diff --git a/src/llama_stack/core/datatypes.py b/src/llama_stack/core/datatypes.py
index 1e29690ff..49747d477 100644
--- a/src/llama_stack/core/datatypes.py
+++ b/src/llama_stack/core/datatypes.py
@@ -376,6 +376,14 @@ class VectorStoresConfig(BaseModel):
         default=None,
         description="Default embedding model configuration for vector stores.",
     )
+    default_query_expansion_model: QualifiedModel | None = Field(
+        default=None,
+        description="Default LLM model for query expansion/rewriting in vector search.",
+    )
+    query_expansion_prompt: str = Field(
+        default="Expand this query with relevant synonyms and related terms. Return only the improved query, no explanations:\n\n{query}\n\nImproved query:",
+        description="Prompt template for query expansion. Use {query} as placeholder for the original query.",
+    )
 
 
 class SafetyConfig(BaseModel):
diff --git a/src/llama_stack/core/routers/vector_io.py b/src/llama_stack/core/routers/vector_io.py
index 5256dda44..a7b30642c 100644
--- a/src/llama_stack/core/routers/vector_io.py
+++ b/src/llama_stack/core/routers/vector_io.py
@@ -99,6 +99,12 @@ class VectorIORouter(VectorIO):
     ) -> QueryChunksResponse:
         logger.debug(f"VectorIORouter.query_chunks: {vector_store_id}")
         provider = await self.routing_table.get_provider_impl(vector_store_id)
+
+        # Ensure params dict exists and add vector_stores_config for query rewriting
+        if params is None:
+            params = {}
+        params["vector_stores_config"] = self.vector_stores_config
+
         return await provider.query_chunks(vector_store_id, query, params)
 
     # OpenAI Vector Stores API endpoints
diff --git a/src/llama_stack/distributions/ci-tests/run-with-postgres-store.yaml b/src/llama_stack/distributions/ci-tests/run-with-postgres-store.yaml
index 7721138c7..8110dbdf6 100644
--- a/src/llama_stack/distributions/ci-tests/run-with-postgres-store.yaml
+++ b/src/llama_stack/distributions/ci-tests/run-with-postgres-store.yaml
@@ -288,5 +288,13 @@ vector_stores:
   default_embedding_model:
     provider_id: sentence-transformers
     model_id: nomic-ai/nomic-embed-text-v1.5
+  query_expansion_prompt: 'Expand this query with relevant synonyms and related terms.
+    Return only the improved query, no explanations:
+
+
+    {query}
+
+
+    Improved query:'
 safety:
   default_shield_id: llama-guard
diff --git a/src/llama_stack/distributions/ci-tests/run.yaml b/src/llama_stack/distributions/ci-tests/run.yaml
index b791e1488..809b0ef1c 100644
--- a/src/llama_stack/distributions/ci-tests/run.yaml
+++ b/src/llama_stack/distributions/ci-tests/run.yaml
@@ -279,5 +279,13 @@ vector_stores:
   default_embedding_model:
     provider_id: sentence-transformers
     model_id: nomic-ai/nomic-embed-text-v1.5
+  query_expansion_prompt: 'Expand this query with relevant synonyms and related terms.
+    Return only the improved query, no explanations:
+
+
+    {query}
+
+
+    Improved query:'
 safety:
   default_shield_id: llama-guard
diff --git a/src/llama_stack/distributions/starter-gpu/run-with-postgres-store.yaml b/src/llama_stack/distributions/starter-gpu/run-with-postgres-store.yaml
index 9c250c05a..ca47d7f4c 100644
--- a/src/llama_stack/distributions/starter-gpu/run-with-postgres-store.yaml
+++ b/src/llama_stack/distributions/starter-gpu/run-with-postgres-store.yaml
@@ -291,5 +291,13 @@ vector_stores:
   default_embedding_model:
     provider_id: sentence-transformers
     model_id: nomic-ai/nomic-embed-text-v1.5
+  query_expansion_prompt: 'Expand this query with relevant synonyms and related terms.
+    Return only the improved query, no explanations:
+
+
+    {query}
+
+
+    Improved query:'
 safety:
   default_shield_id: llama-guard
diff --git a/src/llama_stack/distributions/starter-gpu/run.yaml b/src/llama_stack/distributions/starter-gpu/run.yaml
index 65f9ae326..15555c262 100644
--- a/src/llama_stack/distributions/starter-gpu/run.yaml
+++ b/src/llama_stack/distributions/starter-gpu/run.yaml
@@ -282,5 +282,13 @@ vector_stores:
   default_embedding_model:
     provider_id: sentence-transformers
     model_id: nomic-ai/nomic-embed-text-v1.5
+  query_expansion_prompt: 'Expand this query with relevant synonyms and related terms.
