diff --git a/llama_stack/apis/inference/inference.py b/llama_stack/apis/inference/inference.py
index 4b6530f63..1e7b29722 100644
--- a/llama_stack/apis/inference/inference.py
+++ b/llama_stack/apis/inference/inference.py
@@ -216,7 +216,7 @@ class EmbeddingsResponse(BaseModel):
 
 
 class ModelStore(Protocol):
-    def get_model(self, identifier: str) -> ModelDef: ...
+    def get_model(self, identifier: str) -> Model: ...
 
 
 @runtime_checkable
diff --git a/llama_stack/apis/models/client.py b/llama_stack/apis/models/client.py
index 3880a7f91..d986828ee 100644
--- a/llama_stack/apis/models/client.py
+++ b/llama_stack/apis/models/client.py
@@ -26,16 +26,16 @@ class ModelsClient(Models):
     async def shutdown(self) -> None:
         pass
 
-    async def list_models(self) -> List[ModelDefWithProvider]:
+    async def list_models(self) -> List[Model]:
         async with httpx.AsyncClient() as client:
             response = await client.get(
                 f"{self.base_url}/models/list",
                 headers={"Content-Type": "application/json"},
             )
             response.raise_for_status()
-            return [ModelDefWithProvider(**x) for x in response.json()]
+            return [Model(**x) for x in response.json()]
 
-    async def register_model(self, model: ModelDefWithProvider) -> None:
+    async def register_model(self, model: Model) -> None:
         async with httpx.AsyncClient() as client:
             response = await client.post(
                 f"{self.base_url}/models/register",
@@ -46,7 +46,7 @@ class ModelsClient(Models):
             )
             response.raise_for_status()
 
-    async def get_model(self, identifier: str) -> Optional[ModelDefWithProvider]:
+    async def get_model(self, identifier: str) -> Optional[Model]:
         async with httpx.AsyncClient() as client:
             response = await client.get(
                 f"{self.base_url}/models/get",
@@ -59,7 +59,7 @@ class ModelsClient(Models):
             j = response.json()
             if j is None:
                 return None
-            return ModelDefWithProvider(**j)
+            return Model(**j)
 
 
 async def run_main(host: str, port: int, stream: bool):
diff --git a/llama_stack/apis/models/models.py b/llama_stack/apis/models/models.py
index ffb3b022e..d11f31ab6 100644
--- a/llama_stack/apis/models/models.py
+++ b/llama_stack/apis/models/models.py
@@ -7,37 +7,27 @@
 from typing import Any, Dict, List, Literal, Optional, Protocol, runtime_checkable
 
 from llama_models.schema_utils import json_schema_type, webmethod
-from pydantic import BaseModel, Field
+from pydantic import Field
+
+from llama_stack.apis.resource import Resource
 
 
-class ModelDef(BaseModel):
-    identifier: str = Field(
-        description="A unique name for the model type",
-    )
-    llama_model: str = Field(
-        description="Pointer to the underlying core Llama family model. Each model served by Llama Stack must have a core Llama model.",
-    )
+@json_schema_type
+class Model(Resource):
+    type: Literal["model"] = "model"
     metadata: Dict[str, Any] = Field(
         default_factory=dict,
         description="Any additional metadata for this model",
     )
 
 
-@json_schema_type
-class ModelDefWithProvider(ModelDef):
-    type: Literal["model"] = "model"
-    provider_id: str = Field(
-        description="The provider ID for this model",
-    )
-
-
 @runtime_checkable
 class Models(Protocol):
     @webmethod(route="/models/list", method="GET")
-    async def list_models(self) -> List[ModelDefWithProvider]: ...
+    async def list_models(self) -> List[Model]: ...
 
     @webmethod(route="/models/get", method="GET")
-    async def get_model(self, identifier: str) -> Optional[ModelDefWithProvider]: ...
+    async def get_model(self, identifier: str) -> Optional[Model]: ...
 
