diff --git a/common/chat.cpp b/common/chat.cpp
index 114dbfccdbfe7..a21d09bb1da3a 100644
--- a/common/chat.cpp
+++ b/common/chat.cpp
@@ -1727,7 +1727,8 @@ static common_chat_params common_chat_templates_apply_jinja(
         : *tmpls->template_default;
     const auto & src = tmpl.source();
     const auto & caps = tmpl.original_caps();
-    params.messages = common_chat_msgs_to_json_oaicompat<json>(inputs.messages, /* concat_text= */ !tmpl.original_caps().requires_typed_content);
+    bool concat_text = !inputs.no_part_concat && !tmpl.original_caps().requires_typed_content;
+    params.messages = common_chat_msgs_to_json_oaicompat<json>(inputs.messages, concat_text);
     params.add_generation_prompt = inputs.add_generation_prompt;
     params.tool_choice = inputs.tool_choice;
     params.enable_thinking = inputs.enable_thinking;
diff --git a/common/chat.h b/common/chat.h
index ca807c145ee82..dc8510da20b7d 100644
--- a/common/chat.h
+++ b/common/chat.h
@@ -127,6 +127,9 @@ struct common_chat_templates_inputs {
     bool enable_thinking = true;
     std::chrono::system_clock::time_point now = std::chrono::system_clock::now();
     std::map<std::string, std::string> chat_template_kwargs;
+
+    //If true, the jinja won't concat content parts into single part. That's useful for media parts
+    bool no_part_concat = false;
 };
 
 struct common_chat_params {
diff --git a/include/llama.h b/include/llama.h
index db6a5337b02a7..581b7048085c1 100644
--- a/include/llama.h
+++ b/include/llama.h
@@ -1021,6 +1021,9 @@ extern "C" {
     LLAMA_API llama_token llama_vocab_fim_rep(const struct llama_vocab * vocab);
     LLAMA_API llama_token llama_vocab_fim_sep(const struct llama_vocab * vocab);
 
+    LLAMA_API llama_token llama_vocab_image_token(const struct llama_vocab * vocab);
+    LLAMA_API llama_token llama_vocab_audio_token(const struct llama_vocab * vocab);
+
     DEPRECATED(LLAMA_API const char * llama_token_get_text(const struct llama_vocab * vocab, llama_token token), "use llama_vocab_get_text instead");
     DEPRECATED(LLAMA_API float llama_token_get_score(const struct llama_vocab * vocab, llama_token token), "use llama_vocab_get_score instead");
     DEPRECATED(LLAMA_API enum llama_token_attr llama_token_get_attr(const struct llama_vocab * vocab, llama_token token), "use llama_vocab_get_attr instead");
diff --git a/src/llama-arch.cpp b/src/llama-arch.cpp
index 9454d04e53801..6d42b3d84d521 100644
--- a/src/llama-arch.cpp
+++ b/src/llama-arch.cpp
@@ -224,6 +224,8 @@ static const std::map<llm_kv, const char *> LLM_KV_NAMES = {
     { LLM_KV_TOKENIZER_FIM_PAD_ID,           "tokenizer.ggml.fim_pad_token_id"         },
     { LLM_KV_TOKENIZER_FIM_REP_ID,           "tokenizer.ggml.fim_rep_token_id"         },
     { LLM_KV_TOKENIZER_FIM_SEP_ID,           "tokenizer.ggml.fim_sep_token_id"         },
+    {LLM_KV_TOKENIZER_IMAGE_ID,              "tokenizer.ggml.image_token_id"           },
+    {LLM_KV_TOKENIZER_AUDIO_ID,              "tokenizer.ggml.audio_token_id"           },
 
     { LLM_KV_ADAPTER_TYPE,       "adapter.type"       },
     { LLM_KV_ADAPTER_LORA_ALPHA, "adapter.lora.alpha" },
diff --git a/src/llama-arch.h b/src/llama-arch.h
index 0ead0d6cdb11b..13284c1b40eb1 100644
--- a/src/llama-arch.h
+++ b/src/llama-arch.h
@@ -230,8 +230,13 @@ enum llm_kv {
 
     LLM_KV_CLASSIFIER_OUTPUT_LABELS,
 
+
+    LLM_KV_TOKENIZER_IMAGE_ID,
+    LLM_KV_TOKENIZER_AUDIO_ID,
+
     LLM_KV_SHORTCONV_L_CACHE,
 
+
     // deprecated:
     LLM_KV_TOKENIZER_PREFIX_ID,
     LLM_KV_TOKENIZER_SUFFIX_ID,
diff --git a/src/llama-vocab.cpp b/src/llama-vocab.cpp
index 2181c01e31a87..8db8a2782a971 100644
--- a/src/llama-vocab.cpp
+++ b/src/llama-vocab.cpp
@@ -1551,6 +1551,8 @@ struct llama_vocab::impl {
     llama_token special_fim_pad_id = LLAMA_TOKEN_NULL;
     llama_token special_fim_rep_id = LLAMA_TOKEN_NULL; // repo
     llama_token special_fim_sep_id = LLAMA_TOKEN_NULL; // file separator
+    llama_token special_image_id = LLAMA_TOKEN_NULL;
+    llama_token special_audio_id = LLAMA_TOKEN_NULL;
 
