diff --git a/llama_stack/distribution/routers/__init__.py b/llama_stack/distribution/routers/__init__.py
index 6660e180c..d0fca8771 100644
--- a/llama_stack/distribution/routers/__init__.py
+++ b/llama_stack/distribution/routers/__init__.py
@@ -45,7 +45,7 @@ async def get_routing_table_impl(
     return impl
 
 
-async def get_auto_router_impl(api: Api, routing_table: RoutingTable, _deps: Dict[str, Any]) -> Any:
+async def get_auto_router_impl(api: Api, routing_table: RoutingTable, deps: Dict[str, Any]) -> Any:
     from .routers import (
         DatasetIORouter,
         EvalRouter,
@@ -66,17 +66,16 @@ async def get_auto_router_impl(api: Api, routing_table: RoutingTable, _deps: Dic
         "tool_runtime": ToolRuntimeRouter,
     }
     api_to_deps = {
-        "inference": [Api.telemetry],
+        "inference": {"telemetry": Api.telemetry},
     }
     if api.value not in api_to_routers:
         raise ValueError(f"API {api.value} not found in router map")
 
-    deps = []
-    for dep in api_to_deps.get(api.value, []):
-        if dep not in _deps:
-            raise ValueError(f"Dependency {dep} not found in _deps")
-        deps.append(_deps[dep])
+    api_to_dep_impl = {}
+    for dep_name, dep_api in api_to_deps.get(api.value, {}).items():
+        if dep_api in deps:
+            api_to_dep_impl[dep_name] = deps[dep_api]
 
-    impl = api_to_routers[api.value](routing_table, *deps)
+    impl = api_to_routers[api.value](routing_table, **api_to_dep_impl)
     await impl.initialize()
     return impl
diff --git a/llama_stack/distribution/routers/routers.py b/llama_stack/distribution/routers/routers.py
index 4620efef7..a9fc13502 100644
--- a/llama_stack/distribution/routers/routers.py
+++ b/llama_stack/distribution/routers/routers.py
@@ -119,12 +119,13 @@ class InferenceRouter(Inference):
     def __init__(
         self,
         routing_table: RoutingTable,
-        telemetry: Telemetry,
+        telemetry: Optional[Telemetry] = None,
     ) -> None:
         self.routing_table = routing_table
         self.telemetry = telemetry
-        self.tokenizer = Tokenizer.get_instance()
-        self.formatter = ChatFormat(self.tokenizer)
+        if self.telemetry:
+            self.tokenizer = Tokenizer.get_instance()
+            self.formatter = ChatFormat(self.tokenizer)
 
     async def initialize(self) -> None:
         pass
@@ -226,13 +227,13 @@ class InferenceRouter(Inference):
             tool_config=tool_config,
         )
         provider = self.routing_table.get_provider_impl(model_id)
+        model_input = self.formatter.encode_dialog_prompt(
+            messages,
+            tool_config.tool_prompt_format,
+        )
         if stream:
 
             async def stream_generator():
-                model_input = self.formatter.encode_dialog_prompt(
-                    messages,
-                    tool_config.tool_prompt_format,
-                )
                 prompt_tokens = len(model_input.tokens) if model_input.tokens else 0
                 completion_text = ""
                 async for chunk in await provider.chat_completion(**params):
@@ -255,16 +256,13 @@ class InferenceRouter(Inference):
                                 total_tokens=total_tokens,
                             )
                         )
-                        await self._log_token_usage(prompt_tokens, completion_tokens, total_tokens, model)
+                        if self.telemetry:
+                            await self._log_token_usage(prompt_tokens, completion_tokens, total_tokens, model)
                     yield chunk
 
             return stream_generator()
         else:
             response = await provider.chat_completion(**params)
-            model_input = self.formatter.encode_dialog_prompt(
-                messages,
-                tool_config.tool_prompt_format,
-            )
             model_output = self.formatter.encode_dialog_prompt(
                 [response.completion_message],
                 tool_config.tool_prompt_format,
@@ -281,7 +279,8 @@ class InferenceRouter(Inference):
                     total_tokens=total_tokens,
                 )
             )
-            await self._log_token_usage(prompt_tokens, completion_tokens, total_tokens, model)
+            if self.telemetry:
+                await self._log_token_usage(prompt_tokens, completion_tokens, total_tokens, model)
             return response
 
     async def completion(