diff --git a/libs/labelbox/src/labelbox/client.py b/libs/labelbox/src/labelbox/client.py
index cccd23be1..16f28148e 100644
--- a/libs/labelbox/src/labelbox/client.py
+++ b/libs/labelbox/src/labelbox/client.py
@@ -8,7 +8,7 @@
 import urllib.parse
 from collections import defaultdict
 from types import MappingProxyType
-from typing import Any, Callable, Dict, List, Optional, Union, overload
+from typing import Any, Callable, Dict, List, Optional, Set, Union, overload
 
 import lbox.exceptions
 import requests
@@ -23,6 +23,7 @@
 from labelbox.orm.db_object import DbObject
 from labelbox.orm.model import Entity, Field
 from labelbox.pagination import PaginatedCollection
+from labelbox.project_validation import _CoreProjectInput
 from labelbox.schema import role
 from labelbox.schema.catalog import Catalog
 from labelbox.schema.data_row import DataRow
@@ -596,7 +597,18 @@ def create_dataset(
             raise e
         return dataset
 
-    def create_project(self, **kwargs) -> Project:
+    def create_project(
+        self,
+        name: str,
+        media_type: MediaType,
+        description: Optional[str] = None,
+        quality_modes: Optional[Set[QualityMode]] = {
+            QualityMode.Benchmark,
+            QualityMode.Consensus,
+        },
+        is_benchmark_enabled: Optional[bool] = None,
+        is_consensus_enabled: Optional[bool] = None,
+    ) -> Project:
         """Creates a Project object on the server.
 
         Attribute values are passed as keyword arguments.
@@ -605,7 +617,6 @@ def create_project(self, **kwargs) -> Project:
                 name="<project_name>",
                 description="<project_description>",
                 media_type=MediaType.Image,
-                queue_mode=QueueMode.Batch
             )
 
         Args:
@@ -613,53 +624,38 @@ def create_project(self, **kwargs) -> Project:
             description (str): A short summary for the project
             media_type (MediaType): The type of assets that this project will accept
             queue_mode (Optional[QueueMode]): The queue mode to use
-            quality_mode (Optional[QualityMode]): The quality mode to use (e.g. Benchmark, Consensus). Defaults to
-                Benchmark
             quality_modes (Optional[List[QualityMode]]): The quality modes to use (e.g. Benchmark, Consensus). Defaults to
                 Benchmark.
+            is_benchmark_enabled (Optional[bool]): Whether the project supports benchmark. Defaults to None.
+            is_consensus_enabled (Optional[bool]): Whether the project supports consensus. Defaults to None.
         Returns:
             A new Project object.
         Raises:
-            InvalidAttributeError: If the Project type does not contain
-                any of the attribute names given in kwargs.
-
-        NOTE: the following attributes are used only in chat model evaluation projects:
-            dataset_name_or_id, append_to_existing_dataset, data_row_count, editor_task_type
-            They are not used for general projects and not supported in this method
+            ValueError: If inputs are invalid.
         """
-        #  The following arguments are not supported for general projects, only for chat model evaluation projects
-        kwargs.pop("dataset_name_or_id", None)
-        kwargs.pop("append_to_existing_dataset", None)
-        kwargs.pop("data_row_count", None)
-        kwargs.pop("editor_task_type", None)
-        return self._create_project(**kwargs)
-
-    @overload
-    def create_model_evaluation_project(
-        self,
-        dataset_name: str,
-        dataset_id: str = None,
-        data_row_count: int = 100,
-        **kwargs,
-    ) -> Project:
-        pass
-
-    @overload
-    def create_model_evaluation_project(
-        self,
-        dataset_id: str,
-        dataset_name: str = None,
-        data_row_count: int = 100,
-        **kwargs,
-    ) -> Project:
-        pass
+        input = {
+            "name": name,
+            "description": description,
+            "media_type": media_type,
+            "quality_modes": quality_modes,
+            "is_benchmark_enabled": is_benchmark_enabled,
+            "is_consensus_enabled": is_consensus_enabled,
+        }
+        return self._create_project(_CoreProjectInput(**input))
 
     def create_model_evaluation_project(
         self,
+        name: str,
+        description: Optional[str] = None,
+        quality_modes: Optional[Set[QualityMode]] = {
+            QualityMode.Benchmark,
+            QualityMode.Consensus,
+        },
+        is_benchmark_enabled: Optional[bool] = None,
+        is_consensus_enabled: Optional[bool] = None,
         dataset_id: Optional[str] = None,
         dataset_name: Optional[str] = None,
         data_row_count: int = 100,
-        **kwargs,
     ) -> Project:
         """
         Use this method exclusively to create a chat model evaluation project.
@@ -667,12 +663,12 @@ def create_model_evaluation_project(
             dataset_name: When creating a new dataset, pass the name
             dataset_id: When using an existing dataset, pass the id
             data_row_count: The number of data row assets to use for the project
-            **kwargs: Additional parameters to pass to the the create_project method
+            See create_project for additional parameters
         Returns:
             Project: The created project
 
         Examples:
-            >>> client.create_model_evaluation_project(name=project_name, dataset_name="new data set")
+            >>> client.create_model_evaluation_project(name=project_name, media_type=dataset_name="new data set")
             >>>     This creates a new dataset with a default number of rows (100), creates new project and assigns a batch of the newly created datarows to the project.
 