+    Return only the improved query, no explanations:
+
+
+    {query}
+
+
+    Improved query:'
 safety:
   default_shield_id: llama-guard
diff --git a/src/llama_stack/distributions/starter/run-with-postgres-store.yaml b/src/llama_stack/distributions/starter/run-with-postgres-store.yaml
index 3314bb9e9..423b30452 100644
--- a/src/llama_stack/distributions/starter/run-with-postgres-store.yaml
+++ b/src/llama_stack/distributions/starter/run-with-postgres-store.yaml
@@ -288,5 +288,13 @@ vector_stores:
   default_embedding_model:
     provider_id: sentence-transformers
     model_id: nomic-ai/nomic-embed-text-v1.5
+  query_expansion_prompt: 'Expand this query with relevant synonyms and related terms.
+    Return only the improved query, no explanations:
+
+
+    {query}
+
+
+    Improved query:'
 safety:
   default_shield_id: llama-guard
diff --git a/src/llama_stack/distributions/starter/run.yaml b/src/llama_stack/distributions/starter/run.yaml
index e88539e6a..a0f56fc42 100644
--- a/src/llama_stack/distributions/starter/run.yaml
+++ b/src/llama_stack/distributions/starter/run.yaml
@@ -279,5 +279,13 @@ vector_stores:
   default_embedding_model:
     provider_id: sentence-transformers
     model_id: nomic-ai/nomic-embed-text-v1.5
+  query_expansion_prompt: 'Expand this query with relevant synonyms and related terms.
+    Return only the improved query, no explanations:
+
+
+    {query}
+
+
+    Improved query:'
 safety:
   default_shield_id: llama-guard
diff --git a/src/llama_stack/providers/utils/memory/openai_vector_store_mixin.py b/src/llama_stack/providers/utils/memory/openai_vector_store_mixin.py
index bbfd60e25..f33bb29c8 100644
--- a/src/llama_stack/providers/utils/memory/openai_vector_store_mixin.py
+++ b/src/llama_stack/providers/utils/memory/openai_vector_store_mixin.py
@@ -611,6 +611,7 @@ class OpenAIVectorStoreMixin(ABC):
                 "max_chunks": max_num_results * CHUNK_MULTIPLIER,
                 "score_threshold": score_threshold,
                 "mode": search_mode,
+                "rewrite_query": rewrite_query,
             }
             # TODO: Add support for ranking_options.ranker
 
diff --git a/src/llama_stack/providers/utils/memory/vector_store.py b/src/llama_stack/providers/utils/memory/vector_store.py
index b6a671ddb..6fbf4a424 100644
--- a/src/llama_stack/providers/utils/memory/vector_store.py
+++ b/src/llama_stack/providers/utils/memory/vector_store.py
@@ -17,6 +17,7 @@ import numpy as np
 from numpy.typing import NDArray
 from pydantic import BaseModel
 
+from llama_stack.core.datatypes import VectorStoresConfig
 from llama_stack.log import get_logger
 from llama_stack.models.llama.llama3.tokenizer import Tokenizer
 from llama_stack.providers.utils.inference.prompt_adapter import (
@@ -34,6 +35,11 @@ from llama_stack_api import (
     RAGDocument,
     VectorStore,
 )
+from llama_stack_api.inference import (
+    OpenAIChatCompletionRequestWithExtraBody,
+    OpenAIUserMessageParam,
+)
+from llama_stack_api.models import ModelType
 
 log = get_logger(name=__name__, category="providers::utils")
 
@@ -262,6 +268,7 @@ class VectorStoreWithIndex:
     vector_store: VectorStore
     index: EmbeddingIndex
     inference_api: Api.inference
+    vector_stores_config: VectorStoresConfig | None = None
 
     async def insert_chunks(
         self,
@@ -296,6 +303,11 @@ class VectorStoreWithIndex:
     ) -> QueryChunksResponse:
         if params is None:
             params = {}
+
+        # Extract configuration if provided by router
+        if "vector_stores_config" in params:
+            self.vector_stores_config = params["vector_stores_config"]
+
         k = params.get("max_chunks", 3)
         mode = params.get("mode")
         score_threshold = params.get("score_threshold", 0.0)
@@ -318,6 +330,11 @@ class VectorStoreWithIndex:
                 reranker_params = {"impact_factor": k_value}
 
         query_string = interleaved_content_as_str(query)
+
+        # Apply query rewriting if enabled
+        if params.get("rewrite_query", False):
+            query_string = await self._rewrite_query_for_search(query_string)
+
         if mode == "keyword":
             return await self.index.query_keyword(query_string, k, score_threshold)
 
@@ -333,3 +350,67 @@ class VectorStoreWithIndex:
             )
         else:
             return await self.index.query_vector(query_vector, k, score_threshold)
+
+    async def _rewrite_query_for_search(self, query: str) -> str:
+        """Rewrite the user query to improve vector search performance.
