ checkpoint path
+variations:
+  onnx:
+    group: model-format
+    default: true
+    env:
+      MLC_MODEL_FORMAT: onnx
+      MLC_MODEL_RCLONE_FILEPATH: model_checkpoint_deeplab/deeplabv3+_8mp.onnx
+      MLC_ML_MODEL_FILENAME: deeplabv3+_8mp.onnx
+  dynamic: {}
+  onnx,dynamic:
+    group: model-format
+    env:
+      MLC_MODEL_FORMAT: onnx
+      MLC_MODEL_RCLONE_FILEPATH: model_checkpoint_deeplab/deeplabv3+_dynamic.onnx
+      MLC_ML_MODEL_FILENAME: deeplabv3+_dynamic.onnx
+  pytorch:
+    group: model-format
+    env:
+      MLC_MODEL_FORMAT: pth
+      MLC_MODEL_RCLONE_FILEPATH: model_checkpoint_deeplab/latest_deeplabv3plus_resnet50_cognata_os16_it100000.pth
+      MLC_ML_MODEL_FILENAME: latest_deeplabv3plus_resnet50_cognata_os16_it100000.pth
+  mlc:
+    group: download-src
+    default: true
+    prehook_deps:
+      - tags: get,rclone
+        enable_if_env:
+          MLC_TMP_REQUIRE_DOWNLOAD:
+          - yes
+      - tags: get,rclone-config,_config-name.cognata
+        force_cache: true
+        enable_if_env:
+          MLC_TMP_REQUIRE_DOWNLOAD:
+          - yes
+        env:
+          MLC_RCLONE_DRIVE_FOLDER_ID: 1u5FDoeXHVtDrd4zClE47Gmyr7iLFidz1
+      - enable_if_env:
+          MLC_TMP_REQUIRE_DOWNLOAD:
+          - 'yes'
+        env:
+          MLC_DOWNLOAD_FINAL_ENV_NAME: MLC_ML_MODEL_DEEPLABV3_PLUS_PATH
+          MLC_EXTRACT_FINAL_ENV_NAME: MLC_ML_MODEL_DEEPLABV3_PLUS_PATH
+          MLC_DOWNLOAD_URL: 'mlc-cognata:mlc_cognata_dataset/<<<MLC_MODEL_RCLONE_FILEPATH>>>'
+          MLC_DOWNLOAD_EXTRA_OPTIONS: ' --include '
+        extra_cache_tags: ml,model,deeplabv3,plus
+        force_cache: true
+        names:
+          - dae
+        tags: download-and-extract
+        force_env_keys:
+          - MLC_OUTDIRNAME  
+        update_tags_from_env_with_prefix:
+          _url.:
+            - MLC_DOWNLOAD_URL
+    env:
+      MLC_DOWNLOAD_SRC: mlcommons
+  rclone:
+    group: download-tool
+    add_deps_recursive:
+      dae:
+        tags: _rclone
+    default: true
+  dry-run:
+    group: run-mode
+    env:
+      MLC_DOWNLOAD_MODE: dry
+  dry-run,rclone:
+    env:
+      MLC_DOWNLOAD_EXTRA_OPTIONS: --dry-run
+tests:
+  run_inputs:
+  - variations_list:
+      - onnx,rclone,mlc,dry-run
+      - onnx_dynamic,rclone,mlc,dry-run
+      - pytorch,rclone,mlc,dry-run
\ No newline at end of file
diff --git a/script/get-ml-model-deeplabv3_plus/run.sh b/script/get-ml-model-deeplabv3_plus/run.sh
new file mode 100644
index 000000000..05a7907cf
--- /dev/null
+++ b/script/get-ml-model-deeplabv3_plus/run.sh
@@ -0,0 +1,2 @@
+#!/bin/bash
+
diff --git a/script/get-mlperf-automotive-src/COPYRIGHT.md b/script/get-mlperf-automotive-src/COPYRIGHT.md
new file mode 100644
index 000000000..d2ceead84
--- /dev/null
+++ b/script/get-mlperf-automotive-src/COPYRIGHT.md
@@ -0,0 +1,9 @@
+# Copyright Notice
+
+© 2025-2026 MLCommons. All Rights Reserved.
+
+This file is licensed under the Apache License, Version 2.0 (the "License"). You may not use this file except in compliance with the License. A copy of the License can be obtained at:
+
+[Apache License, Version 2.0](http://www.apache.org/licenses/LICENSE-2.0)
+
+Unless required by applicable law or agreed to in writing, software distributed under the License is provided on an "AS IS" basis, without warranties or conditions of any kind, either express or implied. Please refer to the License for the specific language governing permissions and limitations under the License.
diff --git a/script/get-mlperf-automotive-src/customize.py b/script/get-mlperf-automotive-src/customize.py
new file mode 100644
index 000000000..69b336134
--- /dev/null
+++ b/script/get-mlperf-automotive-src/customize.py
@@ -0,0 +1,154 @@
+from mlc import utils
+from utils import is_true
+import os
+import shutil
+
+
+def preprocess(i):
+
+    os_info = i['os_info']
+
+    env = i['env']
+    meta = i['meta']
+
+    script_path = i['run_script_input']['path']
+
+    if env.get('MLC_GIT_CHECKOUT', '') == '' and env.get(
+            'MLC_GIT_URL', '') == '' and env.get('MLC_VERSION', '') == '':
+        # if custom checkout and url parameters are not set and MLC_VERSION is
+        # not specified
+        env['MLC_VERSION'] = "master"
+        env["MLC_GIT_CHECKOUT"] = "master"
+        env["MLC_GIT_URL"] = "https://github.com/mlcommons/mlperf_automotive"
+    elif env.get('MLC_GIT_CHECKOUT', '') != '' and env.get('MLC_TMP_GIT_CHECKOUT', '') != '' and env.get('MLC_GIT_CHECKOUT', '') != env.get('MLC_TMP_GIT_CHECKOUT', ''):
+        # if checkout branch is assigned inside version and custom branch is
+        # also specified
+        return {
+            "return": 1, "error": "Conflicting branches between version assigned and user specified."}
+    elif env.get('MLC_GIT_URL', '') != '' and env.get('MLC_TMP_GIT_URL', '') != '' and env.get('MLC_GIT_URL', '') != env.get('MLC_TMP_GIT_URL', ''):
+        # if GIT URL is assigned inside version and custom branch is also
+        # specified
+        return {
+            "return": 1, "error": "Conflicting URL's between version assigned and user specified."}
+
+    if env.get('MLC_VERSION', '') == '':
+        env['MLC_VERSION'] = "custom"
+
+    # check whether branch and url is specified,
+    # if not try to assign the values specified in version parameters,
+    # if version parameters does not have the value to a parameter, set the
+    # default one
+    if env.get('MLC_GIT_CHECKOUT', '') == '' and env.get(
+            'MLC_GIT_CHECKOUT_TAG', '') == '':
+        if env.get('MLC_TMP_GIT_CHECKOUT', '') != '':
+            env["MLC_GIT_CHECKOUT"] = env["MLC_TMP_GIT_CHECKOUT"]
+        else:
+            env["MLC_GIT_CHECKOUT"] = "master"
+
+    if env.get('MLC_GIT_URL', '') == '':
+        if env.get('MLC_TMP_GIT_URL', '') != '':
+            env["MLC_GIT_URL"] = env["MLC_TMP_GIT_URL"]
+        else:
+            env["MLC_GIT_URL"] = "https://github.com/mlcommons/mlperf_automotive"
+
+    if env.get("MLC_MLPERF_LAST_RELEASE", '') == '':
+        env["MLC_MLPERF_LAST_RELEASE"] = "v0.5"
+
+    if 'MLC_GIT_DEPTH' not in env:
+        env['MLC_GIT_DEPTH'] = ''
+
+    if 'MLC_GIT_RECURSE_SUBMODULES' not in env:
+        env['MLC_GIT_RECURSE_SUBMODULES'] = ''
+    submodules = []
+    possible_submodules = {
+        "pybind": "third_party/pybind",
+    }
+    for submodule in possible_submodules:
+        env_name = submodule.upper().replace("-", "_")
+        if is_true(env.get("MLC_SUBMODULE_" + env_name)):
+            submodules.append(possible_submodules[submodule])
+
+    env['MLC_GIT_SUBMODULES'] = ",".join(submodules)
+
+    if env.get('MLC_GIT_PATCH_FILENAME', '') != '':
+        patch_file_name = env['MLC_GIT_PATCH_FILENAME']
+        env['MLC_GIT_PATCH_FILEPATHS'] = os.path.join(
+            script_path, 'patch', patch_file_name)
+
+    need_version = env.get('MLC_VERSION', '')
+    versions = meta['versions']
+
+    if need_version != '' and not need_version in versions:
+        env['MLC_GIT_CHECKOUT'] = need_version
+
+    return {'return': 0}
+
+
+def postprocess(i):
+
+    env = i['env']
+    state = i['state']
+
+    automotive_root = env['MLC_MLPERF_INFERENCE_SOURCE']
+    env['MLC_MLPERF_INFERENCE_BEVFORMER_PATH'] = os.path.join(
+        automotive_root, 'automotive', 'camera-3d-detection')
+    env['MLC_MLPERF_INFERENCE_SSD_RESNET50_PATH'] = os.path.join(
+        automotive_root, 'automotive', '2d-object-detection')
+    env['MLC_MLPERF_INFERENCE_DEEPLABV3PLUS_PATH'] = os.path.join(
+        automotive_root, 'automotive', 'semantic-segmentation')
+
+    env['MLC_GET_DEPENDENT_CACHED_PATH'] = automotive_root
+
+#        20221024: we save and restore env in the main script and can clean env here for determinism
+#    if '+PYTHONPATH' not in env: env['+PYTHONPATH'] = []
+    env['+PYTHONPATH'] = []
+
+    if os.path.exists(os.path.join(automotive_root, "loadgen", "VERSION.txt")):
+        with open(os.path.join(automotive_root, "loadgen", "VERSION.txt")) as f:
+            version_info = f.read().strip()
+        env['MLC_MLPERF_INFERENCE_SOURCE_VERSION'] = version_info
+
+    if is_true(env.get('MLC_GET_MLPERF_IMPLEMENTATION_ONLY', '')):
+        return {'return': 0}
+
+    env['MLC_MLPERF_INFERENCE_CONF_PATH'] = os.path.join(
+        automotive_root, 'mlperf.conf')
+    env['+PYTHONPATH'].append(
+        os.path.join(
+            env['MLC_MLPERF_INFERENCE_SOURCE'],
+            'tools',
+            'submission'))
+
+    # To be uncommented after Pablo's PR is merged: https://github.com/mlcommons/mlperf_automotive/pull/14
+    # valid_models = get_valid_models(
+    #     env['MLC_MLPERF_LAST_RELEASE'],
+    #     env['MLC_MLPERF_INFERENCE_SOURCE'])
+
+    # state['MLC_MLPERF_AUTOMOTIVE_MODELS'] = valid_models
+
+    if env.get('MLC_GIT_REPO_CURRENT_HASH', '') != '':
+        env['MLC_VERSION'] += "-git-" + env['MLC_GIT_REPO_CURRENT_HASH']
+
+    return {'return': 0, 'version': env['MLC_VERSION']}
+
+
+def get_valid_models(mlperf_version, mlperf_path):
+
+    import sys
+
+    submission_checker_dir = os.path.join(mlperf_path, "tools", "submission")
+
+    sys.path.append(submission_checker_dir)
+
+    if not os.path.exists(os.path.join(
+            submission_checker_dir, "submission_checker.py")):
+        shutil.copy(os.path.join(submission_checker_dir, "submission-checker.py"), os.path.join(submission_checker_dir,
+                                                                                                "submission_checker.py"))
+
+    import submission_checker as checker
+
+    config = checker.MODEL_CONFIG
+
+    valid_models = config[mlperf_version]["models"]
+
+    return valid_models
diff --git a/script/get-mlperf-automotive-src/meta.yaml b/script/get-mlperf-automotive-src/meta.yaml
new file mode 100644
index 000000000..9fa26d5ca
--- /dev/null
+++ b/script/get-mlperf-automotive-src/meta.yaml
@@ -0,0 +1,103 @@
+alias: get-mlperf-automotive-src
+automation_alias: script
+automation_uid: 5b4e0237da074764
+cache: true
+category: MLPerf benchmark support
+default_env:
+  MLC_GIT_CHECKOUT_FOLDER: automotive
+  MLC_GIT_DEPTH: --depth 4
+  MLC_GIT_PATCH: 'no'
+  MLC_GIT_RECURSE_SUBMODULES: ''
+default_version: master
+deps:
+- tags: detect,os
+- names:
+  - python
+  - python3
+  tags: get,python3
+new_env_keys:
+- MLC_MLPERF_INFERENCE_BEVFORMER_PATH
+- MLC_MLPERF_INFERENCE_SSD_RESNET50_PATH
+- MLC_MLPERF_INFERENCE_DEEPLABV3PLUS_PATH
+- MLC_MLPERF_LAST_RELEASE
+- MLC_MLPERF_INFERENCE_SOURCE
+- MLC_MLPERF_INFERENCE_SOURCE_VERSION
+- +PYTHONPATH
+prehook_deps:
+- env:
+    MLC_GIT_CHECKOUT_PATH_ENV_NAME: MLC_MLPERF_INFERENCE_SOURCE
+  extra_cache_tags: automotive,src
+  force_env_keys:
+  - MLC_GIT_*
+  names:
+  - automotive-git-repo
+  tags: get,git,repo
+  update_tags_from_env_with_prefix:
+    _branch.:
+    - MLC_GIT_CHECKOUT
+    _repo.:
+    - MLC_GIT_URL
+    _sha.:
+    - MLC_GIT_SHA
+    _submodules.:
+    - MLC_GIT_SUBMODULES
+print_env_at_the_end:
+  MLC_MLPERF_INFERENCE_SOURCE: Path to MLPerf automotive benchmark source
+tags:
+- get
+- src
+- source
+- automotive
+- automotive-src
+- automotive-source
+- mlperf
+- mlcommons
+uid: c3842e6e35d947ef
+variations:
+  branch.#:
+    default_version: custom
+    env:
+      MLC_GIT_CHECKOUT: '#'
+    group: checkout
+  full-history:
+    env:
+      MLC_GIT_DEPTH: ''
+    group: git-history
+  no-recurse-submodules:
+    env:
+      MLC_GIT_RECURSE_SUBMODULES: ''
+  patch:
+    ad:
+      automotive-git-repo:
+        tags: _patch
+    env:
+      MLC_GIT_PATCH: 'yes'
+  pybind:
+    env:
+      MLC_SUBMODULE_PYBIND: 'yes'
+  recurse-submodules:
+    env:
+      MLC_GIT_RECURSE_SUBMODULES: ' --recurse-submodules'
+  repo.#:
+    env:
+      MLC_GIT_URL: '#'
+  sha.#:
+    env:
+      MLC_GIT_SHA: '#'
+    group: checkout
+  short-history:
+    default: true
+    env:
+      MLC_GIT_DEPTH: --depth 10
+    group: git-history
+  submodules.#:
+    env:
+      MLC_GIT_SUBMODULES: '#'
+versions:
+  custom:
+    env:
+      MLC_MLPERF_LAST_RELEASE: v0.5
+  master:
+    env:
+      MLC_MLPERF_LAST_RELEASE: v0.5
+      MLC_TMP_GIT_CHECKOUT: master
diff --git a/script/get-mlperf-automotive-utils/COPYRIGHT.md b/script/get-mlperf-automotive-utils/COPYRIGHT.md
new file mode 100644
index 000000000..d2ceead84
--- /dev/null
+++ b/script/get-mlperf-automotive-utils/COPYRIGHT.md
@@ -0,0 +1,9 @@
+# Copyright Notice
+
+© 2025-2026 MLCommons. All Rights Reserved.
+
+This file is licensed under the Apache License, Version 2.0 (the "License"). You may not use this file except in compliance with the License. A copy of the License can be obtained at:
+
+[Apache License, Version 2.0](http://www.apache.org/licenses/LICENSE-2.0)
+
+Unless required by applicable law or agreed to in writing, software distributed under the License is provided on an "AS IS" basis, without warranties or conditions of any kind, either express or implied. Please refer to the License for the specific language governing permissions and limitations under the License.
diff --git a/script/get-mlperf-automotive-utils/customize.py b/script/get-mlperf-automotive-utils/customize.py
new file mode 100644
index 000000000..7ae5d02bd
--- /dev/null
+++ b/script/get-mlperf-automotive-utils/customize.py
@@ -0,0 +1,36 @@
+from mlc import utils
+from utils import is_true
+import os
+import sys
+
+
+def preprocess(i):
+
+    os_info = i['os_info']
+
+    env = i['env']
+
+    meta = i['meta']
+
+    automation = i['automation']
+
+    quiet = is_true(env.get('MLC_QUIET', False))
+
+    utils_path = env['MLC_TMP_CURRENT_SCRIPT_PATH']
+
+    env['+PYTHONPATH'] = [utils_path]
+
+    submission_checker_dir = os.path.join(
+        env['MLC_MLPERF_INFERENCE_SOURCE'], "tools", "submission")
+
+    sys.path.append(submission_checker_dir)
+    sys.path.append(utils_path)
+
+    return {'return': 0}
+
+
+def postprocess(i):
+
+    env = i['env']
+
+    return {'return': 0}
diff --git a/script/get-mlperf-automotive-utils/meta.yaml b/script/get-mlperf-automotive-utils/meta.yaml
new file mode 100644
index 000000000..bdd5c667b
--- /dev/null
+++ b/script/get-mlperf-automotive-utils/meta.yaml
@@ -0,0 +1,25 @@
+alias: get-mlperf-automotive-utils
+automation_alias: script
+automation_uid: 5b4e0237da074764
+cache: false
+tags:
+- get
+- mlperf
+- automotive
+- util
+- utils
+- functions
+uid: c20cfade1c184f83
+deps:
+  - tags: get,mlperf,automotive,src
+    names:
+      - automotive-src
+new_env_keys:
+  - '+PYTHONPATH'
+  - MLC_MLPERF_INFERENCE_BEVFORMER_PATH
+  - MLC_MLPERF_INFERENCE_SSD_RESNET50_PATH
+  - MLC_MLPERF_INFERENCE_DEEPLABV3PLUS_PATH
+  - MLC_MLPERF_LAST_RELEASE
+  - MLC_MLPERF_INFERENCE_SOURCE
+  - MLC_MLPERF_INFERENCE_VERSION
+  - MLC_MLPERF_INFERENCE_SOURCE_VERSION
\ No newline at end of file
diff --git a/script/get-mlperf-automotive-utils/mlperf_utils.py b/script/get-mlperf-automotive-utils/mlperf_utils.py
new file mode 100644
index 000000000..f7441cedd
--- /dev/null
+++ b/script/get-mlperf-automotive-utils/mlperf_utils.py
@@ -0,0 +1,353 @@
+import sys
+import os
+import submission_checker as checker
+from log_parser import MLPerfLog
+
+
+def get_result_from_log(version, model, scenario,
+                        result_path, mode, automotive_src_version=None):
+
+    config = checker.Config(
+        version,
+        None,
+        ignore_uncommited=False,
+        skip_power_check=False,
+    )
+    mlperf_model = config.get_mlperf_model(model)
+    # scenario = checker.SCENARIO_MAPPING[scenario]
+
+    result = ''
+    power_result = None
+    valid = {}
+    if mode == "performance":
+        # has_power = os.path.exists(os.path.join(result_path, "..", "power"))
+        version_tuple = None
+        if automotive_src_version:
+            version_tuple = tuple(map(int, automotive_src_version.split('.')))
+
+        if version_tuple and version_tuple >= (4, 1, 22):
+            result_ = checker.get_performance_metric(
+                config, mlperf_model, result_path, scenario)
+        else:
+            result_ = checker.get_performance_metric(
+                config, mlperf_model, result_path, scenario, None, None, has_power)
+        mlperf_log = MLPerfLog(
+            os.path.join(
+                result_path,
+                "mlperf_log_detail.txt"))
+        if (
+            "result_validity" not in mlperf_log.get_keys()
+            or mlperf_log["result_validity"] != "VALID"
+        ):
+            valid['performance'] = False
+        else:
+            valid['performance'] = True
+
+        if "stream" in scenario.lower():
+            result = result_ / 1000000  # convert to milliseconds
+        else:
+            result = result_
+        result = str(round(result, 3))
+
+        # if has_power:
+        #     power_valid, power_metric, scenario, avg_power_efficiency = checker.get_power_metric(
+        #         config, scenario, result_path, True, result_)
+        #     power_result = f"{round(power_metric,3)},{round(avg_power_efficiency,3)}"
+        #     valid['power'] = power_valid
+
+    elif mode == "accuracy" and os.path.exists(os.path.join(result_path, 'accuracy.txt')):
+
+        acc_valid, acc_results, acc_targets, acc_limits = get_accuracy_metric(
+            config, mlperf_model, result_path)
+        valid['accuracy'] = acc_valid
+
+        if len(acc_results) == 1:
+            for acc in acc_results:
+                result = str(round(float(acc_results[acc]), 5))
+        else:
+            result = '('
+            result_list = []
+            for i, acc in enumerate(acc_results):
+                result_list.append(str(round(float(acc_results[acc]), 5)))
+            result += ", ".join(result_list) + ")"
+
+    return result, valid, power_result
+
+
+def get_accuracy_metric(config, model, path):
+
+    import re
+    is_valid = False
+    all_accuracy_valid = True
+    acc = None
+    result_acc = None
+    target = config.get_accuracy_target(model)
+    acc_upper_limit = config.get_accuracy_upper_limit(model)
+    patterns = []
+    acc_targets = []
+    acc_limits = [None] * (len(target) // 2)
+    up_patterns = [None] * (len(target) // 2)
+    acc_types = []
+
+    if acc_upper_limit is not None:
+        acc_limit_check = True
+
+        for ii in range(0, len(target), 2):
+            acc_type1, tmp = target[ii:ii + 2]
+            for i in range(0, len(acc_upper_limit), 2):
+                acc_type, acc_target = acc_upper_limit[i:i + 2]
+                if acc_type != acc_type1:
+                    continue
+                acc_limits[ii // 2] = acc_target
+                up_patterns[ii // 2] = checker.ACC_PATTERN[acc_type]
+
+    for i in range(0, len(target), 2):
+        acc_type, acc_target = target[i:i + 2]
+        acc_types.append(acc_type)
+        patterns.append(checker.ACC_PATTERN[acc_type])
+        acc_targets.append(acc_target)
+
+    acc_seen = [False for _ in acc_targets]
+    acc_results = {}
+    with open(os.path.join(path, "accuracy.txt"), "r", encoding="utf-8") as f:
+        for line in f:
+            for i, (pattern, acc_target, acc_type) in enumerate(
+                    zip(patterns, acc_targets, acc_types)):
+                m = re.match(pattern, line)
+                if m:
+                    acc = m.group(1)
+
+                    acc_results[acc_type] = acc
+
+                if acc is not None and float(acc) >= acc_target:
+                    all_accuracy_valid &= True
+                    acc_seen[i] = True
+                elif acc is not None:
+                    all_accuracy_valid = False
+                    # log.warning("%s accuracy not met: expected=%f, found=%s", path, acc_target, acc)
+                if i == 0 and acc:
+                    result_acc = acc
+                acc = None
+            if acc_upper_limit is not None:
+                for i, (pattern, acc_limit) in enumerate(
+                        zip(up_patterns, acc_limits)):
+                    if not pattern:
+                        continue
+                    m = re.match(pattern, line)
+                    if m:
+                        acc = m.group(1)
+                    if acc is not None and acc_upper_limit is not None and float(
+                            acc) > acc_limit:
+                        acc_limit_check = False
+                        # log.warning("%s accuracy not met: upper limit=%f, found=%s", path, acc_limit, acc)
+                    acc = None
+            if all(acc_seen):
+                break
+        is_valid = all_accuracy_valid & all(acc_seen)
+        if acc_upper_limit is not None:
+            is_valid &= acc_limit_check
+
+    return is_valid, acc_results, acc_targets, acc_limits
+
+
+def get_result_string(version, model, scenario, result_path, has_power, sub_res,
+                      division="open", system_json=None, model_precision="fp32", automotive_src_version=None):
+
+    config = checker.Config(
+        version,
+        None,
+        ignore_uncommited=False,
+        skip_power_check=False,
+    )
+    mlperf_model = config.get_mlperf_model(model)
+    performance_path = os.path.join(result_path, "performance", "run_1")
+    accuracy_path = os.path.join(result_path, "accuracy")
+    scenario = checker.SCENARIO_MAPPING[scenario.lower()]
+
+    fname = os.path.join(performance_path, "mlperf_log_detail.txt")
+    mlperf_log = MLPerfLog(fname)
+    effective_scenario = mlperf_log["effective_scenario"]
+    inferred = False
+    result = {}
+
+    version_tuple = None
+    if automotive_src_version:
+        version_tuple = tuple(map(int, automotive_src_version.split('.')))
+
+    if version_tuple and version_tuple >= (4, 1, 22):
+        performance_result = checker.get_performance_metric(
+            config, mlperf_model, performance_path, scenario)
+    else:
+        performance_result = checker.get_performance_metric(
+            config, mlperf_model, performance_path, scenario, None, None)
+    if "stream" in scenario.lower():
+        performance_result_ = performance_result / 1000000  # convert to milliseconds
+    else:
+        performance_result_ = performance_result
+    result['performance'] = round(performance_result_, 3)
+
+    if scenario != effective_scenario:
+        inferred, inferred_result = checker.get_inferred_result(
+            scenario, effective_scenario, performance_result, mlperf_log, config, False)
+
+    # if has_power:
+    #     is_valid, power_metric, scenario, avg_power_efficiency = checker.get_power_metric(
+    #         config, scenario, performance_path, True, performance_result)
+    #     if "stream" in scenario.lower():
+    #         power_metric_unit = "milliJoules"
+    #     else:
+    #         power_metric_unit = "Watts"
+    #     power_result_string = f"`Power consumed`: `{round(power_metric, 3)} {power_metric_unit}`, `Power efficiency`: `{round(avg_power_efficiency * 1000, 3)} samples per Joule`"
+
+    #     power_result = round(power_metric, 3)
+    #     power_efficiency_result = round(avg_power_efficiency, 3)
+    #     result['power'] = power_result
+    #     result['power_efficiency'] = power_efficiency_result
+
+    # compliance_list = ["TEST01", "TEST04", "TEST06"]
+    # if division == "closed":
+    #     for test in compliance_list:
+    #         test_path = os.path.join(result_path, test)
+    #         if os.path.exists(
+    #                 test_path):  # We dont consider missing test folders now - submission checker will do that
+    #             # test_pass = checker.check_compliance_dir(test_path, mlperf_model, scenario, config, "closed", system_json, sub_res)
+    #             test_pass = checker.check_compliance_perf_dir(
+    #                 test_path) if test != "TEST06" else True
+    #             if test_pass and test in ["TEST01", "TEST06"]:
+    #                 # test_pass = checker.check_compliance_acc_dir(test_path, mlperf_model, config)
+    #                 pass  # accuracy truncation script is done after submission generation. We assume here that it'll pass
+    #             if test_pass:
+    #                 result[test] = "passed"
+    #             else:
+    #                 result[test] = "failed"
+
+    acc_valid, acc_results, acc_targets, acc_limits = get_accuracy_metric(
+        config, mlperf_model, accuracy_path)
+
+    result_field = checker.RESULT_FIELD[effective_scenario]
+
+    performance_result_string = f"`{result_field}`: `{performance_result}`\n"
+    if inferred:
+        inferred_result_field = checker.RESULT_FIELD[scenario]
+        performance_result_string += f"Inferred result: `{inferred_result_field}`: `{inferred_result}`  \n"
+
+    accuracy_result_string = ''
+    accuracy_results = []
+    for i, acc in enumerate(acc_results):
+        accuracy_results.append(str(round(float(acc_results[acc]), 5)))
+        accuracy_result_string += f"`{acc}`: `{round(float(acc_results[acc]), 5)}`"
+        if not acc_limits or not acc_limits[i]:
+            accuracy_result_string += f", Required accuracy for closed division `>= {round(acc_targets[i], 5)}`"
+        else:
+            accuracy_result_string += f", Required accuracy for closed division `>= {round(acc_targets[i], 5)}` and `<= {round(acc_limits[i], 5)}`"
+        accuracy_result_string += "\n"
+
+    if len(accuracy_results) == 1:
+        accuracy_result = accuracy_results[0]
+    else:
+        accuracy_result = "(" + ", ".join(accuracy_results) + ")"
+    result['accuracy'] = accuracy_result
+
+    result_string = f"\n\n## Results\n"
+    result_string += f"\nPlatform: {sub_res}\n"
+    result_string += f"\nModel Precision: {model_precision}\n"
+    result_string += "\n### Accuracy Results \n" + accuracy_result_string
+    result_string += "\n### Performance Results \n" + performance_result_string
+    # if has_power:
+    #     result_string += "\n### Power Results \n" + power_result_string
+
+    return result_string, result
+
+
+def get_result_table(results):
+
+    headers = [
+        "Model",
+        "Scenario",
+        "Accuracy",
+        "Throughput",
+        "Latency (in ms)",
+        "Power Efficiency (in samples/J)",
+        "TEST01",
+        "TEST04"]
+    table = []
+    for model in results:
+        for scenario in results[model]:
+            row = []
+            row.append(model)
+            row.append(scenario)
+            if results[model][scenario].get('accuracy'):
+                val = str(results[model][scenario]['accuracy'])
+                if not results[model][scenario].get('accuracy_valid', True):
+                    val = "X " + val
+                row.append(val)
+            else:
+                row.append("-")
+
+            if results[model][scenario].get('performance'):
+
+                if "stream" in scenario.lower():
+                    if float(results[model][scenario]['performance']) == 0:
+                        row.append("-")
+                    elif scenario.lower() == "singlestream":
+                        val_qps = str(
+                            round(
+                                1000 /
+                                float(
+                                    results[model][scenario]['performance']),
+                                3))
+                        if not results[model][scenario].get(
+                                'performance_valid', True):  # we explicitly mark invalid results
+                            val_qps = "X " + val_qps
+                        row.append(val_qps)
+                    elif scenario.lower() == "multistream":
+                        val_qps = str(
+                            round(
+                                8000 /
+                                float(
+                                    results[model][scenario]['performance']),
+                                3))
+                        if not results[model][scenario].get(
+                                'performance_valid', True):
+                            val_qps = "X " + val_qps
+                        row.append(val_qps)
+                    val = str(results[model][scenario]['performance'])
+                    if not results[model][scenario].get(
+                            'performance_valid', True):
+                        val = "X " + val
+                    row.append(val)
+                else:
+                    val = str(results[model][scenario]['performance'])
+                    if not results[model][scenario].get(
+                            'performance_valid', True):
+                        val = "X " + val
+                    row.append(val)
+                    row.append("-")
+
+            # val1 = results[model][scenario].get('TEST01')
+            # val2 = results[model][scenario].get('TEST05')
+            # val3 = results[model][scenario].get('TEST04')
+
+            # if results[model][scenario].get('power','') != '':
+            #    row.append(results[model][scenario]['power'])
+            # if results[model][scenario].get('power_efficiency', '') != '':
+            #     val = str(results[model][scenario]['power_efficiency'])
+            #     if not results[model][scenario].get('power_valid', True):
+            #         val = "X " + val
+            #     row.append(val)
+            # elif val1 or val3:  # Don't output unless there are any further column data
+            #     row.append(None)
+
+            # if val1:
+            #     row.append(val1)
+            #     if val3:
+            #         row.append(val3)
+
+            # else:
+            #     if val3:
+            #         row.append("missing")
+            #         row.append(val3)
+
+            table.append(row)
+
+    return table, headers
diff --git a/script/get-mlperf-inference-loadgen/meta.yaml b/script/get-mlperf-inference-loadgen/meta.yaml
index ad59163fd..e841b3293 100644
--- a/script/get-mlperf-inference-loadgen/meta.yaml
+++ b/script/get-mlperf-inference-loadgen/meta.yaml
@@ -24,10 +24,21 @@ deps:
   - MLC_GIT_CHECKOUT
   names:
   - inference-src-loadgen
-  skip_if_env:
+  skip_if_any_env:
     MLC_MLPERF_INFERENCE_LOADGEN_DOWNLOAD:
     - 'YES'
+    MLC_INFERENCE_AUTOMOTIVE_REPO: 
+    - 'YES'
   tags: get,mlcommons,inference,src
+- force_env_keys:
+  - MLC_GIT_URL
+  - MLC_GIT_CHECKOUT
+  names:
+  - automotive-src
+  enable_if_env:
+    MLC_INFERENCE_AUTOMOTIVE_REPO: 
+    - 'YES'
+  tags: get,mlcommons,automotive,src
 - enable_if_env:
     MLC_MLPERF_INFERENCE_LOADGEN_DOWNLOAD:
     - 'YES'
@@ -49,7 +60,7 @@ deps:
 - enable_if_env:
     MLC_HOST_OS_TYPE:
     - windows
-  skip_if_env:
+  skip_if_any_env:
     MLC_TMP_MLPERF_INFERENCE_LOADGEN_INSTALL_FROM_PIP:
     - 'yes'
   names:
@@ -155,7 +166,13 @@ variations:
       '+ CXXFLAGS':
         - '-Werror'
         - '-Wno-unused-parameter'
-
+  automotive:
+    env:
+      MLC_INFERENCE_AUTOMOTIVE_REPO: 'YES'
+  inference:
+    default: true
+    env:
+      MLC_INFERENCE_AUTOMOTIVE_REPO: 'NO'
 versions:
   custom:
     add_deps:
diff --git a/script/get-mlperf-inference-nvidia-common-code/meta.yaml b/script/get-mlperf-inference-nvidia-common-code/meta.yaml
index 3c0657dda..5fda7a3dd 100644
--- a/script/get-mlperf-inference-nvidia-common-code/meta.yaml
+++ b/script/get-mlperf-inference-nvidia-common-code/meta.yaml
@@ -32,6 +32,10 @@ variations:
     group: repo-owner
   nvidia-only:
     group: repo-owner
+  v5.0:
+    add_deps_recursive:
+      mlperf-inference-results:
+        tags: _code-only,_v5.0
 versions:
   r2.1:
     add_deps_recursive:
diff --git a/script/get-mlperf-inference-results/meta.yaml b/script/get-mlperf-inference-results/meta.yaml
index 8b1da1310..9b42fdf2a 100644
--- a/script/get-mlperf-inference-results/meta.yaml
+++ b/script/get-mlperf-inference-results/meta.yaml
@@ -7,7 +7,6 @@ default_env:
   MLC_GIT_CHECKOUT: master
   MLC_GIT_DEPTH: --depth 1
   MLC_GIT_PATCH: 'no'
-default_version: v4.0
 deps: []
 new_env_keys:
 - MLC_MLPERF_INFERENCE_RESULTS_*
@@ -65,6 +64,11 @@ variations:
       GITHUB_REPO_OWNER: GATEOverflow
       NVIDIA_ONLY: 'yes'
     group: source-repo
+  v5.0:
+    env:
+      MLC_GIT_URL: https://github.com/<<<GITHUB_REPO_OWNER>>>/inference_results_v5.0.git
+      MLC_MLPERF_INFERENCE_RESULTS_VERSION_NAME: v5.0
+      MLC_VERSION: "v5.0"
 versions:
   v2.1:
     env:
@@ -86,3 +90,4 @@ versions:
     env:
       MLC_GIT_URL: https://github.com/<<<GITHUB_REPO_OWNER>>>/inference_results_v4.1.git
       MLC_MLPERF_INFERENCE_RESULTS_VERSION_NAME: v4.1
+
diff --git a/script/get-mlperf-inference-src/meta.yaml b/script/get-mlperf-inference-src/meta.yaml
index bd76d04da..852c85d68 100644
--- a/script/get-mlperf-inference-src/meta.yaml
+++ b/script/get-mlperf-inference-src/meta.yaml
@@ -27,7 +27,6 @@ new_env_keys:
 - MLC_MLPERF_INFERENCE_RGAT_PATH
 - MLC_MLPERF_INFERENCE_SOURCE
 - MLC_MLPERF_INFERENCE_SOURCE_VERSION
-- MLC_MLPERF_INFERENCE_VERSION
 - MLC_MLPERF_INFERENCE_VISION_PATH
 - MLC_MLPERF_LAST_RELEASE
 - MLC_MLPERF_INFERENCE_POINTPAINTING_PATH
diff --git a/script/get-nvidia-mitten/customize.py b/script/get-nvidia-mitten/customize.py
index a2acfde43..8d8693ca0 100644
--- a/script/get-nvidia-mitten/customize.py
+++ b/script/get-nvidia-mitten/customize.py
@@ -5,8 +5,7 @@
 def preprocess(i):
 