             >>> client.create_model_evaluation_project(name=project_name, dataset_name="new data set", data_row_count=10)
@@ -690,8 +686,6 @@ def create_model_evaluation_project(
             raise ValueError(
                 "dataset_name or data_set_id must be present and not be an empty string."
             )
-        if data_row_count <= 0:
-            raise ValueError("data_row_count must be a positive integer.")
 
         if dataset_id:
             append_to_existing_dataset = True
@@ -700,42 +694,68 @@ def create_model_evaluation_project(
             append_to_existing_dataset = False
             dataset_name_or_id = dataset_name
 
-        kwargs["media_type"] = MediaType.Conversational
-        kwargs["dataset_name_or_id"] = dataset_name_or_id
-        kwargs["append_to_existing_dataset"] = append_to_existing_dataset
-        kwargs["data_row_count"] = data_row_count
-        kwargs["editor_task_type"] = EditorTaskType.ModelChatEvaluation.value
+        media_type = MediaType.Conversational
+        editor_task_type = EditorTaskType.ModelChatEvaluation
 
-        return self._create_project(**kwargs)
+        input = {
+            "name": name,
+            "description": description,
+            "media_type": media_type,
+            "quality_modes": quality_modes,
+            "is_benchmark_enabled": is_benchmark_enabled,
+            "is_consensus_enabled": is_consensus_enabled,
+            "dataset_name_or_id": dataset_name_or_id,
+            "append_to_existing_dataset": append_to_existing_dataset,
+            "data_row_count": data_row_count,
+            "editor_task_type": editor_task_type,
+        }
+        return self._create_project(_CoreProjectInput(**input))
 
-    def create_offline_model_evaluation_project(self, **kwargs) -> Project:
+    def create_offline_model_evaluation_project(
+        self,
+        name: str,
+        description: Optional[str] = None,
+        quality_modes: Optional[Set[QualityMode]] = {
+            QualityMode.Benchmark,
+            QualityMode.Consensus,
+        },
+        is_benchmark_enabled: Optional[bool] = None,
+        is_consensus_enabled: Optional[bool] = None,
+    ) -> Project:
         """
         Creates a project for offline model evaluation.
         Args:
-            **kwargs: Additional parameters to pass see the create_project method
+            See create_project for parameters
         Returns:
             Project: The created project
         """
-        kwargs["media_type"] = (
-            MediaType.Conversational
-        )  # Only Conversational is supported
-        kwargs["editor_task_type"] = (
-            EditorTaskType.OfflineModelChatEvaluation.value
-        )  # Special editor task type for offline model evaluation
-
-        # The following arguments are not supported for offline model evaluation
-        kwargs.pop("dataset_name_or_id", None)
-        kwargs.pop("append_to_existing_dataset", None)
-        kwargs.pop("data_row_count", None)
-
-        return self._create_project(**kwargs)
+        input = {
+            "name": name,
+            "description": description,
+            "media_type": MediaType.Conversational,
+            "quality_modes": quality_modes,
+            "is_benchmark_enabled": is_benchmark_enabled,
+            "is_consensus_enabled": is_consensus_enabled,
+            "editor_task_type": EditorTaskType.OfflineModelChatEvaluation,
+        }
+        return self._create_project(_CoreProjectInput(**input))
 
     def create_prompt_response_generation_project(
         self,
+        name: str,
+        media_type: MediaType,
+        description: Optional[str] = None,
+        auto_audit_percentage: Optional[float] = None,
+        auto_audit_number_of_labels: Optional[int] = None,
+        quality_modes: Optional[Set[QualityMode]] = {
+            QualityMode.Benchmark,
+            QualityMode.Consensus,
+        },
+        is_benchmark_enabled: Optional[bool] = None,
+        is_consensus_enabled: Optional[bool] = None,
         dataset_id: Optional[str] = None,
         dataset_name: Optional[str] = None,
         data_row_count: int = 100,
-        **kwargs,
     ) -> Project:
         """
         Use this method exclusively to create a prompt and response generation project.
@@ -744,7 +764,8 @@ def create_prompt_response_generation_project(
             dataset_name: When creating a new dataset, pass the name
             dataset_id: When using an existing dataset, pass the id
             data_row_count: The number of data row assets to use for the project
-            **kwargs: Additional parameters to pass see the create_project method
+            media_type: The type of assets that this project will accept. Limited to LLMPromptCreation and LLMPromptResponseCreation
+            See create_project for additional parameters
         Returns:
             Project: The created project
 
@@ -774,9 +795,6 @@ def create_prompt_response_generation_project(
                 "Only provide a dataset_name or dataset_id, not both."
             )
 
-        if data_row_count <= 0:
-            raise ValueError("data_row_count must be a positive integer.")
-
         if dataset_id:
             append_to_existing_dataset = True
             dataset_name_or_id = dataset_id
@@ -784,7 +802,7 @@ def create_prompt_response_generation_project(
             append_to_existing_dataset = False
             dataset_name_or_id = dataset_name
 
-        if "media_type" in kwargs and kwargs.get("media_type") not in [
+        if media_type not in [
             MediaType.LLMPromptCreation,
             MediaType.LLMPromptResponseCreation,
         ]:
@@ -792,131 +810,54 @@ def create_prompt_response_generation_project(
                 "media_type must be either LLMPromptCreation or LLMPromptResponseCreation"
             )
 