+
+        :param query: The original user query
+        :returns: The rewritten query optimized for vector search
+        """
+        # Check if query expansion model is configured
+        if not self.vector_stores_config or not self.vector_stores_config.default_query_expansion_model:
+            raise ValueError("No default_query_expansion_model configured for query rewriting")
+
+        # Use the configured model
+        expansion_model = self.vector_stores_config.default_query_expansion_model
+        chat_model = f"{expansion_model.provider_id}/{expansion_model.model_id}"
+
+        # Validate that the model is available and is an LLM
+        try:
+            models_response = await self.inference_api.routing_table.list_models()
+        except Exception as e:
+            raise RuntimeError(f"Failed to list available models for validation: {e}") from e
+
+        model_found = False
+        for model in models_response.data:
+            if model.identifier == chat_model:
+                if model.model_type != ModelType.llm:
+                    raise ValueError(
+                        f"Configured query expansion model '{chat_model}' is not an LLM model "
+                        f"(found type: {model.model_type}). Query rewriting requires an LLM model."
+                    )
+                model_found = True
+                break
+
+        if not model_found:
+            available_llm_models = [m.identifier for m in models_response.data if m.model_type == ModelType.llm]
+            raise ValueError(
+                f"Configured query expansion model '{chat_model}' is not available. "
+                f"Available LLM models: {available_llm_models}"
+            )
+
+        # Use the configured prompt (has a default value)
+        rewrite_prompt = self.vector_stores_config.query_expansion_prompt.format(query=query)
+
+        chat_request = OpenAIChatCompletionRequestWithExtraBody(
+            model=chat_model,
+            messages=[
+                OpenAIUserMessageParam(
+                    role="user",
+                    content=rewrite_prompt,
+                )
+            ],
+            max_tokens=100,
+        )
+
+        try:
+            response = await self.inference_api.openai_chat_completion(chat_request)
+        except Exception as e:
+            raise RuntimeError(f"Failed to generate rewritten query: {e}") from e
+
+        if response.choices and len(response.choices) > 0:
+            rewritten_query = response.choices[0].message.content.strip()
+            log.info(f"Query rewritten: '{query}' → '{rewritten_query}'")
+            return rewritten_query
+        else:
+            raise RuntimeError("No response received from LLM model for query rewriting")
diff --git a/tests/integration/common/recordings/models-d98e7566147f9d534bc0461f2efe61e3f525c18360a07bb3dda397579e25c27b-a882f554.json b/tests/integration/common/recordings/models-d98e7566147f9d534bc0461f2efe61e3f525c18360a07bb3dda397579e25c27b-a882f554.json
new file mode 100644
index 000000000..c38561dbb
--- /dev/null
+++ b/tests/integration/common/recordings/models-d98e7566147f9d534bc0461f2efe61e3f525c18360a07bb3dda397579e25c27b-a882f554.json
@@ -0,0 +1,647 @@
+{
+  "test_id": null,
+  "request": {
+    "method": "POST",
+    "url": "https://generativelanguage.googleapis.com/v1beta/openai/v1/models",
+    "headers": {},
+    "body": {},
+    "endpoint": "/v1/models",
+    "model": ""
+  },
+  "response": {
+    "body": [
+      {
+        "__type__": "openai.types.model.Model",
+        "__data__": {
+          "id": "models/embedding-gecko-001",
+          "created": null,
+          "object": "model",
+          "owned_by": "google",
+          "display_name": "Embedding Gecko"
+        }
+      },
+      {
+        "__type__": "openai.types.model.Model",
+        "__data__": {
+          "id": "models/gemini-2.5-pro-preview-03-25",
+          "created": null,
+          "object": "model",
+          "owned_by": "google",
+          "display_name": "Gemini 2.5 Pro Preview 03-25"
+        }
+      },
+      {
+        "__type__": "openai.types.model.Model",
+        "__data__": {
+          "id": "models/gemini-2.5-flash-preview-05-20",
+          "created": null,
+          "object": "model",
+          "owned_by": "google",
+          "display_name": "Gemini 2.5 Flash Preview 05-20"
+        }
+      },
+      {
+        "__type__": "openai.types.model.Model",
+        "__data__": {
+          "id": "models/gemini-2.5-flash",
+          "created": null,
+          "object": "model",
+          "owned_by": "google",
+          "display_name": "Gemini 2.5 Flash"
+        }
+      },
+      {