     os_info = i['os_info']
-
-    # TBD
+    env = i['env']
 
     return {'return': 0}
 
diff --git a/script/get-nvidia-mitten/meta.yaml b/script/get-nvidia-mitten/meta.yaml
index 3073438bb..80e414a32 100644
--- a/script/get-nvidia-mitten/meta.yaml
+++ b/script/get-nvidia-mitten/meta.yaml
@@ -3,7 +3,7 @@ automation_alias: script
 automation_uid: 5b4e0237da074764
 cache: true
 category: MLPerf benchmark support
-default_version: master
+default_version: main
 deps:
 - tags: detect,os
 - names:
@@ -11,12 +11,14 @@ deps:
   - python
   tags: get,python3
 - tags: get,generic-python-lib,_pycuda
-  version: 2022.2.2
+  names:
+    - pycuda
 - env:
     MLC_GIT_CHECKOUT_PATH_ENV_NAME: MLC_NVIDIA_MITTEN_SRC
   extra_cache_tags: nvidia,mitten,src
   force_env_keys:
   - MLC_GIT_CHECKOUT
+  - MLC_GIT_PATCH_FILEPATHS
   names:
   - nvidia-mitten-git-src
   tags: get,git,_repo.https://github.com/NVIDIA/mitten
@@ -31,3 +33,14 @@ tags:
 - mitten
 - nvidia-mitten
 uid: 1c045f2902374de9
+variations:
+  patched:
+    group: numpy-patch
+    default: true
+    adr:
+      nvidia-mitten-git-src:
+        tags: _patch
+    env: 
+      MLC_GIT_PATCH_FILEPATHS: <<<MLC_TMP_CURRENT_SCRIPT_PATH>>>/patch/numpy-mitten-v5.0.patch
+  default:
+    group: numpy-patch
diff --git a/script/get-nvidia-mitten/patch/numpy-mitten-v5.0.patch b/script/get-nvidia-mitten/patch/numpy-mitten-v5.0.patch
new file mode 100644
index 000000000..b89abe2ab
--- /dev/null
+++ b/script/get-nvidia-mitten/patch/numpy-mitten-v5.0.patch
@@ -0,0 +1,13 @@
+diff --git a/setup.cfg b/setup.cfg
+index 4976354..798175e 100644
+--- a/setup.cfg
++++ b/setup.cfg
+@@ -21,7 +21,7 @@ install_requires =
+     graphlib_backport >=1.0.3;python_version<'3.9'
+     requests >=2.28.1
+     tqdm >=4.65.0
+-    numpy >=1.22.0, <1.24.0
++    numpy >=1.26.4
+     GitPython >=3.1.31
+     pandas
+     opencv-python
diff --git a/script/get-nvidia-mitten/run.sh b/script/get-nvidia-mitten/run.sh
index ac0dc16b2..33f3f5b90 100644
--- a/script/get-nvidia-mitten/run.sh
+++ b/script/get-nvidia-mitten/run.sh
@@ -1,4 +1,6 @@
 #!/bin/bash
 cd ${MLC_NVIDIA_MITTEN_SRC}
-${MLC_PYTHON_BIN_WITH_PATH} -m pip install .
+test $? -eq 0 || exit $?
+PIP_EXTRA=`python3 -c "import importlib.metadata; print(' --break-system-packages ' if int(importlib.metadata.version('pip').split('.')[0]) >= 23 else '')"`
+${MLC_PYTHON_BIN_WITH_PATH} -m pip install . ${PIP_EXTRA}
 test $? -eq 0 || exit $?
diff --git a/script/get-oneapi/COPYRIGHT.md b/script/get-oneapi/COPYRIGHT.md
new file mode 100644
index 000000000..d2ceead84
--- /dev/null
+++ b/script/get-oneapi/COPYRIGHT.md
@@ -0,0 +1,9 @@
+# Copyright Notice
+
+© 2025-2026 MLCommons. All Rights Reserved.
+
+This file is licensed under the Apache License, Version 2.0 (the "License"). You may not use this file except in compliance with the License. A copy of the License can be obtained at:
+
+[Apache License, Version 2.0](http://www.apache.org/licenses/LICENSE-2.0)
+
+Unless required by applicable law or agreed to in writing, software distributed under the License is provided on an "AS IS" basis, without warranties or conditions of any kind, either express or implied. Please refer to the License for the specific language governing permissions and limitations under the License.
diff --git a/script/get-one-api/customize.py b/script/get-oneapi/customize.py
similarity index 68%
rename from script/get-one-api/customize.py
rename to script/get-oneapi/customize.py
index 0f6e78b10..9ad62e0b8 100644
--- a/script/get-one-api/customize.py
+++ b/script/get-oneapi/customize.py
@@ -28,26 +28,30 @@ def preprocess(i):
                                            'run_script_input': i['run_script_input'],
                                            'recursion_spaces': recursion_spaces})
         if r['return'] > 0:
-            # Uncomment when MLC script for installing oneapi compiler is integrated
-            # Initial finding suggests that oneapi could be installed without
-            # hastle in linux using apt, but is tricky in windows
-
-            #           if r['return'] == 16:
-            #               if env.get('MLC_TMP_FAIL_IF_NOT_FOUND','').lower() == 'yes':
-            #                   return r
-            #
-            #               print (recursion_spaces+'    # {}'.format(r['error']))
-            #
-            #               # Attempt to run installer
-            #               r = {'return':0, 'skip':True, 'script':{'tags':'install,gcc,src'}}
-
-            return r
+            r = i['automation'].run_native_script(
+                {'run_script_input': i['run_script_input'], 'env': env, 'script_name': 'install'})
+            if r['return'] > 0:
+                return r
+            version_prefix = env['MLC_ONEAPI_INSTALL_VERSION_PREFIX']
+            env['MLC_TMP_PATH'] = os.path.join(
+                os.getcwd(), "install", version_prefix, "bin")
+
+            r = i['automation'].find_artifact({'file_name': file_name_c,
+                                               'env': env,
+                                               'os_info': os_info,
+                                               'default_path_env_key': 'PATH',
+                                               'detect_version': True,
+                                               'env_path_key': 'MLC_ICX_BIN_WITH_PATH',
+                                               'run_script_input': i['run_script_input'],
+                                               'recursion_spaces': recursion_spaces})
+            if r['return'] > 0:
+                return r
 
     return {'return': 0}
 
 
 def detect_version(i):
-    r = i['automation'].parse_version({'match_text': r'oneAPI\s+.*\(([\d.]+)\)',
+    r = i['automation'].parse_version({'match_text': r'oneAPI\s+.* Compiler\s+([\d+.]+)',
                                        'group_number': 1,
                                        'env_key': 'MLC_ONEAPI_VERSION',
                                        'which_env': i['env']})
@@ -90,6 +94,16 @@ def postprocess(i):
     env['MLC_ONEAPI_COMPILER_WITH_PATH'] = found_file_path
     env['MLC_ONEAPI_COMPILER_FLAG_VERSION'] = 'version'
 
+    env['MLC_DEPENDENT_CACHED_PATH'] = found_file_path
+
+    list_keys = ['+LD_LIBRARY_PATH']
+    for key in list_keys:
+        if not env.get(key):
+            env[key] = []
+
+    env['+LD_LIBRARY_PATH'].append(os.path.join(
+        env['MLC_ONEAPI_INSTALLED_PATH'], "lib"))
+
     # env['MLC_COMPILER_FLAGS_FAST'] = "-O3"
     # env['MLC_LINKER_FLAGS_FAST'] = "-O3"
     # env['MLC_COMPILER_FLAGS_DEBUG'] = "-O0"
diff --git a/script/get-oneapi/install.sh b/script/get-oneapi/install.sh
new file mode 100644
index 000000000..59d523b6a
--- /dev/null
+++ b/script/get-oneapi/install.sh
@@ -0,0 +1,16 @@
+#!/bin/bash
+set -e
+wget -nc ${MLC_ONEAPI_INSTALL_URL_BASE}/${MLC_ONEAPI_INSTALL_FILENAME}
+rm -rf install
+mkdir install
+cmd="bash ./${MLC_ONEAPI_INSTALL_FILENAME} -a --silent --cli --eula accept  --install-dir ${PWD}/install"
+
+echo $cmd
+eval $cmd
+
+if [[ ${MLC_ONEAPI_FORTRAN} == 'yes' ]] then
+  wget -nc https://registrationcenter-download.intel.com/akdlm/IRC_NAS/2238465b-cfc7-4bf8-ad04-e55cb6577cba/intel-fortran-essentials-2025.1.1.8_offline.sh
+  cmd="bash ./intel-fortran-essentials-2025.1.1.8_offline.sh -a --silent --cli --eula accept --install-dir ${PWD}/install"
+  echo $cmd
+  eval $cmd
+fi
diff --git a/script/get-one-api/meta.yaml b/script/get-oneapi/meta.yaml
similarity index 54%
rename from script/get-one-api/meta.yaml
rename to script/get-oneapi/meta.yaml
index 47cf218b0..14394cf2a 100644
--- a/script/get-one-api/meta.yaml
+++ b/script/get-oneapi/meta.yaml
@@ -4,6 +4,7 @@ automation_uid: 5b4e0237da074764
 cache: true
 category: Compiler automation
 clean_files: []
+default_version: 2025.1.1
 deps:
 - tags: detect,os
 name: Detect or install OneAPI compiler
@@ -12,6 +13,8 @@ new_env_keys:
 - MLC_ONEAPI_COMPILER_*
 - MLC_COMPILER_*
 - MLC_LINKER_*
+- +PATH
+- +LD_LIBRARY_PATH
 
