fix(gemini): read the Flash tier off the version too, not "gemini-3"

`_map_reasoning_effort_to_thinking_level` and `_map_thinking_param` each
re-derived the Flash tier with the same substring the outer gate just
stopped using, so a rolling alias reached the Gemini 3 branch and was then
demoted inside it: `reasoning_effort="minimal"` on `gemini-flash-latest`
returned `thinkingLevel="low"`, and `"none"` / `"disable"` likewise, so the
caller silently got more thinking than it asked for. Closes #18245.

Both sites now share `_is_gemini_3_flash_or_newer`, which reuses the major
version read and so covers Gemini 4 Flash without a code change. Flash-Lite
counts; Pro does not, since MINIMAL is a Flash-tier level. Pro keeps "low"
for minimal and "high" for medium, unchanged.

litellm/llms/vertex_ai/gemini/vertex_and_google_ai_studio_gemini.py

@@ -282,6 +282,16 @@ class VertexGeminiConfig(VertexAIBaseConfig, BaseConfig):
             return int(major_version.group(1)) >= 3
         return model.split("/")[-1] in GEMINI_ROLLING_LATEST_ALIASES
 
+    @staticmethod
+    def _is_gemini_3_flash_or_newer(model: str | None) -> bool:
+        """
+        Check if the model is a Gemini 3 or newer Flash, the tier that accepts
+        the MINIMAL thinking level. Flash-Lite counts, Pro does not.
+        """
+        if not model:
+            return False
+        return VertexGeminiConfig._is_gemini_3_or_newer(model) and "flash" in model.lower()
+
     @staticmethod
     def _forward_gemini_function_call_id(model: str) -> bool:
         """
@@ -866,10 +876,7 @@ class VertexGeminiConfig(VertexAIBaseConfig, BaseConfig):
         Returns:
             GeminiThinkingConfig with thinkingLevel and includeThoughts
         """
-        # Check if this is gemini-3-flash which supports MINIMAL thinking level
-        # Covers gemini-3-flash, gemini-3-flash-preview, gemini-3.1-flash, gemini-3.1-flash-lite-preview,
-        # gemini-3.5-flash, and any future 3.x-flash variants.
-        is_gemini3flash: Final = model and ("flash" in model.lower() and "gemini-3" in model.lower())
+        is_gemini3flash: Final = VertexGeminiConfig._is_gemini_3_flash_or_newer(model)
         is_gemini31pro: Final = model and ("gemini-3.1-pro-preview" in model.lower())
         if reasoning_effort == "minimal":
             if is_gemini3flash:
@@ -963,7 +970,7 @@ class VertexGeminiConfig(VertexAIBaseConfig, BaseConfig):
                     params["includeThoughts"] = True
                     # Follow provider defaults unless explicitly opted into legacy behavior.
                     if litellm.enable_gemini_default_thinking_level_low is True:
-                        is_gemini3flash: Final = "gemini-3" in model.lower() and "flash" in model.lower()
+                        is_gemini3flash: Final = VertexGeminiConfig._is_gemini_3_flash_or_newer(model)
                         params["thinkingLevel"] = "minimal" if is_gemini3flash else "low"
             else:
                 # Thinking disabled

tests/test_litellm/llms/vertex_ai/gemini/test_vertex_and_google_ai_studio_gemini.py

@@ -2349,6 +2349,152 @@ def test_thought_signature_fallback_for_rolling_latest_alias():
     assert not any("thoughtSignature" in part for part in parts)
 
