diff --git a/llama_stack/providers/adapters/inference/vllm/vllm.py b/llama_stack/providers/adapters/inference/vllm/vllm.py
index 09c17ee57..0259c7061 100644
--- a/llama_stack/providers/adapters/inference/vllm/vllm.py
+++ b/llama_stack/providers/adapters/inference/vllm/vllm.py
@@ -8,6 +8,7 @@ from typing import AsyncGenerator
 from llama_models.llama3.api.chat_format import ChatFormat
 from llama_models.llama3.api.datatypes import Message
 from llama_models.llama3.api.tokenizer import Tokenizer
+from llama_models.sku_list import all_registered_models, resolve_model
 
 from openai import OpenAI
 
@@ -26,40 +27,16 @@ from llama_stack.providers.utils.inference.prompt_adapter import (
 from .config import VLLMInferenceAdapterConfig
 
 
-VLLM_SUPPORTED_MODELS = {
-    "Llama3.1-8B": "meta-llama/Llama-3.1-8B",
-    "Llama3.1-70B": "meta-llama/Llama-3.1-70B",
-    "Llama3.1-405B:bf16-mp8": "meta-llama/Llama-3.1-405B",
-    "Llama3.1-405B": "meta-llama/Llama-3.1-405B-FP8",
-    "Llama3.1-405B:bf16-mp16": "meta-llama/Llama-3.1-405B",
-    "Llama3.1-8B-Instruct": "meta-llama/Llama-3.1-8B-Instruct",
-    "Llama3.1-70B-Instruct": "meta-llama/Llama-3.1-70B-Instruct",
-    "Llama3.1-405B-Instruct:bf16-mp8": "meta-llama/Llama-3.1-405B-Instruct",
-    "Llama3.1-405B-Instruct": "meta-llama/Llama-3.1-405B-Instruct-FP8",
-    "Llama3.1-405B-Instruct:bf16-mp16": "meta-llama/Llama-3.1-405B-Instruct",
-    "Llama3.2-1B": "meta-llama/Llama-3.2-1B",
-    "Llama3.2-3B": "meta-llama/Llama-3.2-3B",
-    "Llama3.2-11B-Vision": "meta-llama/Llama-3.2-11B-Vision",
-    "Llama3.2-90B-Vision": "meta-llama/Llama-3.2-90B-Vision",
-    "Llama3.2-1B-Instruct": "meta-llama/Llama-3.2-1B-Instruct",
-    "Llama3.2-3B-Instruct": "meta-llama/Llama-3.2-3B-Instruct",
-    "Llama3.2-11B-Vision-Instruct": "meta-llama/Llama-3.2-11B-Vision-Instruct",
-    "Llama3.2-90B-Vision-Instruct": "meta-llama/Llama-3.2-90B-Vision-Instruct",
-    "Llama-Guard-3-11B-Vision": "meta-llama/Llama-Guard-3-11B-Vision",
-    "Llama-Guard-3-1B:int4-mp1": "meta-llama/Llama-Guard-3-1B-INT4",
-    "Llama-Guard-3-1B": "meta-llama/Llama-Guard-3-1B",
-    "Llama-Guard-3-8B": "meta-llama/Llama-Guard-3-8B",
-    "Llama-Guard-3-8B:int8-mp1": "meta-llama/Llama-Guard-3-8B-INT8",
-    "Prompt-Guard-86M": "meta-llama/Prompt-Guard-86M",
-    "Llama-Guard-2-8B": "meta-llama/Llama-Guard-2-8B",
-}
-
-
 class VLLMInferenceAdapter(Inference, ModelsProtocolPrivate):
     def __init__(self, config: VLLMInferenceAdapterConfig) -> None:
         self.config = config
         self.formatter = ChatFormat(Tokenizer.get_instance())
         self.client = None
+        self.huggingface_repo_to_llama_model_id = {
+            model.huggingface_repo: model.descriptor()
+            for model in all_registered_models()
+            if model.huggingface_repo
+        }
 
     async def initialize(self) -> None:
         self.client = OpenAI(base_url=self.config.url, api_key=self.config.api_token)
@@ -71,15 +48,14 @@ class VLLMInferenceAdapter(Inference, ModelsProtocolPrivate):
         pass
 
     async def list_models(self) -> List[ModelDef]:
-        vllm_to_llama_map = {v: k for k, v in VLLM_SUPPORTED_MODELS.items()}
-
         models = []
         for model in self.client.models.list():
-            if model.id not in vllm_to_llama_map:
-                print(f"Unknown model served by vllm: {model.id}")
+            repo = model.id
+            if repo not in self.huggingface_repo_to_llama_model_id:
+                print(f"Unknown model served by vllm: {repo}")
                 continue
 
-            identifier = vllm_to_llama_map[model.id]
+            identifier = self.huggingface_repo_to_llama_model_id[repo]
             models.append(
                 ModelDef(
                     identifier=identifier,
@@ -155,8 +131,13 @@ class VLLMInferenceAdapter(Inference, ModelsProtocolPrivate):
         options = get_sampling_options(request.sampling_params)
         if "max_tokens" not in options:
             options["max_tokens"] = self.config.max_tokens
+
+        model = resolve_model(request.model)
+        if model is None:
+            raise ValueError(f"Unknown model: {request.model}")
+
         return {
-            "model": VLLM_SUPPORTED_MODELS[request.model],
+            "model": model.huggingface_repo,
             "prompt": chat_completion_request_to_prompt(request, self.formatter),
             "stream": request.stream,
             **options,