Route Vertex Gemma MaaS through model garden

litellm/llms/vertex_ai/common_utils.py

@@ -114,7 +114,7 @@ def get_vertex_ai_model_route(
         VertexAIModelRoute.GEMMA
 
         >>> get_vertex_ai_model_route("google/gemma-4-26b-a4b-it-maas")
-        VertexAIModelRoute.GEMMA
+        VertexAIModelRoute.MODEL_GARDEN
 
         >>> get_vertex_ai_model_route("openai/gpt-oss-120b")
         VertexAIModelRoute.MODEL_GARDEN
@@ -152,14 +152,19 @@ def get_vertex_ai_model_route(
         return VertexAIModelRoute.BGE
 
     # Check for gemma models
-    if "gemma/" in model or model.startswith("google/gemma-"):
+    if "gemma/" in model:
         return VertexAIModelRoute.GEMMA
 
     # Check for model garden OpenAI-compatible publisher models.
     # Examples:
+    # - google/gemma-4-26b-a4b-it-maas
     # - openai/gpt-oss-120b-maas
     # - xai/grok-4.1-fast-non-reasoning
-    if "openai" in model or model.startswith("xai/"):
+    if (
+        "openai" in model
+        or model.startswith("google/gemma-")
+        or model.startswith("xai/")
+    ):
         return VertexAIModelRoute.MODEL_GARDEN
 
     # Check for gemini models

tests/test_litellm/llms/vertex_ai/test_vertex_model_garden_openapi.py

@@ -1,7 +1,15 @@
 """Vertex Model Garden: OpenAPI base URL for publisher/model ids vs per-endpoint path."""
 
+import json
+from pathlib import Path
+
 import pytest
 
+import litellm
+from litellm.llms.vertex_ai.common_utils import (
+    VertexAIModelRoute,
+    get_vertex_ai_model_route,
+)
 from litellm.llms.vertex_ai.vertex_model_garden.main import (
     _vertex_model_garden_model_id_in_json_body,
     create_vertex_url,
@@ -11,6 +19,7 @@ from litellm.llms.vertex_ai.vertex_model_garden.main import (
 @pytest.mark.parametrize(
     "model,expect_openapi_base",
     [
+        ("google/gemma-4-26b-a4b-it-maas", True),
         ("xai/grok-4.1-fast-reasoning", True),
         ("openai/foo/bar", True),
         ("5464397967697903616", False),
@@ -37,5 +46,41 @@ def test_create_vertex_url_openapi_vs_deployed_endpoint(
 
 
 def test_model_id_in_json_body_heuristic() -> None:
-    assert _vertex_model_garden_model_id_in_json_body("xai/grok-4.1-fast-reasoning") is True
+    assert (
+        _vertex_model_garden_model_id_in_json_body("google/gemma-4-26b-a4b-it-maas")
+        is True
+    )
+    assert (
+        _vertex_model_garden_model_id_in_json_body("xai/grok-4.1-fast-reasoning")
+        is True
+    )
     assert _vertex_model_garden_model_id_in_json_body("5464397967697903616") is False
+
+
+def test_gemma_4_26b_pricing_metadata_uses_vertex_model_garden_route():
+    model = "google/gemma-4-26b-a4b-it-maas"
+    litellm_model = f"vertex_ai/{model}"
+
+    assert get_vertex_ai_model_route(model=model) == VertexAIModelRoute.MODEL_GARDEN
+    assert (
+        get_vertex_ai_model_route(model="gemma/gemma-3-12b-it")
+        == VertexAIModelRoute.GEMMA
+    )
+
+    repo_root = Path(litellm.__file__).resolve().parents[1]
+    model_cost_files = [
+        repo_root / "model_prices_and_context_window.json",
+        repo_root / "litellm" / "model_prices_and_context_window_backup.json",
+    ]
+
+    for model_cost_file in model_cost_files:
+        model_cost = json.loads(model_cost_file.read_text(encoding="utf-8"))
+
+        assert "vertex_ai/gemma/gemma-4-26b-a4b-it-maas" not in model_cost
+        model_info = model_cost[litellm_model]
+
+        assert model_info["max_input_tokens"] == 262144
+        assert model_info["max_output_tokens"] == 128000
+        assert model_info["max_tokens"] == 128000
+        assert model_info["supports_function_calling"] is True
+        assert model_info["supports_tool_choice"] is True

tests/test_litellm/llms/vertex_ai/vertex_gemma_models/test_vertex_gemma_transformation.py

@@ -5,7 +5,6 @@ Maps to: litellm/llms/vertex_ai/vertex_gemma_models/transformation.py
 """
 
 import json
-from pathlib import Path
 from unittest.mock import AsyncMock, Mock, patch
 
 import pytest
@@ -21,40 +20,6 @@ def _reset_litellm_http_client_cache():
     in_memory_llm_clients_cache.flush_cache()
 
 
-def test_gemma_4_26b_pricing_metadata_uses_vertex_gemma_route():
-    from litellm.llms.vertex_ai.common_utils import (
-        VertexAIModelRoute,
-        get_vertex_ai_model_route,
-    )
-
-    model = "google/gemma-4-26b-a4b-it-maas"
-    litellm_model = f"vertex_ai/{model}"
-
-    assert get_vertex_ai_model_route(model=model) == VertexAIModelRoute.GEMMA
-    assert (
-        get_vertex_ai_model_route(model="gemma/gemma-3-12b-it")
-        == VertexAIModelRoute.GEMMA
-    )
-
-    repo_root = Path(litellm.__file__).resolve().parents[1]
-    model_cost_files = [
-        repo_root / "model_prices_and_context_window.json",
-        repo_root / "litellm" / "model_prices_and_context_window_backup.json",
-    ]
-
-    for model_cost_file in model_cost_files:
-        model_cost = json.loads(model_cost_file.read_text(encoding="utf-8"))
-
-        assert "vertex_ai/gemma/gemma-4-26b-a4b-it-maas" not in model_cost
-        model_info = model_cost[litellm_model]
-
-        assert model_info["max_input_tokens"] == 262144
-        assert model_info["max_output_tokens"] == 128000
-        assert model_info["max_tokens"] == 128000
-        assert model_info["supports_function_calling"] is True
-        assert model_info["supports_tool_choice"] is True
-
-
 class TestVertexGemmaCompletion:
     """Test completion flow for Vertex AI Gemma models using litellm.acompletion()"""