 input_mapping:
   oneapi_dir: MLC_ONEAPI_DIR_PATH
@@ -25,7 +28,19 @@ tags:
 - compiler
 - get-oneapi
 uid: 1af872e81ef54742
+
+versions:
+  2025.1.1:
+    env:
+      MLC_ONEAPI_INSTALL_URL_BASE: https://registrationcenter-download.intel.com/akdlm/IRC_NAS/6bfca885-4156-491e-849b-1cd7da9cc760
+      MLC_ONEAPI_INSTALL_FILENAME: intel-oneapi-base-toolkit-2025.1.1.36_offline.sh
+      MLC_ONEAPI_INSTALL_VERSION_PREFIX: '2025.1'
+      MLC_VERSION: '2025.1.1'
+
 variations:
   path.#:
     env:
       MLC_ONEAPI_DIR_PATH: "#"
+  fortran:
+    env:
+      MLC_ONEAPI_FORTRAN: 'yes'
diff --git a/script/get-one-api/run.bat b/script/get-oneapi/run.bat
similarity index 100%
rename from script/get-one-api/run.bat
rename to script/get-oneapi/run.bat
diff --git a/script/get-one-api/run.sh b/script/get-oneapi/run.sh
similarity index 100%
rename from script/get-one-api/run.sh
rename to script/get-oneapi/run.sh
diff --git a/script/get-preprocessed-dataset-cognata/COPYRIGHT.md b/script/get-preprocessed-dataset-cognata/COPYRIGHT.md
new file mode 100644
index 000000000..2d6a2775e
--- /dev/null
+++ b/script/get-preprocessed-dataset-cognata/COPYRIGHT.md
@@ -0,0 +1,9 @@
+# Copyright Notice
+
+© 2023-2025 MLCommons. All Rights Reserved.
+
+This file is licensed under the Apache License, Version 2.0 (the "License"). You may not use this file except in compliance with the License. A copy of the License can be obtained at:
+
+[Apache License, Version 2.0](http://www.apache.org/licenses/LICENSE-2.0)
+
+Unless required by applicable law or agreed to in writing, software distributed under the License is provided on an "AS IS" basis, without warranties or conditions of any kind, either express or implied. Please refer to the License for the specific language governing permissions and limitations under the License.
diff --git a/script/get-preprocessed-dataset-cognata/README.md b/script/get-preprocessed-dataset-cognata/README.md
new file mode 100644
index 000000000..fee3d0ae4
--- /dev/null
+++ b/script/get-preprocessed-dataset-cognata/README.md
@@ -0,0 +1 @@
+Please see [https://docs.mlcommons.org/cm4mlops/scripts/AI-ML-datasets/get-preprocessed-dataset-kits19](https://docs.mlcommons.org/cm4mlops/scripts/AI-ML-datasets/get-preprocessed-dataset-kits19) for the documentation of this CM script.
diff --git a/script/get-preprocessed-dataset-cognata/customize.py b/script/get-preprocessed-dataset-cognata/customize.py
new file mode 100644
index 000000000..c77e3bb17
--- /dev/null
+++ b/script/get-preprocessed-dataset-cognata/customize.py
@@ -0,0 +1,25 @@
+from mlc import utils
+import os
+import shutil
+from utils import is_true
+
+
+def preprocess(i):
+
+    env = i['env']
+
+    if env.get('MLC_NUSCENES_DATASET_TYPE', '') == "prebuilt" and env.get(
+            'MLC_PREPROCESSED_DATASET_COGNATA_PATH', '') == '':
+        env['MLC_TMP_REQUIRE_DOWNLOAD'] = "yes"
+
+    return {'return': 0}
+
+
+def postprocess(i):
+    env = i['env']
+    if is_true(env.get('MLC_TMP_REQUIRE_DOWNLOAD', '')):
+        env['MLC_PREPROCESSED_DATASET_COGNATA_PATH'] = os.path.join(
+            env['MLC_PREPROCESSED_DATASET_COGNATA_PATH'],
+            env['MLC_DATASET_COGNATA_EXTRACTED_FOLDER_NAME'])
+
+    return {'return': 0}
diff --git a/script/get-preprocessed-dataset-cognata/meta.yaml b/script/get-preprocessed-dataset-cognata/meta.yaml
new file mode 100644
index 000000000..940351310
--- /dev/null
+++ b/script/get-preprocessed-dataset-cognata/meta.yaml
@@ -0,0 +1,114 @@
+alias: get-preprocessed-dataset-cognata
+automation_alias: script
+automation_uid: 5b4e0237da074764
+cache: true
+category: AI/ML datasets
+default_env:
+  MLC_DATASET: cognata
+new_env_keys:
+- MLC_PREPROCESSED_DATASET_*
+tags:
+- get
+- dataset
+- cognata
+- preprocessed
+uid: 29b3a984ff444de9
+print_env_at_the_end:
+  MLC_PREPROCESSED_DATASET_COGNATA_PATH: Preprocessed Cognata dataset path
+variations:
+  validation:
+    default: true
+    group: dataset-type
+    env:
+      MLC_DATASET_COGNATA_TYPE: validation
+  calibration:
+    group: dataset-type
+    env:
+      MLC_DATASET_COGNATA_TYPE: calibration
+  2d_obj_det:
+    default: true
+    group: task
+    env:
+      MLC_DATASET_COGNATA_TASK: 2d_object_detection
+  segmentation:
+    group: task
+    env:
+      MLC_DATASET_COGNATA_TASK: segmentation
+  validation,2d_obj_det:
+    env:
+      MLC_DATASET_COGNATA_EXTRACTED_FOLDER_NAME: val_2d
+      MLC_DATASET_COGNATA_TAR_FILENAME: val_2d.tar.gz
+      MLC_DOWNLOAD_URL: mlc-cognata:mlc_cognata_dataset/preprocessed_2d/<<<MLC_DATASET_COGNATA_TAR_FILENAME>>>
+  calibration,2d_obj_det:
+    env:
+      MLC_DATASET_COGNATA_EXTRACTED_FOLDER_NAME: calib_2d
+      MLC_DATASET_COGNATA_TAR_FILENAME: calib_2d.tar.gz
+      MLC_DOWNLOAD_URL: mlc-cognata:mlc_cognata_dataset/preprocessed_2d/<<<MLC_DATASET_COGNATA_TAR_FILENAME>>>
+  validation,segmentation:
+    env:
+      MLC_DATASET_COGNATA_EXTRACTED_FOLDER_NAME: val_seg
+      MLC_DATASET_COGNATA_TAR_FILENAME: val_seg.tar.gz
+      MLC_DOWNLOAD_URL: mlc-cognata:mlc_cognata_dataset/preprocessed_seg/<<<MLC_DATASET_COGNATA_TAR_FILENAME>>>
+  calibration,segmentation:
+    env:
+      MLC_DATASET_COGNATA_EXTRACTED_FOLDER_NAME: calib_seg
+      MLC_DATASET_COGNATA_TAR_FILENAME: calib_seg.tar.gz
+      MLC_DOWNLOAD_URL: mlc-cognata:mlc_cognata_dataset/preprocessed_seg/<<<MLC_DATASET_COGNATA_TAR_FILENAME>>>
+  prebuilt:
+    default: true
+    group: dataset-src
+    env:
+      MLC_NUSCENES_DATASET_TYPE: prebuilt
+      MLC_DOWNLOAD_FINAL_ENV_NAME: MLC_PREPROCESSED_DATASET_COGNATA_PATH
+      MLC_EXTRACT_FINAL_ENV_NAME: MLC_PREPROCESSED_DATASET_COGNATA_PATH
+      MLC_DOWNLOAD_EXTRA_OPTIONS: ' --include '
+  mlc:
+    group: download-src
+    default: true
+    prehook_deps:
+      - tags: get,rclone
+        enable_if_env:
+          MLC_TMP_REQUIRE_DOWNLOAD:
+          - yes
+      - tags: get,rclone-config,_config-name.mlc-cognata
+        force_cache: true
+        enable_if_env:
+          MLC_TMP_REQUIRE_DOWNLOAD:
+          - yes
+        env:
+          MLC_RCLONE_DRIVE_FOLDER_ID: 1u5FDoeXHVtDrd4zClE47Gmyr7iLFidz1
+      - enable_if_env:
+          MLC_TMP_REQUIRE_DOWNLOAD:
+          - 'yes'
+        extra_cache_tags: cognata,dataset
+        force_cache: true
+        names:
+          - dae
+        tags: download-and-extract
+        force_env_keys:
+          - MLC_OUTDIRNAME  
+        update_tags_from_env_with_prefix:
+          _url.:
+            - MLC_DOWNLOAD_URL
+    env:
+      MLC_DOWNLOAD_SRC: mlcommons
+  rclone:
+    group: download-tool
+    add_deps_recursive:
+      dae:
+        tags: _rclone
+    default: true
+  dry-run:
+    group: run-mode
+    env:
+      MLC_DOWNLOAD_MODE: dry
+  dry-run,rclone:
+    env:
+      MLC_DOWNLOAD_EXTRA_OPTIONS: --dry-run
+tests:
+  run_inputs:
+  - variations_list:
+      - validation,prebuilt,2d_obj_det,rclone,mlc,dry-run
+      - calibration,prebuilt,2d_obj_det,rclone,mlc,dry-run
+      - validation,prebuilt,segmentation,rclone,mlc,dry-run
+      - calibration,prebuilt,segmentation,rclone,mlc,dry-run
\ No newline at end of file
diff --git a/script/get-preprocessed-dataset-cognata/run.sh b/script/get-preprocessed-dataset-cognata/run.sh
new file mode 100644
index 000000000..0c141b8e6
--- /dev/null
+++ b/script/get-preprocessed-dataset-cognata/run.sh
@@ -0,0 +1,9 @@
+#!/bin/bash
+
+if [[ "$MLC_DOWNLOAD_MODE" != "dry" && "$MLC_TMP_REQUIRE_DOWNLOAD" = "yes" ]]; then
+  cd "${MLC_PREPROCESSED_DATASET_COGNATA_PATH}" || exit
+  for f in *.tar.gz; do 
+    tar -xzvf "$f" || { echo "Failed to extract $f"; exit 1; }
+  done
+  cd - || exit
+fi
\ No newline at end of file
diff --git a/script/get-preprocessed-dataset-nuscenes/COPYRIGHT.md b/script/get-preprocessed-dataset-nuscenes/COPYRIGHT.md
new file mode 100644
index 000000000..2d6a2775e
--- /dev/null
+++ b/script/get-preprocessed-dataset-nuscenes/COPYRIGHT.md
@@ -0,0 +1,9 @@
+# Copyright Notice
+
+© 2023-2025 MLCommons. All Rights Reserved.
+
+This file is licensed under the Apache License, Version 2.0 (the "License"). You may not use this file except in compliance with the License. A copy of the License can be obtained at:
+
+[Apache License, Version 2.0](http://www.apache.org/licenses/LICENSE-2.0)
+
+Unless required by applicable law or agreed to in writing, software distributed under the License is provided on an "AS IS" basis, without warranties or conditions of any kind, either express or implied. Please refer to the License for the specific language governing permissions and limitations under the License.
diff --git a/script/get-preprocessed-dataset-nuscenes/README.md b/script/get-preprocessed-dataset-nuscenes/README.md
new file mode 100644
index 000000000..fee3d0ae4
--- /dev/null
+++ b/script/get-preprocessed-dataset-nuscenes/README.md
@@ -0,0 +1 @@
+Please see [https://docs.mlcommons.org/cm4mlops/scripts/AI-ML-datasets/get-preprocessed-dataset-kits19](https://docs.mlcommons.org/cm4mlops/scripts/AI-ML-datasets/get-preprocessed-dataset-kits19) for the documentation of this CM script.
diff --git a/script/get-preprocessed-dataset-nuscenes/customize.py b/script/get-preprocessed-dataset-nuscenes/customize.py
new file mode 100644
index 000000000..5236b5c78
--- /dev/null
+++ b/script/get-preprocessed-dataset-nuscenes/customize.py
@@ -0,0 +1,36 @@
+from mlc import utils
+import os
+import shutil
+from utils import is_true
+
+
+def preprocess(i):
+
+    env = i['env']
+
+    if env.get('MLC_NUSCENES_DATASET_TYPE', '') == "prebuilt" and env.get(
+            'MLC_PREPROCESSED_DATASET_NUSCENES_PATH', '') == '':
+        env['MLC_TMP_REQUIRE_DOWNLOAD'] = "yes"
+
+    return {'return': 0}
+
+
+def postprocess(i):
+    env = i['env']
+
+    if is_true(env.get('MLC_TMP_REQUIRE_DOWNLOAD', '')):
+        env['MLC_PREPROCESSED_DATASET_NUSCENES_PATH'] = os.path.join(
+            env['MLC_PREPROCESSED_DATASET_NUSCENES_PATH'],
+            env['MLC_DATASET_NUSCENES_EXTRACTED_FOLDER_NAME'])
+        if env.get(
+                'MLC_PREPROCESSED_DATASET_NUSCENES_SCENE_LENGTHS_PATH', '') != '':
+            shutil.copy(
+                os.path.join(
+                    env['MLC_PREPROCESSED_DATASET_NUSCENES_SCENE_LENGTHS_PATH'],
+                    env['MLC_DATASET_NUSCENES_SCENE_PICKLE_FILENAME']),
+                os.path.join(
+                    os.path.dirname(
+                        env['MLC_PREPROCESSED_DATASET_NUSCENES_PATH'].rstrip("/")),
+                    env['MLC_DATASET_NUSCENES_SCENE_PICKLE_FILENAME']))
+
+    return {'return': 0}
diff --git a/script/get-preprocessed-dataset-nuscenes/meta.yaml b/script/get-preprocessed-dataset-nuscenes/meta.yaml
new file mode 100644
index 000000000..6436574a6
--- /dev/null
+++ b/script/get-preprocessed-dataset-nuscenes/meta.yaml
@@ -0,0 +1,132 @@
+alias: get-preprocessed-dataset-nuscenes
+automation_alias: script
+automation_uid: 5b4e0237da074764
+cache: true
+category: AI/ML datasets
+default_env:
+  MLC_DATASET: nuscenes
+new_env_keys:
+- MLC_PREPROCESSED_DATASET_*
+tags:
+- get
+- dataset
+- nuscenes
+- preprocessed
+uid: 0e403a2861984a4e
+print_env_at_the_end:
+  MLC_PREPROCESSED_DATASET_NUSCENES_PATH: Preprocessed Nuscenes dataset path
+  MLC_PREPROCESSED_DATASET_NUSCENES_ACC_CHECKER_MIN_FILES_PATH: Path containing minimum files for accuracy checker
+variations:
+  validation:
+    default: true
+    group: dataset-type
+    env:
+      MLC_DATASET_NUSCENES_EXTRACTED_FOLDER_NAME: val_3d
+      MLC_DATASET_NUSCENES_TAR_FILENAME: val_3d.tar.gz
+      MLC_DOWNLOAD_URL: mlc-nuscenes:nuscenes_dataset/preprocessed/<<<MLC_DATASET_NUSCENES_TAR_FILENAME>>>
+  calibration:
+    group: dataset-type
+    env:
+      MLC_DATASET_NUSCENES_EXTRACTED_FOLDER_NAME: calib_3d
+      MLC_DATASET_NUSCENES_TAR_FILENAME: calib_3d.tar.gz
+      MLC_DOWNLOAD_URL: mlc-nuscenes:nuscenes_dataset/preprocessed/<<<MLC_DATASET_NUSCENES_TAR_FILENAME>>>
+  prebuilt:
+    default: true
+    group: dataset-src
+    env:
+      MLC_NUSCENES_DATASET_TYPE: prebuilt
+      MLC_DOWNLOAD_FINAL_ENV_NAME: MLC_PREPROCESSED_DATASET_NUSCENES_PATH
+      MLC_EXTRACT_FINAL_ENV_NAME: MLC_PREPROCESSED_DATASET_NUSCENES_PATH
+      MLC_DOWNLOAD_EXTRA_OPTIONS: ' --include '
+  mlc:
+    group: download-src
+    default: true
+    prehook_deps:
+      - tags: get,rclone
+        enable_if_env:
+          MLC_TMP_REQUIRE_DOWNLOAD:
+          - yes
+      - tags: get,rclone-config,_config-name.mlc-nuscenes
+        force_cache: true
+        enable_if_env:
+          MLC_TMP_REQUIRE_DOWNLOAD:
+          - yes
+        env:
+          MLC_RCLONE_DRIVE_FOLDER_ID: 17CpM5eU8tjrxh_LpH_BTNTeT37PhzcnC
+      - enable_if_env:
+          MLC_TMP_REQUIRE_DOWNLOAD:
+          - 'yes'
+        extra_cache_tags: nuscenes,dataset
+        force_cache: true
+        names:
+          - dae
+        tags: download-and-extract
+        force_env_keys:
+          - MLC_OUTDIRNAME  
+        update_tags_from_env_with_prefix:
+          _url.:
+            - MLC_DOWNLOAD_URL
+    env:
+      MLC_DOWNLOAD_SRC: mlcommons
+  mlc,validation:
+    env:
+      MLC_DATASET_NUSCENES_SCENE_PICKLE_FILENAME: scene_lengths.pkl
+      MLC_DATASET_NUSCENES_ACC_CHECKER_DEP_FILES_TAR_NAME: nuscenes_min.tar.gz
+      MLC_DATASET_NUSCENES_ACC_REQ_FILE_EXTRACTED_FOLDER_NAME: nuscenes
+    prehook_deps:
+      - enable_if_env:
+          MLC_TMP_REQUIRE_DOWNLOAD:
+          - 'yes'
+        extra_cache_tags: nuscenes,dataset,scene_lengths
+        force_cache: true
+        names:
+          - dae_sl
+        tags: download-and-extract
+        force_env_keys:
+          - MLC_OUTDIRNAME  
+        env:
+          MLC_DOWNLOAD_FINAL_ENV_NAME: MLC_PREPROCESSED_DATASET_NUSCENES_SCENE_LENGTHS_PATH
+          MLC_EXTRACT_FINAL_ENV_NAME: MLC_PREPROCESSED_DATASET_NUSCENES_SCENE_LENGTHS_PATH
+          MLC_DOWNLOAD_URL: mlc-nuscenes:nuscenes_dataset/scene_lengths.pkl
+        update_tags_from_env_with_prefix:
+          _url.:
+            - MLC_DOWNLOAD_URL
+      - enable_if_env:
+          MLC_TMP_REQUIRE_DOWNLOAD:
+          - 'yes'
+        extra_cache_tags: nuscenes,dataset,accuracy_checker
+        force_cache: true
+        names:
+          - dae_ac
+        tags: download-and-extract
+        force_env_keys:
+          - MLC_OUTDIRNAME  
+        env:
+          MLC_DOWNLOAD_FINAL_ENV_NAME: MLC_PREPROCESSED_DATASET_NUSCENES_ACC_CHECKER_MIN_FILES_PATH
+          MLC_EXTRACT_FINAL_ENV_NAME: MLC_PREPROCESSED_DATASET_NUSCENES_ACC_CHECKER_MIN_FILES_PATH
+          MLC_DOWNLOAD_URL: mlc-nuscenes:nuscenes_dataset/nuscenes_min.tar.gz
+        update_tags_from_env_with_prefix:
+          _url.:
+            - MLC_DOWNLOAD_URL
+  rclone:
+    group: download-tool
+    add_deps_recursive:
+      dae:
+        tags: _rclone
+      dae_sl:
+        tags: _rclone
+      dae_ac:
+        tags: _rclone
+    default: true
+  dry-run:
+    group: run-mode
+    env:
+      MLC_DOWNLOAD_MODE: dry
+  dry-run,rclone:
+    env:
+      MLC_DOWNLOAD_EXTRA_OPTIONS: --dry-run
+tests:
+  run_inputs:
+  - variations_list:
+      - validation,prebuilt,rclone,mlc,dry-run
+      - calibration,prebuilt,rclone,mlc,dry-run
\ No newline at end of file
diff --git a/script/get-preprocessed-dataset-nuscenes/run.sh b/script/get-preprocessed-dataset-nuscenes/run.sh
new file mode 100644
index 000000000..16337c44d
--- /dev/null
+++ b/script/get-preprocessed-dataset-nuscenes/run.sh
@@ -0,0 +1,13 @@
+#!/bin/bash
+
+if [[ "$MLC_DOWNLOAD_MODE" != "dry" && "$MLC_TMP_REQUIRE_DOWNLOAD" = "yes" ]]; then
+  cd "${MLC_PREPROCESSED_DATASET_NUSCENES_PATH}" || exit
+  for f in *.tar.gz; do 
+    tar -xzvf "$f" || { echo "Failed to extract $f"; exit 1; }
+  done
+  cd "${MLC_PREPROCESSED_DATASET_NUSCENES_ACC_CHECKER_MIN_FILES_PATH}" || exit
+  for f in *.tar.gz; do 
+    tar -xzvf "$f" || { echo "Failed to extract $f"; exit 1; }
+  done
+  cd - || exit
+fi
\ No newline at end of file
diff --git a/script/install-gcc-src/customize.py b/script/install-gcc-src/customize.py
index dba1f0d56..7edf5103b 100644
--- a/script/install-gcc-src/customize.py
+++ b/script/install-gcc-src/customize.py
@@ -17,16 +17,6 @@ def preprocess(i):
 
     recursion_spaces = i['recursion_spaces']
 