     @webmethod(route="/models/register", method="POST")
-    async def register_model(self, model: ModelDefWithProvider) -> None: ...
+    async def register_model(self, model: Model) -> None: ...
diff --git a/llama_stack/distribution/datatypes.py b/llama_stack/distribution/datatypes.py
index b7907d1a0..a2eafe273 100644
--- a/llama_stack/distribution/datatypes.py
+++ b/llama_stack/distribution/datatypes.py
@@ -31,7 +31,7 @@ RoutingKey = Union[str, List[str]]
 
 
 RoutableObject = Union[
-    ModelDef,
+    Model,
     Shield,
     MemoryBankDef,
     DatasetDef,
@@ -41,7 +41,7 @@ RoutableObject = Union[
 
 RoutableObjectWithProvider = Annotated[
     Union[
-        ModelDefWithProvider,
+        Model,
         Shield,
         MemoryBankDefWithProvider,
         DatasetDefWithProvider,
diff --git a/llama_stack/distribution/routers/routers.py b/llama_stack/distribution/routers/routers.py
index cca94485c..2ea9e92f7 100644
--- a/llama_stack/distribution/routers/routers.py
+++ b/llama_stack/distribution/routers/routers.py
@@ -70,7 +70,7 @@ class InferenceRouter(Inference):
     async def shutdown(self) -> None:
         pass
 
-    async def register_model(self, model: ModelDef) -> None:
+    async def register_model(self, model: Model) -> None:
         await self.routing_table.register_model(model)
 
     async def chat_completion(
diff --git a/llama_stack/distribution/routers/routing_tables.py b/llama_stack/distribution/routers/routing_tables.py
index 6c36892db..fcdd448ff 100644
--- a/llama_stack/distribution/routers/routing_tables.py
+++ b/llama_stack/distribution/routers/routing_tables.py
@@ -78,12 +78,7 @@ class CommonRoutingTableImpl(RoutingTable):
         # Register all objects from providers
         for pid, p in self.impls_by_provider_id.items():
             api = get_impl_api(p)
-            if api == Api.inference:
-                p.model_store = self
-                models = await p.list_models()
-                await add_objects(models, pid, ModelDefWithProvider)
-
-            elif api == Api.memory:
+            if api == Api.memory:
                 p.memory_bank_store = self
                 memory_banks = await p.list_memory_banks()
                 await add_objects(memory_banks, pid, None)
@@ -185,13 +180,13 @@ class CommonRoutingTableImpl(RoutingTable):
 
 
 class ModelsRoutingTable(CommonRoutingTableImpl, Models):
-    async def list_models(self) -> List[ModelDefWithProvider]:
+    async def list_models(self) -> List[Model]:
         return await self.get_all_with_type("model")
 
-    async def get_model(self, identifier: str) -> Optional[ModelDefWithProvider]:
+    async def get_model(self, identifier: str) -> Optional[Model]:
         return await self.get_object_by_identifier(identifier)
 
-    async def register_model(self, model: ModelDefWithProvider) -> None:
+    async def register_model(self, model: Model) -> None:
         await self.register_object(model)
 
 
diff --git a/llama_stack/distribution/store/tests/test_registry.py b/llama_stack/distribution/store/tests/test_registry.py
index a9df4bed6..b2f7ada86 100644
--- a/llama_stack/distribution/store/tests/test_registry.py
+++ b/llama_stack/distribution/store/tests/test_registry.py
@@ -9,7 +9,7 @@ import os
 import pytest
 import pytest_asyncio
 from llama_stack.distribution.store import *  # noqa F403
-from llama_stack.apis.inference import ModelDefWithProvider
+from llama_stack.apis.inference import Model
 from llama_stack.apis.memory_banks import VectorMemoryBankDef
 from llama_stack.providers.utils.kvstore import kvstore_impl, SqliteKVStoreConfig
 from llama_stack.distribution.datatypes import *  # noqa F403
@@ -50,9 +50,8 @@ def sample_bank():
 
 @pytest.fixture
 def sample_model():
-    return ModelDefWithProvider(
+    return Model(
         identifier="test_model",
-        llama_model="Llama3.2-3B-Instruct",
         provider_id="test-provider",
     )
 
@@ -84,7 +83,6 @@ async def test_basic_registration(registry, sample_bank, sample_model):
     assert len(results) == 1
     result_model = results[0]
     assert result_model.identifier == sample_model.identifier
-    assert result_model.llama_model == sample_model.llama_model
     assert result_model.provider_id == sample_model.provider_id
 
 
diff --git a/llama_stack/providers/datatypes.py b/llama_stack/providers/datatypes.py
index 7f43e7cbc..e87902127 100644
--- a/llama_stack/providers/datatypes.py
+++ b/llama_stack/providers/datatypes.py
@@ -13,7 +13,7 @@ from pydantic import BaseModel, Field
 
 from llama_stack.apis.datasets import DatasetDef
 from llama_stack.apis.memory_banks import MemoryBankDef
-from llama_stack.apis.models import ModelDef
+from llama_stack.apis.models import Model
 from llama_stack.apis.scoring_functions import ScoringFnDef
 from llama_stack.apis.shields import Shield
 