+        "__type__": "openai.types.model.Model",
+        "__data__": {
+          "id": "models/gemini-2.5-flash-lite-preview-06-17",
+          "created": null,
+          "object": "model",
+          "owned_by": "google",
+          "display_name": "Gemini 2.5 Flash-Lite Preview 06-17"
+        }
+      },
+      {
+        "__type__": "openai.types.model.Model",
+        "__data__": {
+          "id": "models/gemini-2.5-pro-preview-05-06",
+          "created": null,
+          "object": "model",
+          "owned_by": "google",
+          "display_name": "Gemini 2.5 Pro Preview 05-06"
+        }
+      },
+      {
+        "__type__": "openai.types.model.Model",
+        "__data__": {
+          "id": "models/gemini-2.5-pro-preview-06-05",
+          "created": null,
+          "object": "model",
+          "owned_by": "google",
+          "display_name": "Gemini 2.5 Pro Preview"
+        }
+      },
+      {
+        "__type__": "openai.types.model.Model",
+        "__data__": {
+          "id": "models/gemini-2.5-pro",
+          "created": null,
+          "object": "model",
+          "owned_by": "google",
+          "display_name": "Gemini 2.5 Pro"
+        }
+      },
+      {
+        "__type__": "openai.types.model.Model",
+        "__data__": {
+          "id": "models/gemini-2.0-flash-exp",
+          "created": null,
+          "object": "model",
+          "owned_by": "google",
+          "display_name": "Gemini 2.0 Flash Experimental"
+        }
+      },
+      {
+        "__type__": "openai.types.model.Model",
+        "__data__": {
+          "id": "models/gemini-2.0-flash",
+          "created": null,
+          "object": "model",
+          "owned_by": "google",
+          "display_name": "Gemini 2.0 Flash"
+        }
+      },
+      {
+        "__type__": "openai.types.model.Model",
+        "__data__": {
+          "id": "models/gemini-2.0-flash-001",
+          "created": null,
+          "object": "model",
+          "owned_by": "google",
+          "display_name": "Gemini 2.0 Flash 001"
+        }
+      },
+      {
+        "__type__": "openai.types.model.Model",
+        "__data__": {
+          "id": "models/gemini-2.0-flash-exp-image-generation",
+          "created": null,
+          "object": "model",
+          "owned_by": "google",
+          "display_name": "Gemini 2.0 Flash (Image Generation) Experimental"
+        }
+      },
+      {
+        "__type__": "openai.types.model.Model",
+        "__data__": {
+          "id": "models/gemini-2.0-flash-lite-001",
+          "created": null,
+          "object": "model",
+          "owned_by": "google",
+          "display_name": "Gemini 2.0 Flash-Lite 001"
+        }
+      },
+      {
+        "__type__": "openai.types.model.Model",
+        "__data__": {
+          "id": "models/gemini-2.0-flash-lite",
+          "created": null,
+          "object": "model",
+          "owned_by": "google",
+          "display_name": "Gemini 2.0 Flash-Lite"
+        }
+      },
+      {
+        "__type__": "openai.types.model.Model",
+        "__data__": {
+          "id": "models/gemini-2.0-flash-lite-preview-02-05",
+          "created": null,
+          "object": "model",
+          "owned_by": "google",
+          "display_name": "Gemini 2.0 Flash-Lite Preview 02-05"
+        }
+      },
+      {
+        "__type__": "openai.types.model.Model",
+        "__data__": {
+          "id": "models/gemini-2.0-flash-lite-preview",
+          "created": null,
+          "object": "model",
+          "owned_by": "google",
+          "display_name": "Gemini 2.0 Flash-Lite Preview"
+        }
+      },
+      {
+        "__type__": "openai.types.model.Model",
+        "__data__": {
+          "id": "models/gemini-2.0-pro-exp",
+          "created": null,
+          "object": "model",
+          "owned_by": "google",
+          "display_name": "Gemini 2.0 Pro Experimental"
+        }
+      },
+      {
+        "__type__": "openai.types.model.Model",
+        "__data__": {
+          "id": "models/gemini-2.0-pro-exp-02-05",
+          "created": null,
+          "object": "model",
+          "owned_by": "google",
+          "display_name": "Gemini 2.0 Pro Experimental 02-05"
+        }
+      },
+      {
+        "__type__": "openai.types.model.Model",
+        "__data__": {
+          "id": "models/gemini-exp-1206",
+          "created": null,
+          "object": "model",
+          "owned_by": "google",
+          "display_name": "Gemini Experimental 1206"
+        }
+      },
+      {
+        "__type__": "openai.types.model.Model",
+        "__data__": {
+          "id": "models/gemini-2.0-flash-thinking-exp-01-21",
+          "created": null,
+          "object": "model",