-    need_version = env.get('MLC_VERSION', '')
-    if need_version == '':
-        return {'return': 1,
-                'error': 'internal problem - MLC_VERSION is not defined in env'}
-
-    logger.info(f"{recursion_spaces}    # Requested version: {need_version}")
-
-    if 'MLC_GIT_CHECKOUT' not in env:
-        env['MLC_GIT_CHECKOUT'] = 'releases/gcc-' + need_version
-
     env['MLC_GCC_INSTALLED_PATH'] = os.path.join(os.getcwd(), 'install', 'bin')
 
     return {'return': 0}
diff --git a/script/install-gcc-src/meta.yaml b/script/install-gcc-src/meta.yaml
index c463860ed..741ab39b6 100644
--- a/script/install-gcc-src/meta.yaml
+++ b/script/install-gcc-src/meta.yaml
@@ -3,9 +3,27 @@ automation_alias: script
 automation_uid: 5b4e0237da074764
 cache: true
 category: Compiler automation
-default_version: '12'
 deps:
 - tags: detect,os
+- tags: detect,cpu
+- tags: get,generic-sys-util,_flex
+- env:
+    MLC_GIT_CHECKOUT_PATH_ENV_NAME: MLC_GCC_SRC_REPO_PATH
+  extra_cache_tags: gcc,src,gcc-src,gcc-src-repo
+  force_env_keys:
+  - MLC_GIT_*
+  names:
+  - gcc-src-repo
+  tags: get,git,repo
+  update_tags_from_env_with_prefix:
+    _branch.:
+    - MLC_GIT_CHECKOUT
+    _repo.:
+    - MLC_GIT_URL
+    _sha.:
+    - MLC_GIT_CHECKOUT_SHA
+    _tag.:
+    - MLC_GIT_CHECKOUT_TAG
 env:
   MLC_GIT_URL: git://gcc.gnu.org/git/gcc.git
 post_deps:
@@ -19,7 +37,24 @@ tags:
 - gcc
 - src-gcc
 uid: faae0ebd6e1242db
-versions:
+tests:
+  run_inputs:
+    - {}
+variations:
   master:
+    group: version
+    default: true
     env:
       MLC_GIT_CHECKOUT: master
+  version.#:
+    group: version
+    env:
+      MLC_GIT_CHECKOUT: releases/gcc-#
+  branch.#:
+    group: version
+    env:
+      MLC_GIT_CHECKOUT: '#'
+  lang.#:
+    env:
+      +MLC_GCC_ENABLED_LANGUAGES:
+        - '#'
diff --git a/script/install-gcc-src/run.sh b/script/install-gcc-src/run.sh
index c3631255d..c8b1ca291 100644
--- a/script/install-gcc-src/run.sh
+++ b/script/install-gcc-src/run.sh
@@ -4,12 +4,14 @@ CUR_DIR=$PWD
 
 echo "******************************************************"
 
+echo ${MLC_GCC_SRC_REPO_PATH}
+
 if [ ! -d "src" ]; then
-  echo "Cloning GCC from ${MLC_GIT_URL} with branch ${MLC_GIT_CHECKOUT}..."
-  git clone -b "${MLC_GIT_CHECKOUT}" ${MLC_GIT_URL} src
-  if [ "${?}" != "0" ]; then exit 1; fi
+  cp -r ${MLC_GCC_SRC_REPO_PATH} src
+  test $? -eq 0 || exit $?
 fi
 
+
 mkdir -p install
 mkdir -p build
 
@@ -22,16 +24,17 @@ cd ../build
 
 ../src/configure --prefix="${INSTALL_DIR}" --with-gcc-major-version-only --disable-multilib
 
-if [ "${?}" != "0" ]; then exit 1; fi
+test $? -eq 0 || exit $?
 
 echo "******************************************************"
 MLC_MAKE_CORES=${MLC_MAKE_CORES:-${MLC_HOST_CPU_TOTAL_CORES}}
 MLC_MAKE_CORES=${MLC_MAKE_CORES:-2}
 
 make -j${MLC_MAKE_CORES}
-if [ "${?}" != "0" ]; then exit 1; fi
+test $? -eq 0 || exit $?
+
 make install
-if [ "${?}" != "0" ]; then exit 1; fi
+test $? -eq 0 || exit $?
 
