diff --git a/litellm/litellm_core_utils/get_llm_provider_logic.py b/litellm/litellm_core_utils/get_llm_provider_logic.py
index 21d69177336..9d3f8aa881f 100644
--- a/litellm/litellm_core_utils/get_llm_provider_logic.py
+++ b/litellm/litellm_core_utils/get_llm_provider_logic.py
@@ -1,3 +1,4 @@
+from functools import lru_cache
 from typing import Optional, Tuple
 
 import httpx
@@ -98,7 +99,7 @@ def handle_anthropic_text_model_custom_llm_provider(
     return model, custom_llm_provider
 
 
-def get_llm_provider(  # noqa: PLR0915
+def _get_llm_provider_impl(  # noqa: PLR0915
     model: str,
     custom_llm_provider: Optional[str] = None,
     api_base: Optional[str] = None,
@@ -106,13 +107,8 @@ def get_llm_provider(  # noqa: PLR0915
     litellm_params: Optional[LiteLLM_Params] = None,
 ) -> Tuple[str, str, Optional[str], Optional[str]]:
     """
-    Returns the provider for a given model name - e.g. 'azure/chatgpt-v-2' -> 'azure'
-
-    For router -> Can also give the whole litellm param dict -> this function will extract the relevant details
-
-    Raises Error - if unable to map model to a provider
-
-    Return model, custom_llm_provider, dynamic_api_key, api_base
+    Implementation of get_llm_provider. Use get_llm_provider() which adds LRU caching
+    when called with only (model, custom_llm_provider).
     """
     try:
         if litellm.LiteLLMProxyChatConfig._should_use_litellm_proxy_by_default(
@@ -490,6 +486,47 @@ def get_llm_provider(  # noqa: PLR0915
             )
 
 
+@lru_cache(maxsize=1024)
+def _get_llm_provider_cached(
+    model: str, custom_llm_provider: Optional[str]
+) -> Tuple[str, str, Optional[str], Optional[str]]:
+    """Cached path for get_llm_provider when api_base, api_key, litellm_params are None."""
+    return _get_llm_provider_impl(
+        model=model,
+        custom_llm_provider=custom_llm_provider,
+        api_base=None,
+        api_key=None,
+        litellm_params=None,
+    )
+
+
+def get_llm_provider(  # noqa: PLR0915
+    model: str,
+    custom_llm_provider: Optional[str] = None,
+    api_base: Optional[str] = None,
+    api_key: Optional[str] = None,
+    litellm_params: Optional[LiteLLM_Params] = None,
+) -> Tuple[str, str, Optional[str], Optional[str]]:
+    """
+    Returns the provider for a given model name - e.g. 'azure/chatgpt-v-2' -> 'azure'
+
+    For router -> Can also give the whole litellm param dict -> this function will extract the relevant details
+
+    Raises Error - if unable to map model to a provider
+
+    Return model, custom_llm_provider, dynamic_api_key, api_base
+    """
+    if api_base is None and api_key is None and litellm_params is None:
+        return _get_llm_provider_cached(model, custom_llm_provider)
+    return _get_llm_provider_impl(
+        model=model,
+        custom_llm_provider=custom_llm_provider,
+        api_base=api_base,
+        api_key=api_key,
+        litellm_params=litellm_params,
+    )
+
+
 def _get_openai_compatible_provider_info(  # noqa: PLR0915
     model: str,
     api_base: Optional[str],
diff --git a/litellm/utils.py b/litellm/utils.py
index 382464ee796..ca95ac6bc72 100644
--- a/litellm/utils.py
+++ b/litellm/utils.py
@@ -968,11 +968,22 @@ def function_setup(  # noqa: PLR0915
             # signatures to ensure compatibility.
             if isinstance(messages, list) and len(messages) > 0:
                 try:
+                    from litellm.litellm_core_utils.get_llm_provider_logic import (
+                        get_llm_provider,
+                    )
                     from litellm.litellm_core_utils.prompt_templates.factory import (
                         THOUGHT_SIGNATURE_SEPARATOR,
                     )
 
                     custom_llm_provider = kwargs.get("custom_llm_provider")
+                    if not custom_llm_provider and model:
+                        try:
+                            _, custom_llm_provider, _, _ = get_llm_provider(
+                                model=model,
+                                custom_llm_provider=custom_llm_provider,
+                            )
+                        except Exception:
+                            pass
 
                     if not _is_gemini_model(model, custom_llm_provider):
                         verbose_logger.debug(
@@ -1858,7 +1869,10 @@ def client(original_function):  # noqa: PLR0915
                     end_time=end_time,
                 )
 
-            _update_response_metadata(
+            update_response_metadata = getattr(
+                sys.modules[__name__], "update_response_metadata"
+            )
+            update_response_metadata(
                 result=result,
                 logging_obj=logging_obj,
                 model=model,
@@ -5682,16 +5696,7 @@ def get_model_info(model: str, custom_llm_provider: Optional[str] = None) -> Mod
         custom_llm_provider=custom_llm_provider,
     )
 
-    provider_info = get_provider_info(
-        model=model, custom_llm_provider=custom_llm_provider
-    )
-    if provider_info:
-        for key, value in provider_info.items():
-            if value is not None:
-                _model_info[key] = value  # type: ignore
-
-    if verbose_logger.isEnabledFor(logging.DEBUG):
-        verbose_logger.debug(f"model_info: {_model_info}")
+    verbose_logger.debug(f"model_info: {_model_info}")
 
     returned_model_info = ModelInfo(
         **_model_info, supported_openai_params=supported_openai_params