diff --git a/litellm/constants.py b/litellm/constants.py
index 21e30bef32b..9f55d2a94ef 100644
--- a/litellm/constants.py
+++ b/litellm/constants.py
@@ -51,6 +51,9 @@ SINGLE_DEPLOYMENT_TRAFFIC_FAILURE_THRESHOLD = int(
 DEFAULT_REASONING_EFFORT_DISABLE_THINKING_BUDGET = int(
     os.getenv("DEFAULT_REASONING_EFFORT_DISABLE_THINKING_BUDGET", 0)
 )
+DEFAULT_REASONING_EFFORT_MINIMAL_THINKING_BUDGET = int(
+    os.getenv("DEFAULT_REASONING_EFFORT_MINIMAL_THINKING_BUDGET", 128)
+)
 DEFAULT_REASONING_EFFORT_LOW_THINKING_BUDGET = int(
     os.getenv("DEFAULT_REASONING_EFFORT_LOW_THINKING_BUDGET", 1024)
 )
diff --git a/litellm/litellm_core_utils/exception_mapping_utils.py b/litellm/litellm_core_utils/exception_mapping_utils.py
index 25ae0269ab3..ad6b3dcaeb4 100644
--- a/litellm/litellm_core_utils/exception_mapping_utils.py
+++ b/litellm/litellm_core_utils/exception_mapping_utils.py
@@ -24,6 +24,55 @@ from ..exceptions import (
 )
 
 
+def _is_operational_404(original_exception) -> bool:
+    """
+    Determine if a 404 status code represents an operational issue rather than a missing model.
+    
+    Args:
+        original_exception: The exception with status_code 404
+        
+    Returns:
+        True if this is an operational issue (rate limiting, cooldowns, etc.)
+        False if this is actually a missing model
+    """
+    try:
+        # Import here to avoid circular imports
+        from litellm.types.router import RouterErrors
+        
+        # Check for known operational error patterns
+        error_message = str(original_exception).lower()
+        
+        # Check for router-specific operational errors
+        operational_patterns = [
+            RouterErrors.no_deployments_available.value.lower(),
+            "no deployments available",
+            "no healthy deployment available",
+            "no healthy deployments available",
+            "deployment over user-defined ratelimit",
+            "crossed budget",
+            "cooldown",
+            "rate limit exceeded",
+            "too many requests"
+        ]
+        
+        for pattern in operational_patterns:
+            if pattern in error_message:
+                return True
+        
+        # Check if this is a RouterRateLimitError (which indicates operational issues)
+        if hasattr(original_exception, '__class__'):
+            exception_class_name = original_exception.__class__.__name__
+            if "RouterRateLimitError" in exception_class_name:
+                return True
+        
+        return False
+        
+    except Exception:
+        # If we can't determine, default to treating it as a missing model
+        # This is safer than potentially hiding real model not found errors
+        return False
+
+
 class ExceptionCheckers:
     """
     Helper class for checking various error conditions in exception strings.
@@ -462,13 +511,26 @@ def exception_type(  # type: ignore  # noqa: PLR0915
                         )
                     elif original_exception.status_code == 404:
                         exception_mapping_worked = True
-                        raise NotFoundError(
-                            message=f"NotFoundError: {exception_provider} - {message}",
-                            model=model,
-                            llm_provider=custom_llm_provider,
-                            response=getattr(original_exception, "response", None),
-                            litellm_debug_info=extra_information,
-                        )
+                        # Check if this is actually a "model not found" vs operational issue
+                        if _is_operational_404(original_exception):
+                            # This is operational (rate limiting, cooldowns), not a missing model
+                            # The proxy will map this to 429 status code, which is correct
+                            raise litellm.ServiceUnavailableError(
+                                message=f"ServiceUnavailableError: {exception_provider} - {message}",
+                                model=model,
+                                llm_provider=custom_llm_provider,
+                                response=getattr(original_exception, "response", None),
+                                litellm_debug_info=extra_information,
+                            )
+                        else:
+                            # This is actually a missing model
+                            raise NotFoundError(
+                                message=f"NotFoundError: {exception_provider} - {message}",
+                                model=model,
+                                llm_provider=custom_llm_provider,
+                                response=getattr(original_exception, "response", None),
+                                litellm_debug_info=extra_information,
+                            )
                     elif original_exception.status_code == 408:
                         exception_mapping_worked = True
                         raise Timeout(
diff --git a/litellm/llms/vertex_ai/gemini/vertex_and_google_ai_studio_gemini.py b/litellm/llms/vertex_ai/gemini/vertex_and_google_ai_studio_gemini.py
index 37470a6ee09..4da99204165 100644
--- a/litellm/llms/vertex_ai/gemini/vertex_and_google_ai_studio_gemini.py
+++ b/litellm/llms/vertex_ai/gemini/vertex_and_google_ai_studio_gemini.py
@@ -30,6 +30,7 @@ from litellm.constants import (
     DEFAULT_REASONING_EFFORT_HIGH_THINKING_BUDGET,
     DEFAULT_REASONING_EFFORT_LOW_THINKING_BUDGET,
     DEFAULT_REASONING_EFFORT_MEDIUM_THINKING_BUDGET,
+    DEFAULT_REASONING_EFFORT_MINIMAL_THINKING_BUDGET,
 )
 from litellm.llms.base_llm.chat.transformation import BaseConfig, BaseLLMException
 from litellm.llms.custom_httpx.http_handler import (
@@ -423,7 +424,12 @@ class VertexGeminiConfig(VertexAIBaseConfig, BaseConfig):
     def _map_reasoning_effort_to_thinking_budget(
         reasoning_effort: str,
     ) -> GeminiThinkingConfig:
-        if reasoning_effort == "low":
+        if reasoning_effort == "minimal":
+            return {
+                "thinkingBudget": DEFAULT_REASONING_EFFORT_MINIMAL_THINKING_BUDGET,
+                "includeThoughts": True,
+            }
+        elif reasoning_effort == "low":
             return {
                 "thinkingBudget": DEFAULT_REASONING_EFFORT_LOW_THINKING_BUDGET,
                 "includeThoughts": True,