 # Clean build directory (too large)
 cd ${CUR_DIR}
diff --git a/script/preprocess-mlperf-inference-submission/meta.yaml b/script/preprocess-mlperf-inference-submission/meta.yaml
index 5381b36dd..0ddc10d51 100644
--- a/script/preprocess-mlperf-inference-submission/meta.yaml
+++ b/script/preprocess-mlperf-inference-submission/meta.yaml
@@ -9,17 +9,26 @@ deps:
   - python
   - python3
   tags: get,python3
-- names:
-  - inference-src
-  - submission-checker-src
-  tags: get,mlcommons,inference,src,_branch.dev
-  version: custom
 - names:
   - get-mlperf-submission-dir
   skip_if_env:
     MLC_MLPERF_INFERENCE_SUBMISSION_DIR:
     - 'on'
   tags: get,mlperf,submission,dir
+variations:
+  inference:
+    default: true
+    deps:
+      - names:
+        - inference-src
+        - submission-checker-src
+        tags: mlcommons,inference,src,_branch.dev
+        version: custom
+  automotive:
+    deps:
+      - names:
+        - automotive-src
+        tags: mlcommons,automotive,src
 input_mapping:
   input: MLC_MLPERF_INFERENCE_SUBMISSION_DIR
   submission_dir: MLC_MLPERF_INFERENCE_SUBMISSION_DIR
diff --git a/script/process-mlperf-accuracy/customize.py b/script/process-mlperf-accuracy/customize.py
index 4ef3fbd43..8a2168956 100644
--- a/script/process-mlperf-accuracy/customize.py
+++ b/script/process-mlperf-accuracy/customize.py
@@ -1,271 +1,283 @@
-from mlc import utils
-import os
-
-
-def preprocess(i):
-
-    os_info = i['os_info']
-
-    xsep = ';' if os_info['platform'] == 'windows' else ':'
-
-    env = i['env']
-    logger = i['automation'].logger
-
-    results_dir = env.get("MLC_MLPERF_ACCURACY_RESULTS_DIR", "")
-
-    if results_dir == "":
-        logger.error("Please set MLC_MLPERF_ACCURACY_RESULTS_DIR")
-        return {'return': -1}
-
-    # In fact, we expect only 1 command line here
-    run_cmds = []
-
-    if env.get('MLC_MAX_EXAMPLES', '') != '' and env.get(
-            'MLC_MLPERF_RUN_STYLE', '') != 'valid':
-        max_examples_string = " --max_examples " + env['MLC_MAX_EXAMPLES']
-    else:
-        max_examples_string = ""
-
-    results_dir_split = results_dir.split(xsep)
-    dataset = env['MLC_DATASET']
-    regenerate_accuracy_file = env.get(
-        'MLC_MLPERF_REGENERATE_ACCURACY_FILE', env.get(
-            'MLC_RERUN', False))
-
-    for result_dir in results_dir_split:
-
-        out_file = os.path.join(result_dir, 'accuracy.txt')
-
-        if os.path.exists(out_file) and (
-                os.stat(out_file).st_size != 0) and not regenerate_accuracy_file:
-            continue
-
-        if dataset == "openimages":
-            if env.get('MLC_DATASET_PATH_ROOT', '') != '':
-                dataset_dir = env['MLC_DATASET_PATH_ROOT']
-                if 'DATASET_ANNOTATIONS_FILE_PATH' in env:
-                    del (env['DATASET_ANNOTATIONS_FILE_PATH'])
-            else:
-                env['DATASET_ANNOTATIONS_FILE_PATH'] = env['MLC_DATASET_ANNOTATIONS_FILE_PATH']
-                dataset_dir = os.getcwd()  # not used, just to keep the script happy
-            CMD = env['MLC_PYTHON_BIN_WITH_PATH'] + " " + "'" + os.path.join(env['MLC_MLPERF_INFERENCE_CLASSIFICATION_AND_DETECTION_PATH'], "tools",
-                                                                             "accuracy-openimages.py") + "'" + " --mlperf-accuracy-file " + "'" + os.path.join(result_dir,
-                                                                                                                                                               "mlperf_log_accuracy.json") + "'" + " --openimages-dir " + "'" + dataset_dir + "'" + " --verbose > " + "'" + \
-                out_file + "'"
-
-        elif dataset == "imagenet":
-            CMD = env['MLC_PYTHON_BIN_WITH_PATH'] + " '" + os.path.join(env['MLC_MLPERF_INFERENCE_CLASSIFICATION_AND_DETECTION_PATH'], "tools",
-                                                                        "accuracy-imagenet.py") + "' --mlperf-accuracy-file '" + os.path.join(result_dir,
-                                                                                                                                              "mlperf_log_accuracy.json") + "' --imagenet-val-file '" + os.path.join(env['MLC_DATASET_AUX_PATH'],
-                                                                                                                                                                                                                     "val.txt") + "' --dtype " + env.get('MLC_ACCURACY_DTYPE', "float32") + " > '" + out_file + "'"
-
-        elif dataset == "squad":
-            CMD = env['MLC_PYTHON_BIN_WITH_PATH'] + " '" + os.path.join(env['MLC_MLPERF_INFERENCE_BERT_PATH'],
-                                                                        "accuracy-squad.py") + "' --val_data '" + env['MLC_DATASET_SQUAD_VAL_PATH'] + \
-                "' --log_file '" + os.path.join(result_dir, "mlperf_log_accuracy.json") + \
-                "' --vocab_file '" + env['MLC_ML_MODEL_BERT_VOCAB_FILE_WITH_PATH'] + \
-                "' --out_file '" + os.path.join(result_dir, 'predictions.json') + \
-                "' --features_cache_file '" + os.path.join(env['MLC_MLPERF_INFERENCE_BERT_PATH'], 'eval_features.pickle') + \
-                "' --output_dtype " + env['MLC_ACCURACY_DTYPE'] + env.get(
-                'MLC_OUTPUT_TRANSPOSED', '') + max_examples_string + " > '" + out_file + "'"
-
-        elif dataset == "cnndm":
-            if env.get('MLC_MLPERF_IMPLEMENTATION', '') == 'intel':
-                accuracy_checker_file = env['MLC_MLPERF_INFERENCE_INTEL_GPTJ_ACCURACY_FILE_WITH_PATH']
-                env['+PYTHONPATH'] = [os.path.dirname(env['MLC_MLPERF_INFERENCE_INTEL_GPTJ_DATASET_FILE_WITH_PATH'])] + [
-                    os.path.dirname(env['MLC_MLPERF_INFERENCE_INTEL_GPTJ_DATASET_ITEM_FILE_WITH_PATH'])] + env['+PYTHONPATH']
-                suffix_string = " --model-name-or-path '" + \
-                    env['GPTJ_CHECKPOINT_PATH'] + "'"
-            else:
-                accuracy_checker_file = os.path.join(env['MLC_MLPERF_INFERENCE_SOURCE'], "language", "gpt-j",
-                                                     "evaluation.py")
-                suffix_string = " --dtype " + \
-                    env.get('MLC_ACCURACY_DTYPE', "float32")
-            CMD = env['MLC_PYTHON_BIN_WITH_PATH'] + " '" + accuracy_checker_file + "' --mlperf-accuracy-file '" + os.path.join(result_dir, "mlperf_log_accuracy.json") + \
-                "' --dataset-file '" + \
-                env['MLC_DATASET_EVAL_PATH'] + "'" + \
-                suffix_string + " > '" + out_file + "'"
-
-        elif dataset == "openorca":
-            accuracy_checker_file = os.path.join(env['MLC_MLPERF_INFERENCE_SOURCE'], "language", "llama2-70b",
-                                                 "evaluate-accuracy.py")
-            if env.get('MLC_VLLM_SERVER_MODEL_NAME', '') == '':
-                checkpoint_path = env['MLC_ML_MODEL_LLAMA2_FILE_WITH_PATH']
-            else:
-                checkpoint_path = env['MLC_VLLM_SERVER_MODEL_NAME']
-            CMD = env['MLC_PYTHON_BIN_WITH_PATH'] + " '" + accuracy_checker_file + "' --checkpoint-path '" + checkpoint_path + "' --mlperf-accuracy-file '" + os.path.join(result_dir, "mlperf_log_accuracy.json") + \
-                "' --dataset-file '" + env['MLC_DATASET_PREPROCESSED_PATH'] + "'" + " --dtype " + env.get(
-                    'MLC_ACCURACY_DTYPE', "int32") + " > '" + out_file + "'"
-
-        elif dataset == "openorca-gsm8k-mbxp-combined":
-            accuracy_checker_file = os.path.join(env['MLC_MLPERF_INFERENCE_SOURCE'], "language", "mixtral-8x7b",
-                                                 "evaluate-accuracy.py")
-            CMD = env['MLC_PYTHON_BIN_WITH_PATH'] + " '" + accuracy_checker_file + "' --checkpoint-path '" + env['MIXTRAL_CHECKPOINT_PATH'] + "' --mlperf-accuracy-file '" + os.path.join(result_dir, "mlperf_log_accuracy.json") + \
-                "' --dataset-file '" + env['MLC_DATASET_MIXTRAL_PREPROCESSED_PATH'] + "'" + \
-                " --dtype " + env.get('MLC_ACCURACY_DTYPE',
-                                      "float32") + " > '" + out_file + "'"
-
-        elif dataset == "coco2014":
-            env['+PYTHONPATH'] = [
-                os.path.join(
-                    env['MLC_MLPERF_INFERENCE_SOURCE'],
-                    "text_to_image",
-                    "tools"),
-                os.path.join(
-                    env['MLC_MLPERF_INFERENCE_SOURCE'],
-                    "text_to_image",
-                    "tools",
-                    "fid")]
-            extra_options = ""
-
-            if env.get('MLC_SDXL_STATISTICS_FILE_PATH', '') != '':
-                extra_options += (
-                    f""" --statistics-path '{
-                        env['MLC_SDXL_STATISTICS_FILE_PATH']}'"""
-                )
-
-            if env.get('MLC_SDXL_COMPLIANCE_IMAGES_PATH', '') != '':
-                extra_options += (
-                    f""" --compliance-images-path '{
-                        env['MLC_SDXL_COMPLIANCE_IMAGES_PATH']}' """
-                )
-            else:
-                extra_options += f""" --compliance-images-path '{
-                    os.path.join(
-                        result_dir, "images")}' """
-
-            if env.get('MLC_COCO2014_SAMPLE_ID_PATH', '') != '':
-                extra_options += (
-                    f" --ids-path '{env['MLC_COCO2014_SAMPLE_ID_PATH']}' "
-                )
-
-            if env.get('MLC_SDXL_ACCURACY_RUN_DEVICE', '') != '':
-                extra_options += (
-                    f" --device '{env['MLC_SDXL_ACCURACY_RUN_DEVICE']}' "
-                )
-
-            # env['DATASET_ANNOTATIONS_FILE_PATH'] = env['MLC_DATASET_ANNOTATIONS_FILE_PATH']
-            CMD = env['MLC_PYTHON_BIN_WITH_PATH'] + " '" + os.path.join(env['MLC_MLPERF_INFERENCE_SOURCE'], "text_to_image", "tools",
-                                                                        "accuracy_coco.py") + "' --mlperf-accuracy-file '" + os.path.join(result_dir, "mlperf_log_accuracy.json") + \
-                "' --caption-path '" + os.path.join(
-                env['MLC_MLPERF_INFERENCE_SOURCE'],
-                "text_to_image",
-                "coco2014",
-                "captions",
-                "captions_source.tsv") + "'" + extra_options + " > '" + out_file + "'"
-
-        elif dataset == "kits19":
-            CMD = env['MLC_PYTHON_BIN_WITH_PATH'] + " '" + os.path.join(env['MLC_MLPERF_INFERENCE_3DUNET_PATH'],
-                                                                        "accuracy_kits.py") + \
-                "' --preprocessed_data_dir '" + env['MLC_DATASET_PREPROCESSED_PATH'] +\
-                "' --postprocessed_data_dir '" + result_dir +\
-                "' --log_file '" + os.path.join(result_dir, "mlperf_log_accuracy.json") + \
-                "' --output_dtype " + \
-                env['MLC_ACCURACY_DTYPE'] + " > '" + out_file + "'"
-
-        elif dataset == "librispeech":
-            CMD = env['MLC_PYTHON_BIN_WITH_PATH'] + " '" + os.path.join(env['MLC_MLPERF_INFERENCE_RNNT_PATH'],
-                                                                        "accuracy_eval.py") + \
-                "' --dataset_dir '" + os.path.join(env['MLC_DATASET_PREPROCESSED_PATH'], "..") +\
-                "' --manifest '" + env['MLC_DATASET_PREPROCESSED_JSON'] +\
-                "' --log_dir '" + result_dir + \
-                "' --output_dtype " + \
-                env['MLC_ACCURACY_DTYPE'] + " > '" + out_file + "'"
-
-        elif dataset == "terabyte":
-            extra_options = ""
-            if env.get('MLC_DLRM_V2_AGGREGATION_TRACE_FILE_PATH', '') != '':
-                extra_options += (
-                    f""" --aggregation-trace-file '{
-                        env['MLC_DLRM_V2_AGGREGATION_TRACE_FILE_PATH']}' """
-                )
-            if env.get('MLC_DLRM_V2_DAY23_FILE_PATH', '') != '':
-                extra_options += (
-                    f""" --day-23-file '{
-                        env['MLC_DLRM_V2_DAY23_FILE_PATH']}' """
-                )
-            CMD = env['MLC_PYTHON_BIN_WITH_PATH'] + " '" + os.path.join(env['MLC_MLPERF_INFERENCE_DLRM_V2_PATH'], "pytorch", "tools",
-                                                                        "accuracy-dlrm.py") + "' --mlperf-accuracy-file '" + os.path.join(result_dir,
-                                                                                                                                          "mlperf_log_accuracy.json") + "'" + extra_options + \
-                " --dtype " + env.get('MLC_ACCURACY_DTYPE',
-                                      "float32") + " > '" + out_file + "'"
-
-        elif dataset == "igbh":
-            if env.get('MLC_DATASET_IGBH_SIZE', '') == '':
-                if env.get('MLC_MLPERF_SUBMISSION_GENERATION_STYLE',
-                           '') == "full":
-                    env['MLC_DATASET_IGBH_SIZE'] = "full"
-                else:
-                    env['MLC_DATASET_IGBH_SIZE'] = "tiny"
-            CMD = env['MLC_PYTHON_BIN_WITH_PATH'] + " '" + os.path.join(env['MLC_MLPERF_INFERENCE_SOURCE'], "graph", "R-GAT", "tools", "accuracy_igbh.py") + "' --mlperf-accuracy-file '" + os.path.join(
-                result_dir, "mlperf_log_accuracy.json") + "' --dataset-path '" + env['MLC_DATASET_IGBH_PATH'] + "' --dataset-size '" + env['MLC_DATASET_IGBH_SIZE'] + "' --output-file '" + out_file + "'"
-
-        elif dataset == "dataset_llama3":
-            CMD = env['MLC_PYTHON_BIN_WITH_PATH'] + " '" + os.path.join(env['MLC_MLPERF_INFERENCE_SOURCE'], "language", "llama3.1-405b", "evaluate-accuracy.py") + "' --checkpoint-path '" + env['MLC_ML_MODEL_LLAMA3_CHECKPOINT_PATH'] + "' --mlperf-accuracy-file '" + os.path.join(
-                result_dir, "mlperf_log_accuracy.json") + "' --dtype '" + env['MLC_ACCURACY_DTYPE'] + "' --dataset-file '" + env['MLC_DATASET_LLAMA3_PATH'] + "' > '" + out_file + "'"
-
-        elif dataset == "waymo":
-            CMD = env['MLC_PYTHON_BIN_WITH_PATH'] + " '" + os.path.join(env['MLC_MLPERF_INFERENCE_SOURCE'], "automotive", "3d-object-detection", "accuracy_waymo.py") + "' --mlperf-accuracy-file '" + os.path.join(
-                result_dir, "mlperf_log_accuracy.json") + "' --waymo-dir '" + env['MLC_DATASET_WAYMO_PATH'] + "' > '" + out_file + "'"
-
-        else:
-            return {'return': 1, 'error': 'Unsupported dataset'}
-
-        run_cmds.append(CMD)
-
-    if os_info['platform'] == 'windows':
-        env['MLC_RUN_CMDS'] = (
-            '\n'.join(run_cmds)).replace(
-            "'",
-            '"').replace(
-            '>',
-            '^>')
-    else:
-        env['MLC_RUN_CMDS'] = "??".join(run_cmds)
-
-    return {'return': 0}
-
-
-def postprocess(i):
-
-    os_info = i['os_info']
-    env = i['env']
-    state = i['state']
-    logger = i['automation'].logger
-    xsep = ';' if os_info['platform'] == 'windows' else ':'
-
-    results_dir = env.get("MLC_MLPERF_ACCURACY_RESULTS_DIR", "")
-
-    results_dir_split = results_dir.split(xsep)
-
-    for result_dir in results_dir_split:
-        accuracy_file = os.path.join(result_dir, "accuracy.txt")
-
-        if os.path.exists(accuracy_file):
-            logger.info('')
-            logger.info('Accuracy file: {}'.format(accuracy_file))
-            logger.info('')
-
-            x = ''
-            with open(accuracy_file, "r") as fp:
-                x = fp.read()
-
-            if x != '':
-                logger.info(f"{x}")
-
-                # Trying to extract accuracy dict
-                for y in x.split('\n'):
-                    if y.startswith('{') and y.endswith('}'):
-
-                        import json
-
-                        try:
-                            z = json.loads(y)
-                            state['app_mlperf_inference_accuracy'] = z
-
-                            break
-                        except ValueError as e:
-                            pass
-
-            logger.info('')
-    return {'return': 0}
+from mlc import utils
+import os
+
+
+def preprocess(i):
+
+    os_info = i['os_info']
+
+    xsep = ';' if os_info['platform'] == 'windows' else ':'
+
+    env = i['env']
+    logger = i['automation'].logger
+
+    results_dir = env.get("MLC_MLPERF_ACCURACY_RESULTS_DIR", "")
+
+    if results_dir == "":
+        logger.error("Please set MLC_MLPERF_ACCURACY_RESULTS_DIR")
+        return {'return': -1}
+
+    # In fact, we expect only 1 command line here
+    run_cmds = []
+
+    if env.get('MLC_MAX_EXAMPLES', '') != '' and env.get(
+            'MLC_MLPERF_RUN_STYLE', '') != 'valid':
+        max_examples_string = " --max_examples " + env['MLC_MAX_EXAMPLES']
+    else:
+        max_examples_string = ""
+
+    results_dir_split = results_dir.split(xsep)
+    dataset = env['MLC_DATASET']
+    regenerate_accuracy_file = env.get(
+        'MLC_MLPERF_REGENERATE_ACCURACY_FILE', env.get(
+            'MLC_RERUN', False))
+
+    for result_dir in results_dir_split:
+
+        out_file = os.path.join(result_dir, 'accuracy.txt')
+
+        if os.path.exists(out_file) and (
+                os.stat(out_file).st_size != 0) and not regenerate_accuracy_file:
+            continue
+
+        if dataset == "openimages":