@@ -41,9 +41,7 @@ class Api(Enum):
 
 
 class ModelsProtocolPrivate(Protocol):
-    async def list_models(self) -> List[ModelDef]: ...
-
-    async def register_model(self, model: ModelDef) -> None: ...
+    async def register_model(self, model: Model) -> None: ...
 
 
 class ShieldsProtocolPrivate(Protocol):
diff --git a/llama_stack/providers/inline/inference/meta_reference/inference.py b/llama_stack/providers/inline/inference/meta_reference/inference.py
index b643ac238..2fdc8f2d5 100644
--- a/llama_stack/providers/inline/inference/meta_reference/inference.py
+++ b/llama_stack/providers/inline/inference/meta_reference/inference.py
@@ -12,7 +12,7 @@ from llama_models.sku_list import resolve_model
 
 from llama_models.llama3.api.datatypes import *  # noqa: F403
 from llama_stack.apis.inference import *  # noqa: F403
-from llama_stack.providers.datatypes import ModelDef, ModelsProtocolPrivate
+from llama_stack.providers.datatypes import Model, ModelsProtocolPrivate
 
 from llama_stack.providers.utils.inference.prompt_adapter import (
     convert_image_media_to_url,
@@ -45,16 +45,11 @@ class MetaReferenceInferenceImpl(Inference, ModelsProtocolPrivate):
         else:
             self.generator = Llama.build(self.config)
 
-    async def register_model(self, model: ModelDef) -> None:
-        raise ValueError("Dynamic model registration is not supported")
-
-    async def list_models(self) -> List[ModelDef]:
-        return [
-            ModelDef(
-                identifier=self.model.descriptor(),
-                llama_model=self.model.descriptor(),
+    async def register_model(self, model: Model) -> None:
+        if model.identifier != self.model.descriptor():
+            raise ValueError(
+                f"Model mismatch: {model.identifier} != {self.model.descriptor()}"
             )
-        ]
 
     async def shutdown(self) -> None:
         if self.config.create_distributed_process_group:
diff --git a/llama_stack/providers/inline/inference/vllm/vllm.py b/llama_stack/providers/inline/inference/vllm/vllm.py
index cf5b0572b..a25707310 100644
--- a/llama_stack/providers/inline/inference/vllm/vllm.py
+++ b/llama_stack/providers/inline/inference/vllm/vllm.py
@@ -20,7 +20,7 @@ from vllm.sampling_params import SamplingParams as VLLMSamplingParams
 
 from llama_stack.apis.inference import *  # noqa: F403
 
-from llama_stack.providers.datatypes import ModelDef, ModelsProtocolPrivate
+from llama_stack.providers.datatypes import Model, ModelsProtocolPrivate
 from llama_stack.providers.utils.inference.openai_compat import (
     OpenAICompatCompletionChoice,
     OpenAICompatCompletionResponse,
@@ -83,14 +83,14 @@ class VLLMInferenceImpl(Inference, ModelsProtocolPrivate):
         if self.engine:
             self.engine.shutdown_background_loop()
 
-    async def register_model(self, model: ModelDef) -> None:
+    async def register_model(self, model: Model) -> None:
         raise ValueError(
             "You cannot dynamically add a model to a running vllm instance"
         )
 
-    async def list_models(self) -> List[ModelDef]:
+    async def list_models(self) -> List[Model]:
         return [
-            ModelDef(
+            Model(
                 identifier=self.config.model,
                 llama_model=self.config.model,
             )
diff --git a/llama_stack/providers/remote/inference/ollama/ollama.py b/llama_stack/providers/remote/inference/ollama/ollama.py
index 3530e1234..18cfef50d 100644
--- a/llama_stack/providers/remote/inference/ollama/ollama.py
+++ b/llama_stack/providers/remote/inference/ollama/ollama.py
@@ -15,7 +15,7 @@ from llama_models.llama3.api.tokenizer import Tokenizer
 from ollama import AsyncClient
 
 from llama_stack.apis.inference import *  # noqa: F403
-from llama_stack.providers.datatypes import ModelsProtocolPrivate
+from llama_stack.providers.datatypes import Model, ModelsProtocolPrivate
 
 from llama_stack.providers.utils.inference.openai_compat import (
     get_sampling_options,
@@ -65,10 +65,11 @@ class OllamaInferenceAdapter(Inference, ModelsProtocolPrivate):
     async def shutdown(self) -> None:
         pass
 