-        kwargs["dataset_name_or_id"] = dataset_name_or_id
-        kwargs["append_to_existing_dataset"] = append_to_existing_dataset
-        kwargs["data_row_count"] = data_row_count
-
-        kwargs.pop("editor_task_type", None)
-
-        return self._create_project(**kwargs)
+        input = {
+            "name": name,
+            "description": description,
+            "media_type": media_type,
+            "auto_audit_percentage": auto_audit_percentage,
+            "auto_audit_number_of_labels": auto_audit_number_of_labels,
+            "quality_modes": quality_modes,
+            "is_benchmark_enabled": is_benchmark_enabled,
+            "is_consensus_enabled": is_consensus_enabled,
+            "dataset_name_or_id": dataset_name_or_id,
+            "append_to_existing_dataset": append_to_existing_dataset,
+            "data_row_count": data_row_count,
+        }
+        return self._create_project(_CoreProjectInput(**input))
 
-    def create_response_creation_project(self, **kwargs) -> Project:
+    def create_response_creation_project(
+        self,
+        name: str,
+        description: Optional[str] = None,
+        quality_modes: Optional[Set[QualityMode]] = {
+            QualityMode.Benchmark,
+            QualityMode.Consensus,
+        },
+        is_benchmark_enabled: Optional[bool] = None,
+        is_consensus_enabled: Optional[bool] = None,
+    ) -> Project:
         """
         Creates a project for response creation.
         Args:
-            **kwargs: Additional parameters to pass see the create_project method
+            See create_project for parameters
         Returns:
             Project: The created project
         """
-        kwargs["media_type"] = MediaType.Text  # Only Text is supported
-        kwargs["editor_task_type"] = (
-            EditorTaskType.ResponseCreation.value
-        )  # Special editor task type for response creation projects
-
-        # The following arguments are not supported for response creation projects
-        kwargs.pop("dataset_name_or_id", None)
-        kwargs.pop("append_to_existing_dataset", None)
-        kwargs.pop("data_row_count", None)
-
-        return self._create_project(**kwargs)
-
-    def _create_project(self, **kwargs) -> Project:
-        auto_audit_percentage = kwargs.get("auto_audit_percentage")
-        auto_audit_number_of_labels = kwargs.get("auto_audit_number_of_labels")
-        if (
-            auto_audit_percentage is not None
-            or auto_audit_number_of_labels is not None
-        ):
-            raise ValueError(
-                "quality_modes must be set instead of auto_audit_percentage or auto_audit_number_of_labels."
-            )
-
-        name = kwargs.get("name")
-        if name is None or not name.strip():
-            raise ValueError("project name must be a valid string.")
-
-        queue_mode = kwargs.get("queue_mode")
-        if queue_mode is QueueMode.Dataset:
-            raise ValueError(
-                "Dataset queue mode is deprecated. Please prefer Batch queue mode."
-            )
-        elif queue_mode is QueueMode.Batch:
-            logger.warning(
-                "Passing a queue mode of batch is redundant and will soon no longer be supported."
-            )
-
-        media_type = kwargs.get("media_type")
-        if media_type and MediaType.is_supported(media_type):
-            media_type_value = media_type.value
-        elif media_type:
-            raise TypeError(
-                f"{media_type} is not a valid media type. Use"
-                f" any of {MediaType.get_supported_members()}"
-                " from MediaType. Example: MediaType.Image."
-            )
-        else:
-            logger.warning(
-                "Creating a project without specifying media_type"
-                " through this method will soon no longer be supported."
-            )
-            media_type_value = None
-
-        quality_modes = kwargs.get("quality_modes")
-        quality_mode = kwargs.get("quality_mode")
-        if quality_mode:
-            logger.warning(
-                "Passing quality_mode is deprecated and will soon no longer be supported. Use quality_modes instead."
-            )
-
-        if quality_modes and quality_mode:
-            raise ValueError(
-                "Cannot use both quality_modes and quality_mode at the same time. Use one or the other."
-            )
+        input = {
+            "name": name,
+            "description": description,
+            "media_type": MediaType.Text,  # Only Text is supported
+            "quality_modes": quality_modes,
+            "is_benchmark_enabled": is_benchmark_enabled,
+            "is_consensus_enabled": is_consensus_enabled,
+            "editor_task_type": EditorTaskType.ResponseCreation.value,  # Special editor task type for response creation projects
+        }
+        return self._create_project(_CoreProjectInput(**input))
 
-        if not quality_modes and not quality_mode:
-            logger.info("Defaulting quality modes to Benchmark and Consensus.")
-
-        data = kwargs
-        data.pop("quality_modes", None)
-        data.pop("quality_mode", None)
-
-        # check if quality_modes is a set, if not, convert to set
-        quality_modes_set = quality_modes
-        if quality_modes and not isinstance(quality_modes, set):
-            quality_modes_set = set(quality_modes)
-        if quality_mode:
-            quality_modes_set = {quality_mode}
-
-        if (
-            quality_modes_set is None
-            or len(quality_modes_set) == 0
-            or quality_modes_set
-            == {QualityMode.Benchmark, QualityMode.Consensus}
-        ):
-            data["auto_audit_number_of_labels"] = (
-                CONSENSUS_AUTO_AUDIT_NUMBER_OF_LABELS
-            )
-            data["auto_audit_percentage"] = CONSENSUS_AUTO_AUDIT_PERCENTAGE
-            data["is_benchmark_enabled"] = True
-            data["is_consensus_enabled"] = True
-        elif quality_modes_set == {QualityMode.Benchmark}:
-            data["auto_audit_number_of_labels"] = (
-                BENCHMARK_AUTO_AUDIT_NUMBER_OF_LABELS
-            )
-            data["auto_audit_percentage"] = BENCHMARK_AUTO_AUDIT_PERCENTAGE
-            data["is_benchmark_enabled"] = True
-        elif quality_modes_set == {QualityMode.Consensus}:
-            data["auto_audit_number_of_labels"] = (
-                CONSENSUS_AUTO_AUDIT_NUMBER_OF_LABELS
-            )
-            data["auto_audit_percentage"] = CONSENSUS_AUTO_AUDIT_PERCENTAGE
-            data["is_consensus_enabled"] = True
-        else:
-            raise ValueError(
-                f"{quality_modes_set} is not a valid quality modes set. Allowed values are [Benchmark, Consensus]"
-            )
+    def _create_project(self, input: _CoreProjectInput) -> Project:
+        media_type_value = input.media_type.value
 