+            if env.get('MLC_DATASET_PATH_ROOT', '') != '':
+                dataset_dir = env['MLC_DATASET_PATH_ROOT']
+                if 'DATASET_ANNOTATIONS_FILE_PATH' in env:
+                    del (env['DATASET_ANNOTATIONS_FILE_PATH'])
+            else:
+                env['DATASET_ANNOTATIONS_FILE_PATH'] = env['MLC_DATASET_ANNOTATIONS_FILE_PATH']
+                dataset_dir = os.getcwd()  # not used, just to keep the script happy
+            CMD = env['MLC_PYTHON_BIN_WITH_PATH'] + " " + "'" + os.path.join(env['MLC_MLPERF_INFERENCE_CLASSIFICATION_AND_DETECTION_PATH'], "tools",
+                                                                             "accuracy-openimages.py") + "'" + " --mlperf-accuracy-file " + "'" + os.path.join(result_dir,
+                                                                                                                                                               "mlperf_log_accuracy.json") + "'" + " --openimages-dir " + "'" + dataset_dir + "'" + " --verbose > " + "'" + \
+                out_file + "'"
+
+        elif dataset == "imagenet":
+            CMD = env['MLC_PYTHON_BIN_WITH_PATH'] + " '" + os.path.join(env['MLC_MLPERF_INFERENCE_CLASSIFICATION_AND_DETECTION_PATH'], "tools",
+                                                                        "accuracy-imagenet.py") + "' --mlperf-accuracy-file '" + os.path.join(result_dir,
+                                                                                                                                              "mlperf_log_accuracy.json") + "' --imagenet-val-file '" + os.path.join(env['MLC_DATASET_AUX_PATH'],
+                                                                                                                                                                                                                     "val.txt") + "' --dtype " + env.get('MLC_ACCURACY_DTYPE', "float32") + " > '" + out_file + "'"
+
+        elif dataset == "squad":
+            CMD = env['MLC_PYTHON_BIN_WITH_PATH'] + " '" + os.path.join(env['MLC_MLPERF_INFERENCE_BERT_PATH'],
+                                                                        "accuracy-squad.py") + "' --val_data '" + env['MLC_DATASET_SQUAD_VAL_PATH'] + \
+                "' --log_file '" + os.path.join(result_dir, "mlperf_log_accuracy.json") + \
+                "' --vocab_file '" + env['MLC_ML_MODEL_BERT_VOCAB_FILE_WITH_PATH'] + \
+                "' --out_file '" + os.path.join(result_dir, 'predictions.json') + \
+                "' --features_cache_file '" + os.path.join(env['MLC_MLPERF_INFERENCE_BERT_PATH'], 'eval_features.pickle') + \
+                "' --output_dtype " + env['MLC_ACCURACY_DTYPE'] + env.get(
+                'MLC_OUTPUT_TRANSPOSED', '') + max_examples_string + " > '" + out_file + "'"
+
+        elif dataset == "cnndm":
+            if env.get('MLC_MLPERF_IMPLEMENTATION', '') == 'intel':
+                accuracy_checker_file = env['MLC_MLPERF_INFERENCE_INTEL_GPTJ_ACCURACY_FILE_WITH_PATH']
+                env['+PYTHONPATH'] = [os.path.dirname(env['MLC_MLPERF_INFERENCE_INTEL_GPTJ_DATASET_FILE_WITH_PATH'])] + [
+                    os.path.dirname(env['MLC_MLPERF_INFERENCE_INTEL_GPTJ_DATASET_ITEM_FILE_WITH_PATH'])] + env['+PYTHONPATH']
+                suffix_string = " --model-name-or-path '" + \
+                    env['GPTJ_CHECKPOINT_PATH'] + "'"
+            else:
+                accuracy_checker_file = os.path.join(env['MLC_MLPERF_INFERENCE_SOURCE'], "language", "gpt-j",
+                                                     "evaluation.py")
+                suffix_string = " --dtype " + \
+                    env.get('MLC_ACCURACY_DTYPE', "float32")
+            CMD = env['MLC_PYTHON_BIN_WITH_PATH'] + " '" + accuracy_checker_file + "' --mlperf-accuracy-file '" + os.path.join(result_dir, "mlperf_log_accuracy.json") + \
+                "' --dataset-file '" + \
+                env['MLC_DATASET_EVAL_PATH'] + "'" + \
+                suffix_string + " > '" + out_file + "'"
+
+        elif dataset == "openorca":
+            accuracy_checker_file = os.path.join(env['MLC_MLPERF_INFERENCE_SOURCE'], "language", "llama2-70b",
+                                                 "evaluate-accuracy.py")
+            if env.get('MLC_VLLM_SERVER_MODEL_NAME', '') == '':
+                checkpoint_path = env['MLC_ML_MODEL_LLAMA2_FILE_WITH_PATH']
+            else:
+                checkpoint_path = env['MLC_VLLM_SERVER_MODEL_NAME']
+            CMD = env['MLC_PYTHON_BIN_WITH_PATH'] + " '" + accuracy_checker_file + "' --checkpoint-path '" + checkpoint_path + "' --mlperf-accuracy-file '" + os.path.join(result_dir, "mlperf_log_accuracy.json") + \
+                "' --dataset-file '" + env['MLC_DATASET_PREPROCESSED_PATH'] + "'" + " --dtype " + env.get(
+                    'MLC_ACCURACY_DTYPE', "int32") + " > '" + out_file + "'"
+
+        elif dataset == "openorca-gsm8k-mbxp-combined":
+            accuracy_checker_file = os.path.join(env['MLC_MLPERF_INFERENCE_SOURCE'], "language", "mixtral-8x7b",
+                                                 "evaluate-accuracy.py")
+            CMD = env['MLC_PYTHON_BIN_WITH_PATH'] + " '" + accuracy_checker_file + "' --checkpoint-path '" + env['MIXTRAL_CHECKPOINT_PATH'] + "' --mlperf-accuracy-file '" + os.path.join(result_dir, "mlperf_log_accuracy.json") + \
+                "' --dataset-file '" + env['MLC_DATASET_MIXTRAL_PREPROCESSED_PATH'] + "'" + \
+                " --dtype " + env.get('MLC_ACCURACY_DTYPE',
+                                      "float32") + " > '" + out_file + "'"
+
+        elif dataset == "coco2014":
+            env['+PYTHONPATH'] = [
+                os.path.join(
+                    env['MLC_MLPERF_INFERENCE_SOURCE'],
+                    "text_to_image",
+                    "tools"),
+                os.path.join(
+                    env['MLC_MLPERF_INFERENCE_SOURCE'],
+                    "text_to_image",
+                    "tools",
+                    "fid")]
+            extra_options = ""
+
+            if env.get('MLC_SDXL_STATISTICS_FILE_PATH', '') != '':
+                extra_options += (
+                    f""" --statistics-path '{
+                        env['MLC_SDXL_STATISTICS_FILE_PATH']}'"""
+                )
+
+            if env.get('MLC_SDXL_COMPLIANCE_IMAGES_PATH', '') != '':
+                extra_options += (
+                    f""" --compliance-images-path '{
+                        env['MLC_SDXL_COMPLIANCE_IMAGES_PATH']}' """
+                )
+            else:
+                extra_options += f""" --compliance-images-path '{
+                    os.path.join(
+                        result_dir, "images")}' """
+
+            if env.get('MLC_COCO2014_SAMPLE_ID_PATH', '') != '':
+                extra_options += (
+                    f" --ids-path '{env['MLC_COCO2014_SAMPLE_ID_PATH']}' "
+                )
+
+            if env.get('MLC_SDXL_ACCURACY_RUN_DEVICE', '') != '':
+                extra_options += (
+                    f" --device '{env['MLC_SDXL_ACCURACY_RUN_DEVICE']}' "
+                )
+
+            # env['DATASET_ANNOTATIONS_FILE_PATH'] = env['MLC_DATASET_ANNOTATIONS_FILE_PATH']
+            CMD = env['MLC_PYTHON_BIN_WITH_PATH'] + " '" + os.path.join(env['MLC_MLPERF_INFERENCE_SOURCE'], "text_to_image", "tools",
+                                                                        "accuracy_coco.py") + "' --mlperf-accuracy-file '" + os.path.join(result_dir, "mlperf_log_accuracy.json") + \
+                "' --caption-path '" + os.path.join(
+                env['MLC_MLPERF_INFERENCE_SOURCE'],
+                "text_to_image",
+                "coco2014",
+                "captions",
+                "captions_source.tsv") + "'" + extra_options + " > '" + out_file + "'"
+
+        elif dataset == "kits19":
+            CMD = env['MLC_PYTHON_BIN_WITH_PATH'] + " '" + os.path.join(env['MLC_MLPERF_INFERENCE_3DUNET_PATH'],
+                                                                        "accuracy_kits.py") + \
+                "' --preprocessed_data_dir '" + env['MLC_DATASET_PREPROCESSED_PATH'] +\
+                "' --postprocessed_data_dir '" + result_dir +\
+                "' --log_file '" + os.path.join(result_dir, "mlperf_log_accuracy.json") + \
+                "' --output_dtype " + \
+                env['MLC_ACCURACY_DTYPE'] + " > '" + out_file + "'"
+
+        elif dataset == "librispeech":
+            CMD = env['MLC_PYTHON_BIN_WITH_PATH'] + " '" + os.path.join(env['MLC_MLPERF_INFERENCE_RNNT_PATH'],
+                                                                        "accuracy_eval.py") + \
+                "' --dataset_dir '" + os.path.join(env['MLC_DATASET_PREPROCESSED_PATH'], "..") +\
+                "' --manifest '" + env['MLC_DATASET_PREPROCESSED_JSON'] +\
+                "' --log_dir '" + result_dir + \
+                "' --output_dtype " + \
+                env['MLC_ACCURACY_DTYPE'] + " > '" + out_file + "'"
+
+        elif dataset == "terabyte":
+            extra_options = ""
+            if env.get('MLC_DLRM_V2_AGGREGATION_TRACE_FILE_PATH', '') != '':
+                extra_options += (
+                    f""" --aggregation-trace-file '{
+                        env['MLC_DLRM_V2_AGGREGATION_TRACE_FILE_PATH']}' """
+                )
+            if env.get('MLC_DLRM_V2_DAY23_FILE_PATH', '') != '':
+                extra_options += (
+                    f""" --day-23-file '{
+                        env['MLC_DLRM_V2_DAY23_FILE_PATH']}' """
+                )
+            CMD = env['MLC_PYTHON_BIN_WITH_PATH'] + " '" + os.path.join(env['MLC_MLPERF_INFERENCE_DLRM_V2_PATH'], "pytorch", "tools",
+                                                                        "accuracy-dlrm.py") + "' --mlperf-accuracy-file '" + os.path.join(result_dir,
+                                                                                                                                          "mlperf_log_accuracy.json") + "'" + extra_options + \
+                " --dtype " + env.get('MLC_ACCURACY_DTYPE',
+                                      "float32") + " > '" + out_file + "'"
+
+        elif dataset == "igbh":
+            if env.get('MLC_DATASET_IGBH_SIZE', '') == '':
+                if env.get('MLC_MLPERF_SUBMISSION_GENERATION_STYLE',
+                           '') == "full":
+                    env['MLC_DATASET_IGBH_SIZE'] = "full"
+                else:
+                    env['MLC_DATASET_IGBH_SIZE'] = "tiny"
+            CMD = env['MLC_PYTHON_BIN_WITH_PATH'] + " '" + os.path.join(env['MLC_MLPERF_INFERENCE_SOURCE'], "graph", "R-GAT", "tools", "accuracy_igbh.py") + "' --mlperf-accuracy-file '" + os.path.join(
+                result_dir, "mlperf_log_accuracy.json") + "' --dataset-path '" + env['MLC_DATASET_IGBH_PATH'] + "' --dataset-size '" + env['MLC_DATASET_IGBH_SIZE'] + "' --output-file '" + out_file + "'"
+
+        elif dataset == "dataset_llama3":
+            CMD = env['MLC_PYTHON_BIN_WITH_PATH'] + " '" + os.path.join(env['MLC_MLPERF_INFERENCE_SOURCE'], "language", "llama3.1-405b", "evaluate-accuracy.py") + "' --checkpoint-path '" + env['MLC_ML_MODEL_LLAMA3_CHECKPOINT_PATH'] + "' --mlperf-accuracy-file '" + os.path.join(
+                result_dir, "mlperf_log_accuracy.json") + "' --dtype '" + env['MLC_ACCURACY_DTYPE'] + "' --dataset-file '" + env['MLC_DATASET_LLAMA3_PATH'] + "' > '" + out_file + "'"
+
+        elif dataset == "waymo":
+            CMD = env['MLC_PYTHON_BIN_WITH_PATH'] + " '" + os.path.join(env['MLC_MLPERF_INFERENCE_SOURCE'], "automotive", "3d-object-detection", "accuracy_waymo.py") + "' --mlperf-accuracy-file '" + os.path.join(
+                result_dir, "mlperf_log_accuracy.json") + "' --waymo-dir '" + env['MLC_DATASET_WAYMO_PATH'] + "' > '" + out_file + "'"
+
+        elif dataset == "nuscenes":
+            CMD = env['MLC_PYTHON_BIN_WITH_PATH'] + " '" + os.path.join(env['MLC_MLPERF_INFERENCE_BEVFORMER_PATH'], "accuracy_nuscenes_cpu.py") + "' --mlperf-accuracy-file '" + os.path.join(
+                result_dir, "mlperf_log_accuracy.json") + "' --nuscenes-dir '" + env['MLC_PREPROCESSED_DATASET_NUSCENES_ACC_CHECKER_MIN_FILES_PATH'] + "' --config '" + os.path.join(env['MLC_MLPERF_INFERENCE_BEVFORMER_PATH'], "projects" + "configs" + "bevformer" + "bevformer_tiny.py") + "' > '" + out_file + "'"
+
+        elif dataset == "cognata_ssd":
+            CMD = env['MLC_PYTHON_BIN_WITH_PATH'] + " '" + os.path.join(env['MLC_MLPERF_INFERENCE_SSD_RESNET50_PATH'], "accuracy_cognata.py") + "' --mlperf-accuracy-file '" + os.path.join(
+                result_dir, "mlperf_log_accuracy.json") + "' --dataset-path '" + env['MLC_PREPROCESSED_DATASET_COGNATA_PATH'] + "' --config '" + "baseline_8MP_ss_scales_fm1_5x5_all" + "' > '" + out_file + "'"
+
+        elif dataset == "cognata_deeplab":
+            CMD = env['MLC_PYTHON_BIN_WITH_PATH'] + " '" + os.path.join(env['MLC_MLPERF_INFERENCE_DEEPLABV3PLUS_PATH'], "accuracy_cognata.py") + "' --mlperf-accuracy-file '" + os.path.join(
+                result_dir, "mlperf_log_accuracy.json") + "' --dataset-path '" + env['MLC_PREPROCESSED_DATASET_COGNATA_PATH'] + "' > '" + out_file + "'"
+
+        else:
+            return {'return': 1, 'error': 'Unsupported dataset'}
+
+        run_cmds.append(CMD)
+
+    if os_info['platform'] == 'windows':
+        env['MLC_RUN_CMDS'] = (
+            '\n'.join(run_cmds)).replace(
+            "'",
+            '"').replace(
+            '>',
+            '^>')
+    else:
+        env['MLC_RUN_CMDS'] = "??".join(run_cmds)
+
+    return {'return': 0}
+
+
+def postprocess(i):
+
+    os_info = i['os_info']
+    env = i['env']
+    state = i['state']
+    logger = i['automation'].logger
+    xsep = ';' if os_info['platform'] == 'windows' else ':'
+
+    results_dir = env.get("MLC_MLPERF_ACCURACY_RESULTS_DIR", "")
+
+    results_dir_split = results_dir.split(xsep)
+
+    for result_dir in results_dir_split:
+        accuracy_file = os.path.join(result_dir, "accuracy.txt")
+
+        if os.path.exists(accuracy_file):
+            logger.info('')
+            logger.info('Accuracy file: {}'.format(accuracy_file))
+            logger.info('')
+
+            x = ''
+            with open(accuracy_file, "r") as fp:
+                x = fp.read()
+
+            if x != '':
+                logger.info(f"{x}")
+
+                # Trying to extract accuracy dict
+                for y in x.split('\n'):
+                    if y.startswith('{') and y.endswith('}'):
+
+                        import json
+
+                        try:
+                            z = json.loads(y)
+                            state['app_mlperf_inference_accuracy'] = z
+
+                            break
+                        except ValueError as e:
+                            pass
+
+            logger.info('')
+    return {'return': 0}
diff --git a/script/process-mlperf-accuracy/meta.yaml b/script/process-mlperf-accuracy/meta.yaml
index cd14ef67a..b2d628611 100644
--- a/script/process-mlperf-accuracy/meta.yaml
+++ b/script/process-mlperf-accuracy/meta.yaml
@@ -13,6 +13,20 @@ deps:
   - inference-src
   - accuracy-check-src
   tags: get,mlcommons,inference,src
+  skip_if_env:
+    MLC_DATASET:
+      - nuscenes
+      - cognata_deeplab
+      - cognata_ssd
+- names:
+  - automotive-src
+  - accuracy-check-src
+  tags: get,mlcommons,automotive,src
+  enable_if_env:
+    MLC_DATASET:
+      - nuscenes
+      - cognata_deeplab
+      - cognata_ssd
 input_mapping:
   rerun: MLC_RERUN
   result_dir: MLC_MLPERF_ACCURACY_RESULTS_DIR
@@ -273,3 +287,54 @@ variations:
     env:
       MLC_DATASET: waymo
     group: dataset
+  nuscenes:
+    deps:
+      - tags: get,preprocessed,dataset,nuscenes
+        skip_if_env:
+          MLC_RUN_STATE_DOCKER:
+            - "yes"
+        names:
+          - preprocessed-dataset-mlcommons-nuscenes
+      - tags: get,ml-model,bevformer
+        skip_if_env:
+          MLC_RUN_STATE_DOCKER:
+            - "yes"
+        names:
+          - ml-model-bevformer
+    env:
+      MLC_DATASET: nuscenes
+    group: dataset
+  cognata_ssd:
+    deps:
+      - tags: get,preprocessed,dataset,cognata,_mlc
+        skip_if_env:
+          MLC_RUN_STATE_DOCKER:
+            - "yes"
+        names:
+          - preprocessed-dataset-mlcommons-cognata-ssd
+      - tags: get,ml-model,ssd,resnet50,_mlc,_rclone
+        skip_if_any_env:
+          MLC_RUN_STATE_DOCKER:
+            - "yes"
+        names:
+          - ml-model-ssd
+    env:
+      MLC_DATASET: cognata_ssd
+    group: dataset
+  cognata_deeplab:
+    deps:
+      - tags: get,preprocessed,dataset,cognata,_mlc,_segmentation
+        skip_if_env:
+          MLC_RUN_STATE_DOCKER:
+            - "yes"
+        names:
+          - preprocessed-dataset-mlcommons-cognata-deeplabv3-plus
+      - tags: get,ml-model,deeplabv3-plus
+        skip_if_env:
+          MLC_RUN_STATE_DOCKER:
+            - "yes"
+        names:
+          - ml-model-deeplabv3-plus
+    env:
+      MLC_DATASET: cognata_deeplab
+    group: dataset
diff --git a/script/run-mlperf-automotive-app/customize.py b/script/run-mlperf-automotive-app/customize.py
index c3dda9c7a..5e26568db 100644
--- a/script/run-mlperf-automotive-app/customize.py
+++ b/script/run-mlperf-automotive-app/customize.py
@@ -116,7 +116,8 @@ def preprocess(i):
 