     // tokenizer flags
     bool add_space_prefix           = false;
@@ -1999,6 +2001,14 @@ void llama_vocab::impl::load(llama_model_loader & ml, const LLM_KV & kv) {
         ml.get_key(LLM_KV_TOKENIZER_REMOVE_EXTRA_WS, remove_extra_whitespaces, false);
     }
 
+    const int image_idx = gguf_find_key(ctx,kv(LLM_KV_TOKENIZER_IMAGE_ID).c_str());
+    if (image_idx != -1) {
+        special_image_id=gguf_get_val_u32(ctx,image_idx);
+    }
+    const int audio_idx = gguf_find_key(ctx,kv(LLM_KV_TOKENIZER_AUDIO_ID).c_str());
+    if (audio_idx != -1) {
+        special_audio_id=gguf_get_val_u32(ctx,audio_idx);
+    }
     const int token_idx = gguf_find_key(ctx, kv(LLM_KV_TOKENIZER_LIST).c_str());
     if (token_idx == -1) {
         throw std::runtime_error("cannot find tokenizer vocab in model file\n");
@@ -2034,6 +2044,7 @@ void llama_vocab::impl::load(llama_model_loader & ml, const LLM_KV & kv) {
         token_data.score = scores ? scores[i] : 0.0f;
         token_data.attr  = LLAMA_TOKEN_ATTR_NORMAL;
 
+
         if (toktypes) {  //TODO: remove, required until per token attributes are available from GGUF file
             switch(toktypes[i]) {
                 case LLAMA_TOKEN_TYPE_UNKNOWN:      token_data.attr = LLAMA_TOKEN_ATTR_UNKNOWN;      break;
@@ -2094,6 +2105,8 @@ void llama_vocab::impl::load(llama_model_loader & ml, const LLM_KV & kv) {
             { LLM_KV_TOKENIZER_FIM_PAD_ID, special_fim_pad_id },
             { LLM_KV_TOKENIZER_FIM_REP_ID, special_fim_rep_id },
             { LLM_KV_TOKENIZER_FIM_SEP_ID, special_fim_sep_id },
+            { LLM_KV_TOKENIZER_IMAGE_ID, special_image_id },
+            { LLM_KV_TOKENIZER_AUDIO_ID, special_audio_id },
 
             // deprecated
             { LLM_KV_TOKENIZER_PREFIX_ID, special_fim_pre_id },
@@ -2172,6 +2185,16 @@ void llama_vocab::impl::load(llama_model_loader & ml, const LLM_KV & kv) {
                     }
                 }
             }
+            if (special_image_id==LLAMA_TOKEN_NULL) {
+                if (t.first=="<|IMAGE|>" || t.first=="<IMAGE>") {
+                    special_image_id=t.second;
+                }
+            }
+            if (special_audio_id==LLAMA_TOKEN_NULL) {
+                if (t.first=="<|AUDIO|>" || t.first=="<AUDIO>") {
+                    special_audio_id=t.second;
+                }
+            }
 
             // find FIM_PRE token: "<|fim_prefix|>", "<fim-prefix>", "<PRE>", etc.
             if (special_fim_pre_id == LLAMA_TOKEN_NULL) {
@@ -3354,6 +3377,15 @@ llama_token llama_vocab::token_fim_sep() const {
     return pimpl->special_fim_sep_id;
 }
 
+
+llama_token llama_vocab::token_image() const {
+    return pimpl->special_image_id;
+}
+
+llama_token llama_vocab::token_audio() const {
+    return pimpl->special_audio_id;
+}
+
 llama_token llama_vocab::token_mask() const {
     return pimpl->special_mask_id;
 }
@@ -3598,6 +3630,14 @@ llama_token llama_vocab_fim_sep(const struct llama_vocab * vocab) {
     return vocab->token_fim_sep();
 }
 