+          "owned_by": "google",
+          "display_name": "Gemini 2.5 Flash Preview 05-20"
+        }
+      },
+      {
+        "__type__": "openai.types.model.Model",
+        "__data__": {
+          "id": "models/gemini-2.0-flash-thinking-exp",
+          "created": null,
+          "object": "model",
+          "owned_by": "google",
+          "display_name": "Gemini 2.5 Flash Preview 05-20"
+        }
+      },
+      {
+        "__type__": "openai.types.model.Model",
+        "__data__": {
+          "id": "models/gemini-2.0-flash-thinking-exp-1219",
+          "created": null,
+          "object": "model",
+          "owned_by": "google",
+          "display_name": "Gemini 2.5 Flash Preview 05-20"
+        }
+      },
+      {
+        "__type__": "openai.types.model.Model",
+        "__data__": {
+          "id": "models/gemini-2.5-flash-preview-tts",
+          "created": null,
+          "object": "model",
+          "owned_by": "google",
+          "display_name": "Gemini 2.5 Flash Preview TTS"
+        }
+      },
+      {
+        "__type__": "openai.types.model.Model",
+        "__data__": {
+          "id": "models/gemini-2.5-pro-preview-tts",
+          "created": null,
+          "object": "model",
+          "owned_by": "google",
+          "display_name": "Gemini 2.5 Pro Preview TTS"
+        }
+      },
+      {
+        "__type__": "openai.types.model.Model",
+        "__data__": {
+          "id": "models/learnlm-2.0-flash-experimental",
+          "created": null,
+          "object": "model",
+          "owned_by": "google",
+          "display_name": "LearnLM 2.0 Flash Experimental"
+        }
+      },
+      {
+        "__type__": "openai.types.model.Model",
+        "__data__": {
+          "id": "models/gemma-3-1b-it",
+          "created": null,
+          "object": "model",
+          "owned_by": "google",
+          "display_name": "Gemma 3 1B"
+        }
+      },
+      {
+        "__type__": "openai.types.model.Model",
+        "__data__": {
+          "id": "models/gemma-3-4b-it",
+          "created": null,
+          "object": "model",
+          "owned_by": "google",
+          "display_name": "Gemma 3 4B"
+        }
+      },
+      {
+        "__type__": "openai.types.model.Model",
+        "__data__": {
+          "id": "models/gemma-3-12b-it",
+          "created": null,
+          "object": "model",
+          "owned_by": "google",
+          "display_name": "Gemma 3 12B"
+        }
+      },
+      {
+        "__type__": "openai.types.model.Model",
+        "__data__": {
+          "id": "models/gemma-3-27b-it",
+          "created": null,
+          "object": "model",
+          "owned_by": "google",
+          "display_name": "Gemma 3 27B"
+        }
+      },
+      {
+        "__type__": "openai.types.model.Model",
+        "__data__": {
+          "id": "models/gemma-3n-e4b-it",
+          "created": null,
+          "object": "model",
+          "owned_by": "google",
+          "display_name": "Gemma 3n E4B"
+        }
+      },
+      {
+        "__type__": "openai.types.model.Model",
+        "__data__": {
+          "id": "models/gemma-3n-e2b-it",
+          "created": null,
+          "object": "model",
+          "owned_by": "google",
+          "display_name": "Gemma 3n E2B"
+        }
+      },
+      {
+        "__type__": "openai.types.model.Model",
+        "__data__": {
+          "id": "models/gemini-flash-latest",
+          "created": null,
+          "object": "model",
+          "owned_by": "google",
+          "display_name": "Gemini Flash Latest"
+        }
+      },
+      {
+        "__type__": "openai.types.model.Model",
+        "__data__": {
+          "id": "models/gemini-flash-lite-latest",
+          "created": null,
+          "object": "model",
+          "owned_by": "google",
+          "display_name": "Gemini Flash-Lite Latest"
+        }
+      },
+      {
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diff --git a/tests/integration/vector_io/recordings/models-3347a38d1dce9c7428f2fae6f6bb25085a6b93298528e5349dfb4438d3d7324f-17b6020a.json b/tests/integration/vector_io/recordings/models-3347a38d1dce9c7428f2fae6f6bb25085a6b93298528e5349dfb4438d3d7324f-17b6020a.json
new file mode 100644
index 000000000..53f86af99
--- /dev/null
+++ b/tests/integration/vector_io/recordings/models-3347a38d1dce9c7428f2fae6f6bb25085a6b93298528e5349dfb4438d3d7324f-17b6020a.json
@@ -0,0 +1,989 @@
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diff --git a/tests/integration/vector_io/recordings/models-3daddf1063512da260bce92df25fe2b01ac70ec104af88f1a482b6a936be14cc-17b6020a.json b/tests/integration/vector_io/recordings/models-3daddf1063512da260bce92df25fe2b01ac70ec104af88f1a482b6a936be14cc-17b6020a.json