     test_list = []
 
-    variation_implementation = "_" + \
+    variation_benchmark_version = "_" + env["MLC_MLPERF_INFERENCE_VERSION"]
+    variation_implementation = ",_" + \
         env.get("MLC_MLPERF_IMPLEMENTATION", "reference")
     variation_model = ",_" + env["MLC_MLPERF_MODEL"]
     variation_backend = ",_" + \
@@ -135,7 +136,7 @@ def preprocess(i):
     else:
         variation_quantization_string = ""
 
-    tags = "app,abtf-inference," + variation_implementation + variation_model + variation_backend + variation_device + \
+    tags = "app,abtf-inference," + variation_benchmark_version + variation_implementation + variation_model + variation_backend + variation_device + \
         variation_run_style + variation_reproducibility + \
         variation_quantization_string + power_variation
     verbose = inp.get('v', False)
@@ -151,37 +152,37 @@ def preprocess(i):
         add_deps_recursive[key] = adr_from_meta[key]
 
     if env.get('MLC_MLPERF_LOADGEN_MAX_BATCHSIZE', '') != '':
-        if not add_deps_recursive.get('mlperf-inference-implementation', {}):
-            add_deps_recursive['mlperf-inference-implementation'] = {}
-        if add_deps_recursive['mlperf-inference-implementation'].get(
+        if not add_deps_recursive.get('abtf-inference-implementation', {}):
+            add_deps_recursive['abtf-inference-implementation'] = {}
+        if add_deps_recursive['abtf-inference-implementation'].get(
                 'tags', '') == '':
-            add_deps_recursive['mlperf-inference-implementation']['tags'] = ''
+            add_deps_recursive['abtf-inference-implementation']['tags'] = ''
         else:
-            add_deps_recursive['mlperf-inference-implementation']['tags'] += ','
-        add_deps_recursive['mlperf-inference-implementation']['tags'] += "_batch_size." + \
+            add_deps_recursive['abtf-inference-implementation']['tags'] += ','
+        add_deps_recursive['abtf-inference-implementation']['tags'] += "_batch_size." + \
             env['MLC_MLPERF_LOADGEN_MAX_BATCHSIZE']
 
     if env.get('MLC_MLPERF_INFERENCE_SUT_VARIATION', '') != '':
-        if not add_deps_recursive.get('mlperf-inference-implementation', {}):
-            add_deps_recursive['mlperf-inference-implementation'] = {}
-        if add_deps_recursive['mlperf-inference-implementation'].get(
+        if not add_deps_recursive.get('abtf-inference-implementation', {}):
+            add_deps_recursive['abtf-inference-implementation'] = {}
+        if add_deps_recursive['abtf-inference-implementation'].get(
                 'tags', '') == '':
-            add_deps_recursive['mlperf-inference-implementation']['tags'] = ''
+            add_deps_recursive['abtf-inference-implementation']['tags'] = ''
         else:
-            add_deps_recursive['mlperf-inference-implementation']['tags'] += ','
-        add_deps_recursive['mlperf-inference-implementation']['tags'] += "_" + \
+            add_deps_recursive['abtf-inference-implementation']['tags'] += ','
+        add_deps_recursive['abtf-inference-implementation']['tags'] += "_" + \
             env['MLC_MLPERF_INFERENCE_SUT_VARIATION']
 
     if env.get('MLC_NETWORK_LOADGEN', '') != '':
-        if not add_deps_recursive.get('mlperf-inference-implementation', {}):
-            add_deps_recursive['mlperf-inference-implementation'] = {}
+        if not add_deps_recursive.get('abtf-inference-implementation', {}):
+            add_deps_recursive['abtf-inference-implementation'] = {}
         network_variation_tag = f"_network-{env['MLC_NETWORK_LOADGEN']}"
-        if add_deps_recursive['mlperf-inference-implementation'].get(
+        if add_deps_recursive['abtf-inference-implementation'].get(
                 'tags', '') == '':
-            add_deps_recursive['mlperf-inference-implementation']['tags'] = ''
+            add_deps_recursive['abtf-inference-implementation']['tags'] = ''
         else:
-            add_deps_recursive['mlperf-inference-implementation']['tags'] += ','
-        add_deps_recursive['mlperf-inference-implementation']['tags'] += network_variation_tag
+            add_deps_recursive['abtf-inference-implementation']['tags'] += ','
+        add_deps_recursive['abtf-inference-implementation']['tags'] += network_variation_tag
 
     if env.get('MLC_OUTPUT_FOLDER_NAME', '') == '':
         env['MLC_OUTPUT_FOLDER_NAME'] = env['MLC_MLPERF_RUN_STYLE'] + "_results"
@@ -228,6 +229,9 @@ def preprocess(i):
         elif scenario == "Server":
             if env.get('MLC_MLPERF_LOADGEN_SERVER_TARGET_QPS'):
                 env['MLC_MLPERF_LOADGEN_TARGET_QPS'] = env['MLC_MLPERF_LOADGEN_SERVER_TARGET_QPS']
+        elif scenario == "ConstantStream":
+            if env.get('MLC_MLPERF_LOADGEN_CONSTANTSTREAM_TARGET_QPS'):
+                env['MLC_MLPERF_LOADGEN_TARGET_QPS'] = env['MLC_MLPERF_LOADGEN_CONSTANTSTREAM_TARGET_QPS']
         elif scenario == "SingleStream":
             if env.get('MLC_MLPERF_LOADGEN_SINGLESTREAM_TARGET_LATENCY'):
                 env['MLC_MLPERF_LOADGEN_TARGET_LATENCY'] = env['MLC_MLPERF_LOADGEN_SINGLESTREAM_TARGET_LATENCY']
@@ -290,9 +294,9 @@ def preprocess(i):
     if state.get("mlc-mlperf-inference-results"):
         # print(state["mlc-mlperf-inference-results"])
         for sut in state["mlc-mlperf-inference-results"]:  # only one sut will be there
-            # Better to do this in a stand alone CM script with proper deps but
+            # Better to do this in a stand alone MLC script with proper deps but
             # currently we manage this by modifying the sys path of the python
-            # executing CM
+            # executing MLC
             import mlperf_utils  # noqa
 
             logger.info(f"{sut}")
diff --git a/script/run-mlperf-automotive-app/meta.yaml b/script/run-mlperf-automotive-app/meta.yaml
index c70ac9e97..9a2fb7401 100644
--- a/script/run-mlperf-automotive-app/meta.yaml
+++ b/script/run-mlperf-automotive-app/meta.yaml
@@ -43,6 +43,7 @@ input_mapping:
   save_console_log: MLC_SAVE_CONSOLE_LOG
   execution_mode: MLC_MLPERF_RUN_STYLE
   find_performance: MLC_MLPERF_FIND_PERFORMANCE_MODE
+  framework: MLC_MLPERF_BACKEND
   gh_token: MLC_GH_TOKEN
   gpu_name: MLC_NVIDIA_GPU_NAME
   hw_name: MLC_HW_NAME
@@ -72,6 +73,7 @@ input_mapping:
   run_style: MLC_MLPERF_RUN_STYLE
   scenario: MLC_MLPERF_LOADGEN_SCENARIO
   server_target_qps: MLC_MLPERF_LOADGEN_SERVER_TARGET_QPS
+  constantstream_target_qps: MLC_MLPERF_LOADGEN_CONSTANTSTREAM_TARGET_QPS
   singlestream_target_latency: MLC_MLPERF_LOADGEN_SINGLESTREAM_TARGET_LATENCY
   skip_submission_generation: MLC_MLPERF_SKIP_SUBMISSION_GENERATION
   skip_truncation: MLC_SKIP_TRUNCATE_ACCURACY
@@ -105,8 +107,8 @@ deps:
   skip_if_env:
     MLC_MLPERF_USE_DOCKER: [ on ]
 - names:
-  - inference-src
-  tags: get,mlcommons,inference,src
+  - automotive-src
+  tags: get,mlcommons,automotive,src
   skip_if_env:
     MLC_MLPERF_USE_DOCKER: [ on ]
 - tags: get,sut,description
@@ -121,7 +123,7 @@ deps:
   skip_if_env:
     OUTPUT_BASE_DIR: [ on ]
 - tags: install,pip-package,for-mlc-python,_package.tabulate
-- tags: get,mlperf,inference,utils
+- tags: get,mlperf,automotive,utils
   skip_if_env:
     MLC_MLPERF_USE_DOCKER: [ on ]
 
@@ -214,6 +216,11 @@ variations:
       compiler:
         tags: gcc
     group: benchmark-version
+  
+  v0.5:
+    group: benchmark-version
+    env:
+      MLC_MLPERF_INFERENCE_VERSION: v0.5
 
   performance-and-accuracy:
     default: true
@@ -245,4 +252,4 @@ variations:
         - 'false'
         - 'False'
         - '0'
-      tags: generate,mlperf,inference,submission
+      tags: generate,mlperf,inference,submission,_automotive
diff --git a/script/run-mlperf-inference-app/meta.yaml b/script/run-mlperf-inference-app/meta.yaml
index b19362ecc..9cc3064c6 100644
--- a/script/run-mlperf-inference-app/meta.yaml
+++ b/script/run-mlperf-inference-app/meta.yaml
@@ -380,6 +380,20 @@ variations:
       mlperf-inference-nvidia-scratch-space:
         tags: _version.r5.0-dev
 