-        params = {**data}
+        params = input.model_dump(exclude_none=True)
         if media_type_value:
             params["media_type"] = media_type_value
 
diff --git a/libs/labelbox/src/labelbox/project_validation.py b/libs/labelbox/src/labelbox/project_validation.py
new file mode 100644
index 000000000..0380e94f0
--- /dev/null
+++ b/libs/labelbox/src/labelbox/project_validation.py
@@ -0,0 +1,87 @@
+from typing import Optional, Set
+
+from pydantic import BaseModel, ConfigDict, Field, model_validator
+from typing_extensions import Annotated
+
+from labelbox.schema.media_type import MediaType
+from labelbox.schema.ontology_kind import EditorTaskType
+from labelbox.schema.quality_mode import (
+    BENCHMARK_AUTO_AUDIT_NUMBER_OF_LABELS,
+    BENCHMARK_AUTO_AUDIT_PERCENTAGE,
+    CONSENSUS_AUTO_AUDIT_NUMBER_OF_LABELS,
+    CONSENSUS_AUTO_AUDIT_PERCENTAGE,
+    QualityMode,
+)
+from labelbox.schema.queue_mode import QueueMode
+
+PositiveInt = Annotated[int, Field(gt=0)]
+
+
+class _CoreProjectInput(BaseModel):
+    name: str
+    description: Optional[str] = None
+    media_type: MediaType
+    queue_mode: QueueMode = Field(default=QueueMode.Batch, frozen=True)
+    auto_audit_percentage: Optional[float] = None
+    auto_audit_number_of_labels: Optional[int] = None
+    quality_modes: Optional[Set[QualityMode]] = Field(
+        default={QualityMode.Benchmark, QualityMode.Consensus}, exclude=True
+    )
+    is_benchmark_enabled: Optional[bool] = None
+    is_consensus_enabled: Optional[bool] = None
+    dataset_name_or_id: Optional[str] = None
+    append_to_existing_dataset: Optional[bool] = None
+    data_row_count: Optional[PositiveInt] = None
+    editor_task_type: Optional[EditorTaskType] = None
+
+    model_config = ConfigDict(extra="forbid")
+
+    @model_validator(mode="after")
+    def validate_fields(self):
+        if (
+            self.auto_audit_percentage is not None
+            or self.auto_audit_number_of_labels is not None
+        ):
+            raise ValueError(
+                "quality_modes must be set instead of auto_audit_percentage or auto_audit_number_of_labels."
+            )
+
+        if not self.name.strip():
+            raise ValueError("project name must be a valid string.")
+
+        if self.quality_modes == {
+            QualityMode.Benchmark,
+            QualityMode.Consensus,
+        }:
+            self._set_quality_mode_attributes(
+                CONSENSUS_AUTO_AUDIT_NUMBER_OF_LABELS,
+                CONSENSUS_AUTO_AUDIT_PERCENTAGE,
+                is_benchmark_enabled=True,
+                is_consensus_enabled=True,
+            )
+        elif self.quality_modes == {QualityMode.Benchmark}:
+            self._set_quality_mode_attributes(
+                BENCHMARK_AUTO_AUDIT_NUMBER_OF_LABELS,
+                BENCHMARK_AUTO_AUDIT_PERCENTAGE,
+                is_benchmark_enabled=True,
+            )
+        elif self.quality_modes == {QualityMode.Consensus}:
+            self._set_quality_mode_attributes(
+                number_of_labels=CONSENSUS_AUTO_AUDIT_NUMBER_OF_LABELS,
+                percentage=CONSENSUS_AUTO_AUDIT_PERCENTAGE,
+                is_consensus_enabled=True,
+            )
+
+        return self
+
+    def _set_quality_mode_attributes(
+        self,
+        number_of_labels,
+        percentage,
+        is_benchmark_enabled=False,
+        is_consensus_enabled=False,
+    ):
+        self.auto_audit_number_of_labels = number_of_labels
+        self.auto_audit_percentage = percentage
+        self.is_benchmark_enabled = is_benchmark_enabled
+        self.is_consensus_enabled = is_consensus_enabled
diff --git a/libs/labelbox/src/labelbox/schema/ontology_kind.py b/libs/labelbox/src/labelbox/schema/ontology_kind.py
index 3171b811e..79ef7d7a3 100644
--- a/libs/labelbox/src/labelbox/schema/ontology_kind.py
+++ b/libs/labelbox/src/labelbox/schema/ontology_kind.py
@@ -53,7 +53,7 @@ def evaluate_ontology_kind_with_media_type(
         return media_type
 