 
+def test_is_gemini_3_flash_or_newer():
+    from litellm.llms.vertex_ai.gemini.vertex_and_google_ai_studio_gemini import (
+        VertexGeminiConfig,
+    )
+
+    assert VertexGeminiConfig._is_gemini_3_flash_or_newer("gemini-3-flash") == True
+    assert (
+        VertexGeminiConfig._is_gemini_3_flash_or_newer("gemini-3-flash-preview") == True
+    )
+    assert VertexGeminiConfig._is_gemini_3_flash_or_newer("gemini-3.1-flash") == True
+    assert VertexGeminiConfig._is_gemini_3_flash_or_newer("gemini-3.5-flash") == True
+    assert (
+        VertexGeminiConfig._is_gemini_3_flash_or_newer(
+            "gemini-3.1-flash-lite-preview"
+        )
+        == True
+    )
+
+    # Rolling aliases resolving to a Flash tier
+    assert VertexGeminiConfig._is_gemini_3_flash_or_newer("gemini-flash-latest") == True
+    assert (
+        VertexGeminiConfig._is_gemini_3_flash_or_newer("gemini-flash-lite-latest")
+        == True
+    )
+    assert (
+        VertexGeminiConfig._is_gemini_3_flash_or_newer("gemini/gemini-flash-latest")
+        == True
+    )
+    assert (
+        VertexGeminiConfig._is_gemini_3_flash_or_newer("vertex_ai/gemini-flash-latest")
+        == True
+    )
+
+    # Later major versions, without a code change
+    assert VertexGeminiConfig._is_gemini_3_flash_or_newer("gemini-4-flash") == True
+    assert VertexGeminiConfig._is_gemini_3_flash_or_newer("gemini/gemini-10-flash") == True
+
+    # MINIMAL is a Flash-tier level, so Pro is excluded
+    assert VertexGeminiConfig._is_gemini_3_flash_or_newer("gemini-pro-latest") == False
+    assert (
+        VertexGeminiConfig._is_gemini_3_flash_or_newer("gemini-3-pro-preview") == False
+    )
+
+    # Older majors are excluded
+    assert VertexGeminiConfig._is_gemini_3_flash_or_newer("gemini-2.5-flash") == False
+    assert (
+        VertexGeminiConfig._is_gemini_3_flash_or_newer(
+            "gemini-2.5-flash-native-audio-latest"
+        )
+        == False
+    )
+
+    # Edge cases
+    assert VertexGeminiConfig._is_gemini_3_flash_or_newer(None) == False
+    assert VertexGeminiConfig._is_gemini_3_flash_or_newer("") == False
+
+
+def test_reasoning_effort_minimal_reaches_minimal_on_rolling_flash_alias():
+    """
+    `reasoning_effort="minimal"` must reach `thinkingLevel="minimal"` on the
+    Flash tier. `gemini-flash-latest` serves Gemini 3.x Flash, so it was
+    demoted to "low" and the caller silently got more thinking than it asked
+    for.
+    """
+    from litellm.llms.vertex_ai.gemini.vertex_and_google_ai_studio_gemini import (
+        VertexGeminiConfig,
+    )
+
+    v = VertexGeminiConfig()
+
+    for model in [
+        "gemini-flash-latest",
+        "gemini/gemini-flash-latest",
+        "gemini-flash-lite-latest",
+        "gemini-3.5-flash",
+    ]:
+        result = v.map_openai_params(
+            non_default_params={"reasoning_effort": "minimal"},
+            optional_params={},
+            model=model,
+            drop_params=False,
+        )
+        assert result["thinkingConfig"]["thinkingLevel"] == "minimal", model
+        assert result["thinkingConfig"]["includeThoughts"] is True
+
+    # Pro keeps "low" — MINIMAL is a Flash-tier level
+    result = v.map_openai_params(
+        non_default_params={"reasoning_effort": "minimal"},
+        optional_params={},
+        model="gemini-pro-latest",
+        drop_params=False,
+    )
+    assert result["thinkingConfig"]["thinkingLevel"] == "low"
+
+
+def test_reasoning_effort_medium_reaches_medium_on_rolling_flash_alias():
+    from litellm.llms.vertex_ai.gemini.vertex_and_google_ai_studio_gemini import (
+        VertexGeminiConfig,
+    )
+
+    v = VertexGeminiConfig()
+
+    result = v.map_openai_params(
+        non_default_params={"reasoning_effort": "medium"},
+        optional_params={},
+        model="gemini-flash-latest",
+        drop_params=False,
+    )
+    assert result["thinkingConfig"]["thinkingLevel"] == "medium"
+
+    # Pro (other than 3.1) still escalates to "high"
+    result = v.map_openai_params(
+        non_default_params={"reasoning_effort": "medium"},
+        optional_params={},
+        model="gemini-pro-latest",
+        drop_params=False,
+    )
+    assert result["thinkingConfig"]["thinkingLevel"] == "high"
+
+
+def test_default_thinking_level_reaches_minimal_on_rolling_flash_alias(monkeypatch):
+    """
+    The `enable_gemini_default_thinking_level_low` opt-in reads the Flash tier
+    off the same helper, so a rolling alias is not demoted to "low" there
+    either.
+    """
+    import litellm
+    from litellm.llms.vertex_ai.gemini.vertex_and_google_ai_studio_gemini import (
+        VertexGeminiConfig,
+    )
+
+    monkeypatch.setattr(
+        litellm, "enable_gemini_default_thinking_level_low", True, raising=False
+    )
+
+    params = VertexGeminiConfig._map_thinking_param(
+        {"type": "enabled", "budget_tokens": 2048}, model="gemini-flash-latest"
+    )
+    assert params["thinkingLevel"] == "minimal"
+
+    params = VertexGeminiConfig._map_thinking_param(
+        {"type": "enabled", "budget_tokens": 2048}, model="gemini-pro-latest"
+    )
+    assert params["thinkingLevel"] == "low"
+
+
 def _tool_call_messages(tool_call_id: str):
     return [
         {"role": "user", "content": "hi"},