+  r5.0:
+    env:
+      MLC_MLPERF_INFERENCE_VERSION: '5.0'
+      MLC_RUN_MLPERF_INFERENCE_APP_DEFAULTS: r5.0_default
+      MLC_MLPERF_SUBMISSION_CHECKER_VERSION: v5.0
+    group: benchmark-version
+    adr:
+      get-mlperf-inference-results-dir:
+        tags: _version.r5.0
+      get-mlperf-inference-submission-dir:
+        tags: _version.r5.0
+      mlperf-inference-nvidia-scratch-space:
+        tags: _version.r5.0
+
   short:
     add_deps_recursive:
       submission-checker:
@@ -419,7 +433,7 @@ variations:
       skip_if_env:
         MLC_MLPERF_SKIP_SUBMISSION_GENERATION:
         - 'yes'
-      tags: generate,mlperf,inference,submission
+      tags: generate,mlperf,inference,submission,_inference
 
 versions:
   master: {}
diff --git a/script/run-mlperf-inference-submission-checker/meta.yaml b/script/run-mlperf-inference-submission-checker/meta.yaml
index 8d9667ae6..658e8f943 100644
--- a/script/run-mlperf-inference-submission-checker/meta.yaml
+++ b/script/run-mlperf-inference-submission-checker/meta.yaml
@@ -16,10 +16,6 @@ deps:
   - python
   - python3
   tags: get,python3
-- names:
-  - inference-src
-  - submission-checker-src
-  tags: get,mlcommons,inference,src
 - tags: pull,git,repo
   env:
     MLC_GIT_CHECKOUT_PATH: '<<<MLC_MLPERF_INFERENCE_SOURCE>>>'
@@ -43,6 +39,8 @@ deps:
 - enable_if_env:
     MLC_TMP_MLPERF_INFERENCE_PREPROCESS_SUBMISSION:
     - 'on'
+  names:
+    - preprocess-mlperf-submission
   tags: preprocess,mlperf,inference,submission
 docker:
   mlc_repo: mlcommons@mlperf-automations
@@ -137,6 +135,23 @@ variations:
   short-run:
     env:
       MLC_MLPERF_SHORT_RUN: 'yes'
+  inference:
+    default: true
+    add_deps_recursive:
+      preprocess-mlperf-submission:
+        tags: _inference
+    deps:
+      - names:
+        - inference-src
+        tags: mlcommons,inference,src
+  automotive:
+    add_deps_recursive:
+      preprocess-mlperf-submission:
+        tags: _automotive
+    deps:
+      - names:
+        - automotive-src
+        tags: mlcommons,automotive,src
 versions:
   master:
     adr:
diff --git a/script/save-machine-state/capture.py b/script/save-machine-state/capture.py
new file mode 100644
index 000000000..02963eb81
--- /dev/null
+++ b/script/save-machine-state/capture.py
@@ -0,0 +1,106 @@
+import os
+import json
+import psutil
+import platform
+import subprocess
+from datetime import datetime
+
+
+def read_file_safe(path):
+    try:
+        with open(path, 'r') as f:
+            return f.read().strip()
+    except Exception:
+        return None
+
+
+def run_command_safe(command, require_sudo=False):
+    if require_sudo and os.geteuid() != 0:
+        return "Skipped (requires sudo)"
+    try:
+        output = subprocess.check_output(command, shell=True, text=True)
+        return output.strip()
+    except subprocess.CalledProcessError:
+        return "Error running command"
+
+
+def detect_container_context():
+    context = {
+        "docker_env": os.path.exists('/.dockerenv'),
+        "cgroup_indicators": []
+    }
+    cgroup = read_file_safe('/proc/1/cgroup')
+    if cgroup:
+        for line in cgroup.splitlines():
+            if any(x in line for x in ['docker', 'kubepods', 'containerd']):
+                context["cgroup_indicators"].append(line)
+    return context
+
+
+def get_mounted_file_systems():
+    try:
+        with open("/proc/mounts", "r") as f:
+            return [line.strip() for line in f.readlines()]
+    except BaseException:
+        return []
+
+
+def capture_machine_state():
+    state = {
+        "timestamp": datetime.now().isoformat(),
+        "platform": {
+            "system": platform.system(),
+            "node": platform.node(),
+            "release": platform.release(),
+            "version": platform.version(),
+            "machine": platform.machine(),
+            "processor": platform.processor()
+        },
+        "cpu": {
+            "logical_cores": psutil.cpu_count(logical=True),
+            "physical_cores": psutil.cpu_count(logical=False),
+            "load_avg": psutil.getloadavg(),
+            "cpu_percent": psutil.cpu_percent(interval=1)
+        },
+        "memory": {
+            "virtual_memory": dict(psutil.virtual_memory()._asdict()),
+            "swap_memory": dict(psutil.swap_memory()._asdict())
+        },
+        "disk": {
+            "disk_usage": dict(psutil.disk_usage('/')._asdict()),
+            "partitions": [dict(p._asdict()) for p in psutil.disk_partitions()]
+        },
+        "bios": {
+            "vendor": run_command_safe("dmidecode -s bios-vendor", require_sudo=True),
+            "version": run_command_safe("dmidecode -s bios-version", require_sudo=True),
+            "release_date": run_command_safe("dmidecode -s bios-release-date", require_sudo=True)
+        },
+        "thp_settings": {
+            "enabled": read_file_safe("/sys/kernel/mm/transparent_hugepage/enabled") or "Skipped (requires sudo or permission)",
+            "defrag": read_file_safe("/sys/kernel/mm/transparent_hugepage/defrag") or "Skipped (requires sudo or permission)"
+        },
+        "kernel": {
+            "cmdline": read_file_safe("/proc/cmdline")
+        },
+        "uptime": read_file_safe("/proc/uptime"),
+        "process_count": len(psutil.pids()),
+        "users_sessions": [dict(u._asdict()) for u in psutil.users()],
+        "container_context": detect_container_context(),
+        "mounted_filesystems": get_mounted_file_systems()
+    }
+    return state
+
+
+def save_state_to_file(state, filename):
+    with open(filename, "w") as f:
+        json.dump(state, f, indent=4)
+
+
+# Example usage
+if __name__ == "__main__":
+
+    state = capture_machine_state()
+    save_file = os.environ.get(
+        'MLC_SYSTEM_STATE_SAVE_FILENAME',
+        'machine_state.json')
+    save_state_to_file(state, save_file)
diff --git a/script/save-machine-state/customize.py b/script/save-machine-state/customize.py
new file mode 100644
index 000000000..a7dbcc4f2
--- /dev/null
+++ b/script/save-machine-state/customize.py
@@ -0,0 +1,47 @@
+from mlc import utils
+import os
+import subprocess
+
+
+def check_installation(command, os_info):
+    if os_info['platform'] == "windows":
+        return subprocess.call(
+            [command, '--version'], stdout=subprocess.PIPE, stderr=subprocess.PIPE, shell=True) == 0
+    elif os_info['platform'] == "linux":
+        return subprocess.call(['which', command], stdout=subprocess.PIPE,
+                               stderr=subprocess.PIPE) == 0  # 0 means the package is there
+
+
+def preprocess(i):
+
+    os_info = i['os_info']
+    env = i['env']
+
+    if not check_installation("numactl", os_info):
+        env['MLC_INSTALL_NUMACTL'] = 'True'
+
+    # if not check_installation("cpupower",os_info):
+    env['MLC_INSTALL_CPUPOWER'] = 'True'
+
+    if env.get('MLC_PLATFORM_DETAILS_FILE_PATH', '') == '':
+        if env.get('MLC_PLATFORM_DETAILS_DIR_PATH', '') == '':
+            env['MLC_PLATFORM_DETAILS_DIR_PATH'] = os.getcwd()
+        if env.get('MLC_PLATFORM_DETAILS_FILE_NAME', '') == '':
+            env['MLC_PLATFORM_DETAILS_FILE_NAME'] = "system-info.txt"
+        env['MLC_PLATFORM_DETAILS_FILE_PATH'] = os.path.join(
+            env['MLC_PLATFORM_DETAILS_DIR_PATH'], env['MLC_PLATFORM_DETAILS_FILE_NAME'])
+
+    return {'return': 0}
+
+
+def postprocess(i):
+
+    state = i['state']
+
+    env = i['env']
+
+    os_info = i['os_info']
+
+    automation = i['automation']
+
+    return {'return': 0}
diff --git a/script/save-machine-state/meta.yaml b/script/save-machine-state/meta.yaml
new file mode 100644
index 000000000..0e22093f0
--- /dev/null
+++ b/script/save-machine-state/meta.yaml
@@ -0,0 +1,69 @@
+alias: save-machine-state
+automation_alias: script
+automation_uid: 5b4e0237da074764
+cache: false
+category: Platform information
+deps:
+- tags: detect,os
+- skip_if_env:
+    MLC_HOST_OS_TYPE:
+    - windows
+  tags: detect,sudo
+- names:
+  - python
+  - python3
+  tags: get,python
+- skip_if_any_env:
+    MLC_HOST_OS_TYPE:
+    - windows
+  skip_if_env:
+    MLC_SUDO_USER:
+    - 'no'
+  tags: get,sys-util,generic,_psmisc
+- enable_if_env:
+    MLC_HOST_OS_TYPE:
+    - linux
+  skip_if_env:
+    MLC_SUDO_USER:
+    - 'no'
+  tags: get,sys-util,generic,_systemd
+- enable_if_env:
+    MLC_HOST_OS_TYPE:
+    - linux
+  skip_if_env:
+    MLC_SUDO_USER:
+    - 'no'
+  tags: get,sys-util,generic,_dmidecode
+- tags: get,generic-python-lib,_package.psutil
+input_mapping:
+  outfile: MLC_SYSTEM_STATE_SAVE_FILENAME
+prehook_deps:
+- enable_if_env:
+    MLC_HOST_OS_TYPE:
+    - linux
+    MLC_INSTALL_NUMACTL:
+    - 'True'
+  skip_if_env:
+    MLC_SUDO_USER:
+    - 'no'
+  tags: get,sys-util,generic,_numactl
+- enable_if_env:
+    MLC_HOST_OS_TYPE:
+    - linux
+    MLC_INSTALL_CPUPOWER:
+    - 'True'
+  env:
+    MLC_TMP_FAIL_SAFE: 'yes'
+  ignore_missing: true
+  skip_if_env:
+    MLC_SUDO_USER:
+    - 'no'
+  tags: get,sys-util,generic,_linux-tools
+tags:
+- machine-state
+- save
+- machine
+- system
+- system-state
+- state
+uid: 2f62820ed7294659
diff --git a/script/save-machine-state/run.sh b/script/save-machine-state/run.sh
new file mode 100644
index 000000000..28e1867f6
--- /dev/null
+++ b/script/save-machine-state/run.sh
@@ -0,0 +1,4 @@
+#!/bin/bash
+set -e
+
+${MLC_PYTHON_BIN_WITH_PATH} ${MLC_TMP_CURRENT_SCRIPT_PATH}/capture.py
diff --git a/script/set-cpu-frequency/customize.py b/script/set-cpu-frequency/customize.py
new file mode 100644
index 000000000..b4f878d3d
--- /dev/null
+++ b/script/set-cpu-frequency/customize.py
@@ -0,0 +1,59 @@
+from mlc import utils
+import os
+import subprocess
+
+
+def preprocess(i):
+
+    env = i['env']
+    state = i['state']
+
+    freq = env.get('MLC_TARGET_FREQ', '').strip()
+    if freq != '':
+        try:
+            freq = parse_target_freq(freq)
+        except ValueError as e:
+            return {'return': 1, 'error': sys.stderr}
+
+    os_info = i['os_info']
+
+    return {'return': 0}
+
+
+def parse_target_freq(raw: str) -> int | None:
+    """
+    Parse a freq string like '2300KHz', '2.3GHz', '2500M' or a plain integer
+    into an integer number of kHz. Returns None if the env var is empty.
+    """
+    if not raw:
+        return None
+
+    # match <number>[.<fraction>][unit], unit = k/M/G (case-insensitive),
+    # optional "Hz"
+    m = re.fullmatch(r"([0-9]+(?:\.[0-9]+)?)([KMGkmg])(?:[Hh][Zz])?", raw)
+    if m:
+        val, unit = m.group(1), m.group(2).lower()
+        val = float(val)
+        if unit == "g":
+            khz = int(val * 1_000_000)
+        elif unit == "m":
+            khz = int(val * 1_000)
+        else:  # "k"
+            khz = int(val)
+        return khz
+
+    # plain integer? treat as kHz
+    if raw.isdigit():
+        return int(raw)
+
+    raise ValueError(f"Invalid frequency format: '{raw}'")
+
+
+def postprocess(i):
+
+    env = i['env']
+    state = i['state']
+
+    os_info = i['os_info']
+
+    return {'return': 0}
diff --git a/script/set-cpu-frequency/meta.yaml b/script/set-cpu-frequency/meta.yaml
new file mode 100644
index 000000000..85e6960dc
--- /dev/null
+++ b/script/set-cpu-frequency/meta.yaml
@@ -0,0 +1,26 @@
+alias: set-cpu-frequency
+automation_alias: script
+automation_uid: 5b4e0237da074764
+category: MLC Sys Utils
+deps:
+  - tags: detect,os
+  - tags: detect,sudo
+new_env_keys: []
+new_state_keys: []
+post_deps: []
+posthook_deps: []
+prehook_deps: []
+input_mapping:
+  freq: MLC_TARGET_FREQ
+  frequency: MLC_TARGET_FREQ
+tags:
+- set
+- cpu
+- target
+- freq
+- frequency
+tests:
+  run_inputs:
+    - freq: 1GHz
+    - freq: ''
+uid: 1fe0500d7a2e4c6a
diff --git a/script/set-cpu-frequency/run.sh b/script/set-cpu-frequency/run.sh
new file mode 100644
index 000000000..57b22872a
--- /dev/null
+++ b/script/set-cpu-frequency/run.sh
@@ -0,0 +1,60 @@
+#!/usr/bin/env bash
+set -euo pipefail
+
+TARGET_FREQ="${MLC_TARGET_FREQ:-}"
+DRIVER_FILE="/sys/devices/system/cpu/cpu0/cpufreq/scaling_driver"
+
+if [[ ! -r $DRIVER_FILE ]]; then
+  echo "Error: cannot read $DRIVER_FILE. Is cpufreq enabled?" >&2
+  exit 2
+fi
+DRIVER=$(<"$DRIVER_FILE")
+echo "Detected cpufreq driver: $DRIVER"
+
+# Normalize AMD pstate variants
+if [[ $DRIVER == amd-pstate* ]]; then
+  DRIVER_KEY="amd-pstate"
+else
+  DRIVER_KEY="$DRIVER"
+fi
+
+
+case "$DRIVER_KEY" in
+  intel_pstate)
+    echo "→ intel_pstate: disabling turbo, setting performance governor"
+    echo 0 | ${MLC_SUDO} tee /sys/devices/system/cpu/intel_pstate/no_turbo >/dev/null
+    ${MLC_SUDO} cpupower frequency-set -g performance
+    ;;
+
+  amd-pstate)
+    echo "→ amd_pstate: enabling boost, setting performance governor"
+    # boost file is global under cpufreq
+    if [[ -w /sys/devices/system/cpu/cpufreq/boost ]]; then
+      echo 1 | ${MLC_SUDO} tee /sys/devices/system/cpu/cpufreq/boost >/dev/null
+    fi
+    ${MLC_SUDO} cpupower frequency-set -g performance
+    echo ""
+    echo "Note: amd-pstate does _not_ support a userspace/fixed frequency mode."
+    echo "If you need a precise kHz, switch back to acpi-cpufreq in your kernel cmdline."
+    ;;
+
+  acpi-cpufreq)
+    echo "→ acpi-cpufreq: switching to userspace governor + fixed freq"
+    if [[ -z "$TARGET_FREQ" ]]; then
+      TARGET_FREQ=$(< /sys/devices/system/cpu/cpu0/cpufreq/scaling_min_freq)
+      echo "   No target given; defaulting to min freq = ${TARGET_FREQ} kHz"
+    fi
+    ${MLC_SUDO} cpupower frequency-set -g userspace
+    ${MLC_SUDO} cpupower frequency-set -f "${TARGET_FREQ}"
+    ;;
+
+  *)
+    echo "Unsupported driver: $DRIVER" >&2
+    exit 3
+    ;;
+esac
+
+echo ""
+echo "Resulting settings for CPU0:"
+cpupower frequency-info | sed -n '1,5p'
+
diff --git a/script/truncate-mlperf-inference-accuracy-log/meta.yaml b/script/truncate-mlperf-inference-accuracy-log/meta.yaml
index c0f02f6d3..2acbf3b85 100644
--- a/script/truncate-mlperf-inference-accuracy-log/meta.yaml
+++ b/script/truncate-mlperf-inference-accuracy-log/meta.yaml
@@ -9,15 +9,24 @@ deps:
   - python
   - python3
   tags: get,python3
-- names:
-  - inference-src
-  tags: get,mlcommons,inference,src
 - names:
   - get-mlperf-submission-dir
   skip_if_env:
     MLC_MLPERF_INFERENCE_SUBMISSION_DIR:
     - 'on'
   tags: get,mlperf,submission,dir
+variations:
+  inference:
+    default: true
+    deps:
+      - names:
+        - inference-src
+        tags: mlcommons,inference,src
+  automotive:
+    deps:
+      - names:
+        - automotive-src
+        tags: mlcommons,automotive,src
 input_mapping:
   input: MLC_MLPERF_INFERENCE_SUBMISSION_DIR
   submission_dir: MLC_MLPERF_INFERENCE_SUBMISSION_DIR