+llama_token llama_vocab_image_token(const struct llama_vocab * vocab) {
+    return vocab->token_image();
+}
+
+llama_token llama_vocab_audio_token(const struct llama_vocab * vocab) {
+    return vocab->token_audio();
+}
+
 llama_token llama_vocab_mask(const struct llama_vocab* vocab) {
     return vocab->token_mask();
 }
diff --git a/src/llama-vocab.h b/src/llama-vocab.h
index 842b129e86171..9b6a932993fda 100644
--- a/src/llama-vocab.h
+++ b/src/llama-vocab.h
@@ -114,6 +114,8 @@ struct llama_vocab {
     llama_token token_fim_rep() const;
     llama_token token_fim_sep() const;
 
+    llama_token token_image() const;
+    llama_token token_audio() const;
     bool get_add_space_prefix          () const;
     bool get_add_bos                   () const;
     bool get_add_eos                   () const;
diff --git a/tools/mtmd/clip.cpp b/tools/mtmd/clip.cpp
index 9146c9e9c4481..74ab2539e2900 100644
--- a/tools/mtmd/clip.cpp
+++ b/tools/mtmd/clip.cpp
@@ -164,7 +164,7 @@ enum patch_merge_type {
 
 struct clip_hparams {
     int32_t image_size;
-    int32_t patch_size;
+    int32_t patch_size=INT_MAX;
     int32_t n_embd;
     int32_t n_ff;
     int32_t projection_dim;
diff --git a/tools/mtmd/mtmd-cli.cpp b/tools/mtmd/mtmd-cli.cpp
index 599e682e0f894..2194c89f8cfc0 100644
--- a/tools/mtmd/mtmd-cli.cpp
+++ b/tools/mtmd/mtmd-cli.cpp
@@ -160,8 +160,9 @@ struct mtmd_cli_context {
     }
 };
 
-static int generate_response(mtmd_cli_context & ctx, int n_predict) {
+static std::string generate_response(mtmd_cli_context & ctx, int n_predict) {
     llama_tokens generated_tokens;
+    std::string response = "";
     for (int i = 0; i < n_predict; i++) {
         if (i > n_predict || !g_is_generating || g_is_interrupted) {
             LOG("\n");
@@ -176,8 +177,9 @@ static int generate_response(mtmd_cli_context & ctx, int n_predict) {
             LOG("\n");
             break; // end of generation
         }
-
-        LOG("%s", common_token_to_piece(ctx.lctx, token_id).c_str());
+        std::string piece=common_token_to_piece(ctx.lctx, token_id);
+        LOG("%s", piece.c_str());
+        response += piece;
         fflush(stdout);
 
         if (g_is_interrupted) {
@@ -190,17 +192,18 @@ static int generate_response(mtmd_cli_context & ctx, int n_predict) {
         common_batch_add(ctx.batch, token_id, ctx.n_past++, {0}, true);
         if (llama_decode(ctx.lctx, ctx.batch)) {
             LOG_ERR("failed to decode token\n");
-            return 1;
+            return "";
         }
     }
-    return 0;
+    return response;
 }
 
-static int eval_message(mtmd_cli_context & ctx, common_chat_msg & msg, bool add_bos = false) {
+static int eval_message(mtmd_cli_context & ctx, const std::vector<common_chat_msg> & messages, bool add_bos = false) {
     common_chat_templates_inputs tmpl_inputs;
-    tmpl_inputs.messages = {msg};
+    tmpl_inputs.messages = messages;
     tmpl_inputs.add_generation_prompt = true;
-    tmpl_inputs.use_jinja = false; // jinja is buggy here
+    tmpl_inputs.no_part_concat=true;
+    tmpl_inputs.use_jinja = true; // jinja is bughigy here
     auto formatted_chat = common_chat_templates_apply(ctx.tmpls.get(), tmpl_inputs);
     LOG_DBG("formatted_chat.prompt: %s\n", formatted_chat.prompt.c_str());
 
@@ -303,10 +306,10 @@ int main(int argc, char ** argv) {
                 return 1; // error is already printed by libmtmd
             }
         }
-        if (eval_message(ctx, msg, true)) {
+        if (eval_message(ctx,{msg} , true)) {
             return 1;
         }
-        if (!g_is_interrupted && generate_response(ctx, n_predict)) {
+        if (!g_is_interrupted && generate_response(ctx, n_predict).empty()) {
             return 1;
         }
 