 
-class EditorTaskType(Enum):
+class EditorTaskType(str, Enum):
     ModelChatEvaluation = "MODEL_CHAT_EVALUATION"
     ResponseCreation = "RESPONSE_CREATION"
     OfflineModelChatEvaluation = "OFFLINE_MODEL_CHAT_EVALUATION"
diff --git a/libs/labelbox/tests/conftest.py b/libs/labelbox/tests/conftest.py
index d25544034..a57e6b842 100644
--- a/libs/labelbox/tests/conftest.py
+++ b/libs/labelbox/tests/conftest.py
@@ -32,7 +32,6 @@
 from labelbox.schema.ontology import Ontology
 from labelbox.schema.project import Project
 from labelbox.schema.quality_mode import QualityMode
-from labelbox.schema.queue_mode import QueueMode
 
 IMG_URL = "https://picsum.photos/200/300.jpg"
 MASKABLE_IMG_URL = "https://storage.googleapis.com/labelbox-datasets/image_sample_data/2560px-Kitano_Street_Kobe01s5s4110.jpeg"
@@ -444,7 +443,6 @@ def conversation_entity_data_row(client, rand_gen):
 def project(client, rand_gen):
     project = client.create_project(
         name=rand_gen(str),
-        queue_mode=QueueMode.Batch,
         media_type=MediaType.Image,
     )
     yield project
@@ -455,8 +453,7 @@ def project(client, rand_gen):
 def consensus_project(client, rand_gen):
     project = client.create_project(
         name=rand_gen(str),
-        quality_mode=QualityMode.Consensus,
-        queue_mode=QueueMode.Batch,
+        quality_modes={QualityMode.Consensus},
         media_type=MediaType.Image,
     )
     yield project
@@ -646,7 +643,6 @@ def configured_project_with_label(
     """
     project = client.create_project(
         name=rand_gen(str),
-        queue_mode=QueueMode.Batch,
         media_type=MediaType.Image,
     )
     project._wait_until_data_rows_are_processed(
@@ -749,7 +745,6 @@ def configured_batch_project_with_label(
     """
     project = client.create_project(
         name=rand_gen(str),
-        queue_mode=QueueMode.Batch,
         media_type=MediaType.Image,
     )
     data_rows = [dr.uid for dr in list(dataset.data_rows())]
@@ -784,7 +779,6 @@ def configured_batch_project_with_multiple_datarows(
     """
     project = client.create_project(
         name=rand_gen(str),
-        queue_mode=QueueMode.Batch,
         media_type=MediaType.Image,
     )
     global_keys = [dr.global_key for dr in data_rows]
@@ -1065,7 +1059,6 @@ def configured_project_with_complex_ontology(
 ):
     project = client.create_project(
         name=rand_gen(str),
-        queue_mode=QueueMode.Batch,
         media_type=MediaType.Image,
     )
     dataset = initial_dataset
diff --git a/libs/labelbox/tests/data/export/conftest.py b/libs/labelbox/tests/data/export/conftest.py
index 0a62f39c8..2bd00775f 100644
--- a/libs/labelbox/tests/data/export/conftest.py
+++ b/libs/labelbox/tests/data/export/conftest.py
@@ -1,9 +1,11 @@
-import uuid
 import time
+import uuid
+
 import pytest
-from labelbox.schema.queue_mode import QueueMode
+
+from labelbox.schema.annotation_import import AnnotationImportState, LabelImport
 from labelbox.schema.labeling_frontend import LabelingFrontend
-from labelbox.schema.annotation_import import LabelImport, AnnotationImportState
+from labelbox.schema.media_type import MediaType
 
 
 @pytest.fixture
@@ -246,7 +248,7 @@ def configured_project_with_ontology(
     dataset = initial_dataset
     project = client.create_project(
         name=rand_gen(str),
-        queue_mode=QueueMode.Batch,
+        media_type=MediaType.Image,
     )
     editor = list(
         client.get_labeling_frontends(where=LabelingFrontend.name == "editor")
@@ -273,7 +275,24 @@ def configured_project_without_data_rows(
     project = client.create_project(
         name=rand_gen(str),
         description=rand_gen(str),
-        queue_mode=QueueMode.Batch,
+        media_type=MediaType.Image,
+    )
+    editor = list(
+        client.get_labeling_frontends(where=LabelingFrontend.name == "editor")
+    )[0]
+    project.setup(editor, ontology)
+    yield project
+    teardown_helpers.teardown_project_labels_ontology_feature_schemas(project)
+
+
+@pytest.fixture
+def configured_video_project_without_data_rows(
+    client, ontology, rand_gen, teardown_helpers
+):
+    project = client.create_project(
+        name=rand_gen(str),
+        description=rand_gen(str),
+        media_type=MediaType.Video,
     )
     editor = list(
         client.get_labeling_frontends(where=LabelingFrontend.name == "editor")
diff --git a/libs/labelbox/tests/data/export/streamable/test_export_video_streamable.py b/libs/labelbox/tests/data/export/streamable/test_export_video_streamable.py
index 28ef6e0cf..7fa2bd6f6 100644
--- a/libs/labelbox/tests/data/export/streamable/test_export_video_streamable.py
+++ b/libs/labelbox/tests/data/export/streamable/test_export_video_streamable.py
@@ -21,13 +21,13 @@ def org_id(self, client):
     def test_export(
         self,
         client,
-        configured_project_without_data_rows,
+        configured_video_project_without_data_rows,
         video_data,
         video_data_row,
         bbox_video_annotation_objects,
         rand_gen,
     ):
-        project = configured_project_without_data_rows
+        project = configured_video_project_without_data_rows
         project_id = project.uid
         labels = []
 