new file mode 100644
index 000000000..2d29aebfb
--- /dev/null
+++ b/tests/integration/vector_io/recordings/models-3daddf1063512da260bce92df25fe2b01ac70ec104af88f1a482b6a936be14cc-17b6020a.json
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diff --git a/tests/integration/vector_io/recordings/models-52b8e996a4f2c944c6bae30ac5274b714ed42392139e2024601a849af31b9253-a882f554.json b/tests/integration/vector_io/recordings/models-52b8e996a4f2c944c6bae30ac5274b714ed42392139e2024601a849af31b9253-a882f554.json
new file mode 100644
index 000000000..be9e401ec
--- /dev/null
+++ b/tests/integration/vector_io/recordings/models-52b8e996a4f2c944c6bae30ac5274b714ed42392139e2024601a849af31b9253-a882f554.json
@@ -0,0 +1,647 @@
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diff --git a/tests/integration/vector_io/recordings/models-cd7b914c23d754f03d8c0a789ce0df17329547d12cbec8bbcc581dc38df5fdbb-a882f554.json b/tests/integration/vector_io/recordings/models-cd7b914c23d754f03d8c0a789ce0df17329547d12cbec8bbcc581dc38df5fdbb-a882f554.json
new file mode 100644
index 000000000..1ec8ba14b
--- /dev/null
+++ b/tests/integration/vector_io/recordings/models-cd7b914c23d754f03d8c0a789ce0df17329547d12cbec8bbcc581dc38df5fdbb-a882f554.json
@@ -0,0 +1,647 @@
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diff --git a/tests/integration/vector_io/recordings/models-e3257f8a2366634242cfecf5298c0bc7af95853da455d1f7c9316fb7e9d1419b-a882f554.json b/tests/integration/vector_io/recordings/models-e3257f8a2366634242cfecf5298c0bc7af95853da455d1f7c9316fb7e9d1419b-a882f554.json
new file mode 100644
index 000000000..20fae07fe
--- /dev/null
+++ b/tests/integration/vector_io/recordings/models-e3257f8a2366634242cfecf5298c0bc7af95853da455d1f7c9316fb7e9d1419b-a882f554.json
@@ -0,0 +1,647 @@
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diff --git a/tests/integration/vector_io/recordings/models-e9e12107519911efec26749b69f37d360c970ecf6a0334d311302e72afd87d25-17b6020a.json b/tests/integration/vector_io/recordings/models-e9e12107519911efec26749b69f37d360c970ecf6a0334d311302e72afd87d25-17b6020a.json
new file mode 100644
index 000000000..5d44f397b
--- /dev/null
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diff --git a/tests/integration/vector_io/recordings/models-eddc1eb84009b784ae43f6ef48daf1d685230aaeee60e0a6866183450427d162-a882f554.json b/tests/integration/vector_io/recordings/models-eddc1eb84009b784ae43f6ef48daf1d685230aaeee60e0a6866183450427d162-a882f554.json
new file mode 100644
index 000000000..ab89e5a65
--- /dev/null
+++ b/tests/integration/vector_io/recordings/models-eddc1eb84009b784ae43f6ef48daf1d685230aaeee60e0a6866183450427d162-a882f554.json
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diff --git a/tests/integration/vector_io/recordings/models-fdf8866dba534adc96a22dccfcb8ddb92f33ee1f4ab308b1c12e971c13988bf0-17b6020a.json b/tests/integration/vector_io/recordings/models-fdf8866dba534adc96a22dccfcb8ddb92f33ee1f4ab308b1c12e971c13988bf0-17b6020a.json
new file mode 100644
index 000000000..3040751db
--- /dev/null
+++ b/tests/integration/vector_io/recordings/models-fdf8866dba534adc96a22dccfcb8ddb92f33ee1f4ab308b1c12e971c13988bf0-17b6020a.json
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+      },
+      {
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+        "__data__": {
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+      {
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+      {
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+      {
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+          "object": "model",
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+      },
+      {
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+        }
+      },
+      {
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+      {
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+        }
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+      {
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+        "__data__": {
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+          "created": 1759512027,
+          "object": "model",
+          "owned_by": "system"
+        }
+      },
+      {
+        "__type__": "openai.types.model.Model",
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+          "created": 1759512137,
+          "object": "model",
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+          "object": "model",
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+        "__data__": {
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+        }
+      },
+      {
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+        "__data__": {