@@ -324,7 +327,7 @@ int main(int argc, char ** argv) {
 
         bool is_first_msg = true;
         std::string content;
-
+        std::vector<common_chat_msg> messages;
         while (!g_is_interrupted) {
             g_is_generating = false;
             LOG("\n> ");
@@ -357,24 +360,31 @@ int main(int argc, char ** argv) {
                 std::string media_path = line.substr(7);
                 if (ctx.load_media(media_path)) {
                     LOG("%s %s loaded\n", media_path.c_str(), is_image ? "image" : "audio");
-                    content += mtmd_default_marker();
+                    //content += mtmd_default_marker();
+                    common_chat_msg msg;
+                    msg.content_parts.push_back({"image",""});
+                    messages.push_back(std::move(msg));
                 }
                 // else, error is already printed by libmtmd
                 continue;
-            } else {
-                content += line;
             }
             common_chat_msg msg;
             msg.role = "user";
-            msg.content = content;
-            int ret = eval_message(ctx, msg, is_first_msg);
+            msg.content = line;
+            messages.push_back(std::move(msg));
+            int ret = eval_message(ctx, messages, is_first_msg);
             if (ret) {
                 return 1;
             }
             if (g_is_interrupted) break;
-            if (generate_response(ctx, n_predict)) {
+            auto response=generate_response(ctx, n_predict);
+            if (response.empty()) {
                 return 1;
             }
+            common_chat_msg response_message;
+            response_message.role = "assistant";
+            response_message.content = response;
+            messages.push_back(response_message);
             content.clear();
             is_first_msg = false;
         }
diff --git a/tools/mtmd/mtmd.cpp b/tools/mtmd/mtmd.cpp
index e3829738338c3..c8a5c0ded8969 100644
--- a/tools/mtmd/mtmd.cpp
+++ b/tools/mtmd/mtmd.cpp
@@ -254,8 +254,10 @@ struct mtmd_context {
 
         } else if (proj == PROJECTOR_TYPE_QWEN2VL || proj == PROJECTOR_TYPE_QWEN25VL) {
             // <|vision_start|> ... (image embeddings) ... <|vision_end|>
-            img_beg = "<|vision_start|>";
-            img_end = "<|vision_end|>";
+            //There is a valid reason why they are commented here. QWENVL and Qwen Omni has their own tokens for image.\
+            // The jinja produce something like that <|vision_bos|><|IMAGE|><|vision_eos|>.
+            // img_beg = "<|vision_start|>";
+            // img_end = "<|vision_end|>";
 
         } else if (proj == PROJECTOR_TYPE_LLAMA4) {
             // (more details in mtmd_context constructor)
@@ -385,10 +387,21 @@ struct mtmd_tokenizer {
 
     int32_t tokenize(mtmd_input_chunks * output) {
         cur.entries.clear();
-        std::vector<std::string> parts = split_text(input_text, ctx->media_marker);
+
         size_t i_bm = 0; // index of the current bitmap
+        llama_token imageTokenID =llama_vocab_image_token(vocab);
+        std::string imageToken;
+        std::vector<std::string> delimiters;
+        delimiters.push_back(ctx->media_marker);
+
+        if (imageTokenID!=LLAMA_TOKEN_NULL) {
+            imageToken = llama_vocab_get_text(vocab,imageTokenID);
+            delimiters.push_back(imageToken);
+        }
+
+        std::vector<std::string> parts = split_text_multi(input_text, delimiters);
         for (auto & part : parts) {
-            if (part == ctx->media_marker) {
+            if (part == ctx->media_marker || part==imageToken) {
                 // this is a marker, we should add the next bitmap
                 if (i_bm >= bitmaps.size()) {
                     LOG_ERR("%s: error: number of bitmaps (%zu) does not match number of markers (%zu)\n",
@@ -707,6 +720,51 @@ struct mtmd_tokenizer {
         return result;
     }
 
+    static std::vector<std::string> split_text_multi(const std::string& input,
+                                                const std::vector<std::string>& delimiters) {
+        std::vector<std::string> result;
+        if (input.empty()) {
+            return result;
+        }
+
+        size_t pos = 0;
+        while (pos < input.length()) {
+            // Find the earliest occurring delimiter
+            size_t best_match_pos = std::string::npos;
+            std::string best_delimiter;
+
+            for (const auto& delimiter : delimiters) {
+                size_t match_pos = input.find(delimiter, pos);
+                if (match_pos != std::string::npos &&
+                    (best_match_pos == std::string::npos || match_pos < best_match_pos)) {
+                    best_match_pos = match_pos;
+                    best_delimiter = delimiter;
+                    }
+            }
+
+            if (best_match_pos == std::string::npos) {
+                // No more delimiters found, add remaining text
+                if (pos < input.length()) {
+                    result.push_back(input.substr(pos));
+                }
+                break;
+            }
+
+            // Add text before delimiter (if any)
+            if (best_match_pos > pos) {
+                result.push_back(input.substr(pos, best_match_pos - pos));
+            }
+
+            // Add the delimiter itself
+            result.push_back(best_delimiter);
+
+            // Move past the delimiter
+            pos = best_match_pos + best_delimiter.length();
+        }
+
+        return result;
+    }
+
     // copied from common_tokenize
     static std::vector<llama_token> mtmd_tokenize_text_internal(
         const struct llama_vocab * vocab,