diff --git a/libs/labelbox/tests/integration/conftest.py b/libs/labelbox/tests/integration/conftest.py
index c917a6164..f16689950 100644
--- a/libs/labelbox/tests/integration/conftest.py
+++ b/libs/labelbox/tests/integration/conftest.py
@@ -1,30 +1,30 @@
-from collections import defaultdict
-from itertools import islice
 import json
 import os
-import sys
 import re
+import sys
 import time
 import uuid
-import requests
-from types import SimpleNamespace
-from typing import Type, List
+from collections import defaultdict
 from enum import Enum
-from typing import Tuple
+from itertools import islice
+from types import SimpleNamespace
+from typing import List, Tuple, Type
 
 import pytest
 import requests
 
-from labelbox import Dataset, DataRow
-from labelbox import LabelingFrontend
 from labelbox import (
-    OntologyBuilder,
-    Tool,
-    Option,
     Classification,
+    Client,
+    DataRow,
+    Dataset,
+    LabelingFrontend,
     MediaType,
+    OntologyBuilder,
+    Option,
     PromptResponseClassification,
     ResponseOption,
+    Tool,
 )
 from labelbox.orm import query
 from labelbox.pagination import PaginatedCollection
@@ -32,11 +32,9 @@
 from labelbox.schema.catalog import Catalog
 from labelbox.schema.enums import AnnotationImportState
 from labelbox.schema.invite import Invite
+from labelbox.schema.ontology_kind import OntologyKind
 from labelbox.schema.quality_mode import QualityMode
-from labelbox.schema.queue_mode import QueueMode
 from labelbox.schema.user import User
-from labelbox import Client
-from labelbox.schema.ontology_kind import OntologyKind
 
 
 @pytest.fixture
@@ -69,7 +67,6 @@ def project_pack(client):
     projects = [
         client.create_project(
             name=f"user-proj-{idx}",
-            queue_mode=QueueMode.Batch,
             media_type=MediaType.Image,
         )
         for idx in range(2)
@@ -117,7 +114,6 @@ def configured_project_with_complex_ontology(
 ):
     project = client.create_project(
         name=rand_gen(str),
-        queue_mode=QueueMode.Batch,
         media_type=MediaType.Image,
     )
     dataset = initial_dataset
diff --git a/libs/labelbox/tests/integration/test_client_errors.py b/libs/labelbox/tests/integration/test_client_errors.py
index c8721dfc4..38022d1d2 100644
--- a/libs/labelbox/tests/integration/test_client_errors.py
+++ b/libs/labelbox/tests/integration/test_client_errors.py
@@ -8,6 +8,7 @@
 
 import labelbox.client
 from labelbox import Project, User
+from labelbox.schema.media_type import MediaType
 
 
 def test_missing_api_key():
@@ -29,7 +30,7 @@ def test_bad_key(rand_gen):
     client = labelbox.client.Client(api_key=bad_key)
 
     with pytest.raises(lbox.exceptions.AuthenticationError) as excinfo:
-        client.create_project(name=rand_gen(str))
+        client.create_project(name=rand_gen(str), media_type=MediaType.Image)
 
 
 def test_syntax_error(client):
@@ -77,31 +78,7 @@ def test_network_error(client):
     )
 
     with pytest.raises(lbox.exceptions.NetworkError) as excinfo:
-        client.create_project(name="Project name")
-
-
-def test_invalid_attribute_error(
-    client,
-    rand_gen,
-):
-    # Creation
-    with pytest.raises(lbox.exceptions.InvalidAttributeError) as excinfo:
-        client.create_project(name="Name", invalid_field="Whatever")
-    assert excinfo.value.db_object_type == Project
-    assert excinfo.value.field == "invalid_field"
-
-    # Update
-    project = client.create_project(name=rand_gen(str))
-    with pytest.raises(lbox.exceptions.InvalidAttributeError) as excinfo:
-        project.update(invalid_field="Whatever")
-    assert excinfo.value.db_object_type == Project
-    assert excinfo.value.field == "invalid_field"
-
-    # Top-level-fetch
-    with pytest.raises(lbox.exceptions.InvalidAttributeError) as excinfo:
-        client.get_projects(where=User.email == "email")
-    assert excinfo.value.db_object_type == Project
-    assert excinfo.value.field == {User.email}
+        client.create_project(name="Project name", media_type=MediaType.Image)
 
 
 @pytest.mark.skip("timeouts cause failure before rate limit")
diff --git a/libs/labelbox/tests/integration/test_filtering.py b/libs/labelbox/tests/integration/test_filtering.py
index cb6f11baa..bba483b19 100644
--- a/libs/labelbox/tests/integration/test_filtering.py
+++ b/libs/labelbox/tests/integration/test_filtering.py
@@ -2,7 +2,7 @@
 from lbox.exceptions import InvalidQueryError
 
 from labelbox import Project
-from labelbox.schema.queue_mode import QueueMode
+from labelbox.schema.media_type import MediaType
 