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+          "object": "model",
+          "owned_by": "system"
+        }
+      },
+      {
+        "__type__": "openai.types.model.Model",
+        "__data__": {
+          "id": "o3-mini",
+          "created": 1737146383,
+          "object": "model",
+          "owned_by": "system"
+        }
+      },
+      {
+        "__type__": "openai.types.model.Model",
+        "__data__": {
+          "id": "gpt-4o-realtime-preview-2024-12-17",
+          "created": 1733945430,
+          "object": "model",
+          "owned_by": "system"
+        }
+      },
+      {
+        "__type__": "openai.types.model.Model",
+        "__data__": {
+          "id": "o3-pro-2025-06-10",
+          "created": 1749166761,
+          "object": "model",
+          "owned_by": "system"
+        }
+      },
+      {
+        "__type__": "openai.types.model.Model",
+        "__data__": {
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+          "created": 1698957206,
+          "object": "model",
+          "owned_by": "system"
+        }
+      },
+      {
+        "__type__": "openai.types.model.Model",
+        "__data__": {
+          "id": "babbage-002",
+          "created": 1692634615,
+          "object": "model",
+          "owned_by": "system"
+        }
+      },
+      {
+        "__type__": "openai.types.model.Model",
+        "__data__": {
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+          "created": 1754073306,
+          "object": "model",
+          "owned_by": "system"
+        }
+      },
+      {
+        "__type__": "openai.types.model.Model",
+        "__data__": {
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+          "created": 1677610602,
+          "object": "model",
+          "owned_by": "openai"
+        }
+      },
+      {
+        "__type__": "openai.types.model.Model",
+        "__data__": {
+          "id": "gpt-5-2025-08-07",
+          "created": 1754075360,
+          "object": "model",
+          "owned_by": "system"
+        }
+      },
+      {
+        "__type__": "openai.types.model.Model",
+        "__data__": {
+          "id": "chatgpt-4o-latest",
+          "created": 1723515131,
+          "object": "model",
+          "owned_by": "system"
+        }
+      },
+      {
+        "__type__": "openai.types.model.Model",
+        "__data__": {
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+          "created": 1742068463,
+          "object": "model",
+          "owned_by": "system"
+        }
+      },
+      {
+        "__type__": "openai.types.model.Model",
+        "__data__": {
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+          "created": 1759708615,
+          "object": "model",
+          "owned_by": "system"
+        }
+      },
+      {
+        "__type__": "openai.types.model.Model",
+        "__data__": {
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+          "created": 1759708663,
+          "object": "model",
+          "owned_by": "system"
+        }
+      },
+      {
+        "__type__": "openai.types.model.Model",
+        "__data__": {
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+          "created": 1759469707,
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+        }
+      },
+      {
+        "__type__": "openai.types.model.Model",
+        "__data__": {
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+        }
+      },
+      {
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+          "created": 1727659998,
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+      {
+        "__type__": "openai.types.model.Model",
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+        }
+      },
+      {
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+        }
+      },
+      {
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+          "object": "model",
+          "owned_by": "system"
+        }
+      },
+      {
+        "__type__": "openai.types.model.Model",
+        "__data__": {
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+          "created": 1744133506,
+          "object": "model",
+          "owned_by": "system"
+        }
+      },
+      {
+        "__type__": "openai.types.model.Model",
+        "__data__": {
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+          "created": 1748907838,
+          "object": "model",
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+        }
+      },
+      {
+        "__type__": "openai.types.model.Model",
+        "__data__": {
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+          "created": 1727460443,
+          "object": "model",
+          "owned_by": "system"