-    async def register_model(self, model: ModelDef) -> None:
-        raise ValueError("Dynamic model registration is not supported")
+    async def register_model(self, model: Model) -> None:
+        if model.identifier not in OLLAMA_SUPPORTED_MODELS:
+            raise ValueError(f"Model {model.identifier} is not supported by Ollama")
 
-    async def list_models(self) -> List[ModelDef]:
+    async def list_models(self) -> List[Model]:
         ollama_to_llama = {v: k for k, v in OLLAMA_SUPPORTED_MODELS.items()}
 
         ret = []
@@ -80,9 +81,8 @@ class OllamaInferenceAdapter(Inference, ModelsProtocolPrivate):
 
             llama_model = ollama_to_llama[r["model"]]
             ret.append(
-                ModelDef(
+                Model(
                     identifier=llama_model,
-                    llama_model=llama_model,
                     metadata={
                         "ollama_model": r["model"],
                     },
diff --git a/llama_stack/providers/remote/inference/sample/sample.py b/llama_stack/providers/remote/inference/sample/sample.py
index 09171e395..79ce1ffe4 100644
--- a/llama_stack/providers/remote/inference/sample/sample.py
+++ b/llama_stack/providers/remote/inference/sample/sample.py
@@ -14,7 +14,7 @@ class SampleInferenceImpl(Inference):
     def __init__(self, config: SampleConfig):
         self.config = config
 
-    async def register_model(self, model: ModelDef) -> None:
+    async def register_model(self, model: Model) -> None:
         # these are the model names the Llama Stack will use to route requests to this provider
         # perform validation here if necessary
         pass
diff --git a/llama_stack/providers/remote/inference/tgi/tgi.py b/llama_stack/providers/remote/inference/tgi/tgi.py
index e9ba49fa9..8d3d1f86d 100644
--- a/llama_stack/providers/remote/inference/tgi/tgi.py
+++ b/llama_stack/providers/remote/inference/tgi/tgi.py
@@ -16,7 +16,7 @@ from llama_models.sku_list import all_registered_models
 from llama_stack.apis.inference import *  # noqa: F403
 from llama_stack.apis.models import *  # noqa: F403
 
-from llama_stack.providers.datatypes import ModelDef, ModelsProtocolPrivate
+from llama_stack.providers.datatypes import Model, ModelsProtocolPrivate
 
 from llama_stack.providers.utils.inference.openai_compat import (
     get_sampling_options,
@@ -50,14 +50,14 @@ class _HfAdapter(Inference, ModelsProtocolPrivate):
             if model.huggingface_repo
         }
 
-    async def register_model(self, model: ModelDef) -> None:
-        raise ValueError("Model registration is not supported for HuggingFace models")
+    async def register_model(self, model: Model) -> None:
+        pass
 
-    async def list_models(self) -> List[ModelDef]:
+    async def list_models(self) -> List[Model]:
         repo = self.model_id
         identifier = self.huggingface_repo_to_llama_model_id[repo]
         return [
-            ModelDef(
+            Model(
                 identifier=identifier,
                 llama_model=identifier,
                 metadata={
diff --git a/llama_stack/providers/remote/inference/vllm/vllm.py b/llama_stack/providers/remote/inference/vllm/vllm.py
index 8dfe37c55..185aeeb03 100644
--- a/llama_stack/providers/remote/inference/vllm/vllm.py
+++ b/llama_stack/providers/remote/inference/vllm/vllm.py
@@ -13,7 +13,7 @@ from llama_models.sku_list import all_registered_models, resolve_model
 from openai import OpenAI
 
 from llama_stack.apis.inference import *  # noqa: F403
-from llama_stack.providers.datatypes import ModelsProtocolPrivate
+from llama_stack.providers.datatypes import Model, ModelsProtocolPrivate
 
 from llama_stack.providers.utils.inference.openai_compat import (
     get_sampling_options,
@@ -44,13 +44,13 @@ class VLLMInferenceAdapter(Inference, ModelsProtocolPrivate):
     async def initialize(self) -> None:
         self.client = OpenAI(base_url=self.config.url, api_key=self.config.api_token)
 