 
 @pytest.fixture
@@ -11,9 +11,9 @@ def project_to_test_where(client, rand_gen):
     p_b_name = f"b-{rand_gen(str)}"
     p_c_name = f"c-{rand_gen(str)}"
 
-    p_a = client.create_project(name=p_a_name, queue_mode=QueueMode.Batch)
-    p_b = client.create_project(name=p_b_name, queue_mode=QueueMode.Batch)
-    p_c = client.create_project(name=p_c_name, queue_mode=QueueMode.Batch)
+    p_a = client.create_project(name=p_a_name, media_type=MediaType.Image)
+    p_b = client.create_project(name=p_b_name, media_type=MediaType.Image)
+    p_c = client.create_project(name=p_c_name, media_type=MediaType.Image)
 
     yield p_a, p_b, p_c
 
diff --git a/libs/labelbox/tests/integration/test_legacy_project.py b/libs/labelbox/tests/integration/test_legacy_project.py
index 320a2191d..3e652f333 100644
--- a/libs/labelbox/tests/integration/test_legacy_project.py
+++ b/libs/labelbox/tests/integration/test_legacy_project.py
@@ -1,40 +1,13 @@
-import pytest
-
-from labelbox.schema.queue_mode import QueueMode
-
-
-def test_project_dataset(client, rand_gen):
-    with pytest.raises(
-        ValueError,
-        match="Dataset queue mode is deprecated. Please prefer Batch queue mode.",
-    ):
-        client.create_project(
-            name=rand_gen(str),
-            queue_mode=QueueMode.Dataset,
-        )
+from os import name
 
+import pytest
+from pydantic import ValidationError
 
-def test_project_auto_audit_parameters(client, rand_gen):
-    with pytest.raises(
-        ValueError,
-        match="quality_modes must be set instead of auto_audit_percentage or auto_audit_number_of_labels.",
-    ):
-        client.create_project(name=rand_gen(str), auto_audit_percentage=0.5)
-
-    with pytest.raises(
-        ValueError,
-        match="quality_modes must be set instead of auto_audit_percentage or auto_audit_number_of_labels.",
-    ):
-        client.create_project(name=rand_gen(str), auto_audit_number_of_labels=2)
+from labelbox.schema.media_type import MediaType
 
 
 def test_project_name_parameter(client, rand_gen):
     with pytest.raises(
-        ValueError, match="project name must be a valid string."
-    ):
-        client.create_project()
-
-    with pytest.raises(
-        ValueError, match="project name must be a valid string."
+        ValidationError, match="project name must be a valid string"
     ):
-        client.create_project(name="     ")
+        client.create_project(name="     ", media_type=MediaType.Image)
diff --git a/libs/labelbox/tests/integration/test_ontology.py b/libs/labelbox/tests/integration/test_ontology.py
index bf70536d0..c7c7c270c 100644
--- a/libs/labelbox/tests/integration/test_ontology.py
+++ b/libs/labelbox/tests/integration/test_ontology.py
@@ -1,11 +1,10 @@
-import pytest
-
-from labelbox import OntologyBuilder, MediaType, Tool
-from labelbox.orm.model import Entity
 import json
 import time
 
-from labelbox.schema.queue_mode import QueueMode
+import pytest
+
+from labelbox import MediaType, OntologyBuilder, Tool
+from labelbox.orm.model import Entity
 
 
 def test_feature_schema_is_not_archived(client, ontology):
@@ -99,7 +98,6 @@ def test_deletes_an_ontology(client):
 def test_cant_delete_an_ontology_with_project(client):
     project = client.create_project(
         name="test project",
-        queue_mode=QueueMode.Batch,
         media_type=MediaType.Image,
     )
     tool = client.upsert_feature_schema(point.asdict())
@@ -187,7 +185,6 @@ def test_does_not_include_used_ontologies(client):
     )
     project = client.create_project(
         name="test project",
-        queue_mode=QueueMode.Batch,
         media_type=MediaType.Image,
     )
     project.connect_ontology(ontology_with_project)
diff --git a/libs/labelbox/tests/integration/test_project.py b/libs/labelbox/tests/integration/test_project.py
index 6f0f74e35..12046eadd 100644
--- a/libs/labelbox/tests/integration/test_project.py
+++ b/libs/labelbox/tests/integration/test_project.py
@@ -7,16 +7,15 @@
 from lbox.exceptions import InvalidQueryError
 
 from labelbox import Dataset, LabelingFrontend, Project
+from labelbox.schema import media_type
 from labelbox.schema.media_type import MediaType
 from labelbox.schema.quality_mode import QualityMode
-from labelbox.schema.queue_mode import QueueMode
 
 
 def test_project(client, rand_gen):
     data = {
         "name": rand_gen(str),
         "description": rand_gen(str),
-        "queue_mode": QueueMode.Batch.Batch,
         "media_type": MediaType.Image,
     }
     project = client.create_project(**data)
@@ -51,7 +50,7 @@ def data_for_project_test(client, rand_gen):
     def _create_project(name: str = None):
         if name is None:
             name = rand_gen(str)
-        project = client.create_project(name=name)
+        project = client.create_project(name=name, media_type=MediaType.Image)
         projects.append(project)
         return project
 
@@ -140,10 +139,6 @@ def test_extend_reservations(project):
         project.extend_reservations("InvalidQueueType")
 