+        }
+      },
+      {
+        "__type__": "openai.types.model.Model",
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+          "created": 1748908498,
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+          "owned_by": "system"
+        }
+      },
+      {
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+        "__data__": {
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+          "created": 1759469822,
+          "object": "model",
+          "owned_by": "system"
+        }
+      },
+      {
+        "__type__": "openai.types.model.Model",
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+          "created": 1705953180,
+          "object": "model",
+          "owned_by": "system"
+        }
+      },
+      {
+        "__type__": "openai.types.model.Model",
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+        }
+      },
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+        }
+      },
+      {
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+        }
+      },
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+        }
+      },
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+        }
+      },
+      {
+        "__type__": "openai.types.model.Model",
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+        }
+      },
+      {
+        "__type__": "openai.types.model.Model",
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+        }
+      },
+      {
+        "__type__": "openai.types.model.Model",
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+          "created": 1727389042,
+          "object": "model",
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+        }
+      },
+      {
+        "__type__": "openai.types.model.Model",
+        "__data__": {
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+          "created": 1727131766,
+          "object": "model",
+          "owned_by": "system"
+        }
+      },
+      {
+        "__type__": "openai.types.model.Model",
+        "__data__": {
+          "id": "gpt-5-codex",
+          "created": 1757527818,
+          "object": "model",
+          "owned_by": "system"
+        }
+      }
+    ],
+    "is_streaming": false
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+  "id_normalization_mapping": {}
+}
diff --git a/tests/integration/vector_io/test_openai_vector_stores.py b/tests/integration/vector_io/test_openai_vector_stores.py
index 102f3f00c..083c83981 100644
--- a/tests/integration/vector_io/test_openai_vector_stores.py
+++ b/tests/integration/vector_io/test_openai_vector_stores.py
@@ -1698,3 +1698,49 @@ def test_openai_vector_store_file_contents_with_extra_query(
     assert with_flags_embedding is not None, "Embeddings should be included when include_embeddings=True"
     assert len(with_flags_embedding) > 0, "Embedding should be a non-empty list"
     assert without_flags_embedding is None, "Embeddings should not be included when include_embeddings=False"
+
+
+@vector_provider_wrapper
+def test_openai_vector_store_search_with_rewrite_query(
+    compat_client_with_empty_stores,
+    client_with_models,
+    sample_chunks,
+    embedding_model_id,
+    embedding_dimension,
+    vector_io_provider_id,
+):
+    """Test that rewrite_query parameter is properly passed through and handled."""
+    skip_if_provider_doesnt_support_openai_vector_stores(client_with_models)
+
+    compat_client = compat_client_with_empty_stores
+    llama_client = client_with_models
+
+    # Create vector store and insert chunks
+    vector_store = compat_client.vector_stores.create(
+        name="rewrite_test",
+        extra_body={"embedding_model": embedding_model_id, "provider_id": vector_io_provider_id},
+    )
+    llama_client.vector_io.insert(vector_store_id=vector_store.id, chunks=sample_chunks)
+
+    # Test rewrite_query=False (default behavior)
+    response_no_rewrite = compat_client.vector_stores.search(
+        vector_store_id=vector_store.id,
+        query="programming",
+        max_num_results=2,
+        rewrite_query=False,
+    )
+
+    # Test rewrite_query=True (may work if LLM models are available, or gracefully handle if not)
+    response_with_rewrite = compat_client.vector_stores.search(
+        vector_store_id=vector_store.id,
+        query="programming",
+        max_num_results=2,
+        rewrite_query=True,
+    )
+
+    # Both requests should succeed (rewrite_query=True will gracefully fall back if no LLM models)
+    assert response_no_rewrite is not None
+    assert response_with_rewrite is not None
+
+    # Both should return the same data since we have embedding models but may not have LLM models
+    assert len(response_no_rewrite.data) > 0