fix(vertex_ai): route Model Garden models through the generateContent adapter

litellm/utils.py

@@ -10100,19 +10100,18 @@ def get_provider_google_genai_generate_content_config(
 
             return GoogleGenAIConfig()
         elif litellm.LlmProviders.VERTEX_AI == provider:
+            from litellm.llms.vertex_ai.common_utils import (
+                VertexAIModelRoute,
+                get_vertex_ai_model_route,
+            )
             from litellm.llms.vertex_ai.google_genai.transformation import (
                 VertexAIGoogleGenAIConfig,
             )
-            from litellm.llms.vertex_ai.vertex_ai_partner_models.main import (
-                VertexAIPartnerModels,
-            )
 
-            #########################################################
-            # If Vertex Partner models like Anthropic, Mistral, etc. are used,
-            # return None as we want this to go through the litellm.completion() adapter
-            # and not the Google Gen AI adapter
-            #########################################################
-            if VertexAIPartnerModels.is_vertex_partner_model(model):
+            if get_vertex_ai_model_route(model) in (
+                VertexAIModelRoute.PARTNER_MODELS,
+                VertexAIModelRoute.MODEL_GARDEN,
+            ):
                 return None
 
             #########################################################

tests/unit/test_utils.py

@@ -6645,6 +6645,27 @@ def test_get_model_info_gemini(monkeypatch):
             assert info.get("rpm") is not None, f"{model} does not have rpm"
 
 
+@pytest.mark.parametrize(
+    "model, expects_native_config",
+    [
+        ("gemini-2.5-flash", True),
+        ("xai/grok-4.6", False),
+        ("claude-haiku-4-5@20251001", False),
+        ("openai/gpt-oss-120b-maas", False),
+    ],
+)
+def test_vertex_generate_content_config_follows_model_route(model: str, expects_native_config: bool):
+    from litellm.llms.vertex_ai.google_genai.transformation import VertexAIGoogleGenAIConfig
+
+    config: Final = ProviderConfigManager.get_provider_google_genai_generate_content_config(
+        model=model, provider=litellm.LlmProviders.VERTEX_AI
+    )
+    if expects_native_config:
+        assert isinstance(config, VertexAIGoogleGenAIConfig)
+    else:
+        assert config is None
+
+
 @pytest.mark.parametrize(
     ("max_parallel_requests", "rpm", "tpm", "default_max_parallel_requests", "expected"),
     [