 
-@pytest.mark.skipif(
-    condition=os.environ["LABELBOX_TEST_ENVIRON"] == "onprem",
-    reason="new mutation does not work for onprem",
-)
 def test_attach_instructions(client, project):
     with pytest.raises(ValueError) as execinfo:
         project.upsert_instructions("tests/integration/media/sample_pdf.pdf")
@@ -248,9 +243,11 @@ def test_media_type(client, project: Project, rand_gen):
     assert isinstance(project.media_type, MediaType)
 
     # Update test
-    project = client.create_project(name=rand_gen(str))
-    project.update(media_type=MediaType.Image)
-    assert project.media_type == MediaType.Image
+    project = client.create_project(
+        name=rand_gen(str), media_type=MediaType.Image
+    )
+    project.update(media_type=MediaType.Text)
+    assert project.media_type == MediaType.Text
     project.delete()
 
     for media_type in MediaType.get_supported_members():
@@ -271,13 +268,16 @@ def test_media_type(client, project: Project, rand_gen):
 
 def test_queue_mode(client, rand_gen):
     project = client.create_project(
-        name=rand_gen(str)
+        name=rand_gen(str),
+        media_type=MediaType.Image,
     )  # defaults to benchmark and consensus
     assert project.auto_audit_number_of_labels == 3
     assert project.auto_audit_percentage == 0
 
     project = client.create_project(
-        name=rand_gen(str), quality_modes=[QualityMode.Benchmark]
+        name=rand_gen(str),
+        quality_modes=[QualityMode.Benchmark],
+        media_type=MediaType.Image,
     )
     assert project.auto_audit_number_of_labels == 1
     assert project.auto_audit_percentage == 1
@@ -285,13 +285,16 @@ def test_queue_mode(client, rand_gen):
     project = client.create_project(
         name=rand_gen(str),
         quality_modes=[QualityMode.Benchmark, QualityMode.Consensus],
+        media_type=MediaType.Image,
     )
     assert project.auto_audit_number_of_labels == 3
     assert project.auto_audit_percentage == 0
 
 
 def test_label_count(client, configured_batch_project_with_label):
-    project = client.create_project(name="test label count")
+    project = client.create_project(
+        name="test label count", media_type=MediaType.Image
+    )
     assert project.get_label_count() == 0
     project.delete()
 
diff --git a/libs/labelbox/tests/unit/schema/test_user_group.py b/libs/labelbox/tests/unit/schema/test_user_group.py
index 4d78f096e..1df555a64 100644
--- a/libs/labelbox/tests/unit/schema/test_user_group.py
+++ b/libs/labelbox/tests/unit/schema/test_user_group.py
@@ -57,12 +57,6 @@ def setup_method(self):
         self.client.enable_experimental = True
         self.group = UserGroup(client=self.client)
 
-    def test_constructor_experimental_needed(self):
-        client = MagicMock(Client)
-        client.enable_experimental = False
-        with pytest.raises(RuntimeError):
-            group = UserGroup(client)
-
     def test_constructor(self):
         group = UserGroup(self.client)
 
diff --git a/pyproject.toml b/pyproject.toml
index ebce059f5..1a4f19e04 100644
--- a/pyproject.toml
+++ b/pyproject.toml
@@ -28,6 +28,7 @@ dev-dependencies = [
     "pytest-timestamper>=0.0.10",
     "pytest-timeout>=2.3.1",
     "pytest-order>=1.2.1",
+    "pyjwt>=2.9.0",
 ]
 
 [tool.rye.workspace]
@@ -35,7 +36,7 @@ members = ["libs/*", "examples"]
 
 [tool.pytest.ini_options]
 # https://github.com/pytest-dev/pytest-rerunfailures/issues/99
-addopts = "-rP -vvv --reruns 1 --reruns-delay 5 --durations=20 -n auto --cov=labelbox --import-mode=importlib --order-group-scope=module"
+addopts = "-rP -vvv"
 markers = """
     slow: marks tests as slow (deselect with '-m "not slow"')
 """
diff --git a/requirements-dev.lock b/requirements-dev.lock
index a51fa0dcf..fcca5b15d 100644
--- a/requirements-dev.lock
+++ b/requirements-dev.lock
@@ -200,6 +200,7 @@ pygments==2.18.0
     # via nbconvert
     # via rich
     # via sphinx
+pyjwt==2.9.0
 pyproj==3.5.0
     # via labelbox
 pytest==8.2.2
diff --git a/requirements.lock b/requirements.lock
index 16ed91c80..3f32f3286 100644
--- a/requirements.lock
+++ b/requirements.lock
@@ -50,6 +50,10 @@ jinja2==3.1.4
     # via sphinx
 markupsafe==2.1.5
     # via jinja2
+mypy==1.10.1
+    # via labelbox
+mypy-extensions==1.0.0
+    # via mypy
 numpy==1.24.4
     # via labelbox
     # via opencv-python-headless
@@ -119,6 +123,8 @@ sphinxcontrib-serializinghtml==1.1.5
     # via sphinx
 strenum==0.4.15
     # via labelbox
+tomli==2.0.1
+    # via mypy
 tqdm==4.66.4
     # via labelbox
 typeguard==4.3.0
@@ -126,6 +132,7 @@ typeguard==4.3.0
 typing-extensions==4.12.2
     # via annotated-types
     # via labelbox
+    # via mypy
     # via pydantic
     # via pydantic-core
     # via typeguard