-    async def register_model(self, model: ModelDef) -> None:
+    async def register_model(self, model: Model) -> None:
         raise ValueError("Model registration is not supported for vLLM models")
 
     async def shutdown(self) -> None:
         pass
 
-    async def list_models(self) -> List[ModelDef]:
+    async def list_models(self) -> List[Model]:
         models = []
         for model in self.client.models.list():
             repo = model.id
@@ -60,7 +60,7 @@ class VLLMInferenceAdapter(Inference, ModelsProtocolPrivate):
 
             identifier = self.huggingface_repo_to_llama_model_id[repo]
             models.append(
-                ModelDef(
+                Model(
                     identifier=identifier,
                     llama_model=identifier,
                 )
diff --git a/llama_stack/providers/tests/inference/fixtures.py b/llama_stack/providers/tests/inference/fixtures.py
index 77e76b9ee..f6b657622 100644
--- a/llama_stack/providers/tests/inference/fixtures.py
+++ b/llama_stack/providers/tests/inference/fixtures.py
@@ -10,6 +10,7 @@ import pytest
 import pytest_asyncio
 
 from llama_stack.distribution.datatypes import Api, Provider
+from llama_stack.providers.datatypes import Model
 from llama_stack.providers.inline.inference.meta_reference import (
     MetaReferenceInferenceConfig,
 )
@@ -152,7 +153,7 @@ INFERENCE_FIXTURES = [
 
 
 @pytest_asyncio.fixture(scope="session")
-async def inference_stack(request):
+async def inference_stack(request, inference_model):
     fixture_name = request.param
     inference_fixture = request.getfixturevalue(f"inference_{fixture_name}")
     impls = await resolve_impls_for_test_v2(
@@ -161,4 +162,11 @@ async def inference_stack(request):
         inference_fixture.provider_data,
     )
 
+    model = Model(
+        identifier=inference_model,
+        provider_id=inference_fixture.providers[0].provider_id,
+    )
+
+    await impls[Api.models].register_model(model)
+
     return (impls[Api.inference], impls[Api.models])
diff --git a/llama_stack/providers/tests/inference/test_text_inference.py b/llama_stack/providers/tests/inference/test_text_inference.py
index 7de0f7ec2..e7bfbc135 100644
--- a/llama_stack/providers/tests/inference/test_text_inference.py
+++ b/llama_stack/providers/tests/inference/test_text_inference.py
@@ -69,7 +69,7 @@ class TestInference:
         response = await models_impl.list_models()
         assert isinstance(response, list)
         assert len(response) >= 1
-        assert all(isinstance(model, ModelDefWithProvider) for model in response)
+        assert all(isinstance(model, Model) for model in response)
 
         model_def = None
         for model in response:
diff --git a/llama_stack/providers/utils/inference/model_registry.py b/llama_stack/providers/utils/inference/model_registry.py
index c4db0e0c7..141e4af31 100644
--- a/llama_stack/providers/utils/inference/model_registry.py
+++ b/llama_stack/providers/utils/inference/model_registry.py
@@ -4,11 +4,11 @@
 # This source code is licensed under the terms described in the LICENSE file in
 # the root directory of this source tree.
 
-from typing import Dict, List
+from typing import Dict
 
 from llama_models.sku_list import resolve_model
 
-from llama_stack.providers.datatypes import ModelDef, ModelsProtocolPrivate
+from llama_stack.providers.datatypes import Model, ModelsProtocolPrivate
 
 
 class ModelRegistryHelper(ModelsProtocolPrivate):
@@ -28,14 +28,8 @@ class ModelRegistryHelper(ModelsProtocolPrivate):
 
         return self.stack_to_provider_models_map[identifier]
 
-    async def register_model(self, model: ModelDef) -> None:
+    async def register_model(self, model: Model) -> None:
         if model.identifier not in self.stack_to_provider_models_map:
             raise ValueError(
                 f"Unsupported model {model.identifier}. Supported models: {self.stack_to_provider_models_map.keys()}"
             )
-
-    async def list_models(self) -> List[ModelDef]:
-        models = []
-        for llama_model, provider_model in self.stack_to_provider_models_map.items():
-            models.append(ModelDef(identifier=llama_model, llama_model=llama_model))
-        return models