diff --git a/litellm/llms/anthropic/experimental_pass_through/adapters/transformation.py b/litellm/llms/anthropic/experimental_pass_through/adapters/transformation.py
index 109017bda27..ca90df2ff75 100644
--- a/litellm/llms/anthropic/experimental_pass_through/adapters/transformation.py
+++ b/litellm/llms/anthropic/experimental_pass_through/adapters/transformation.py
@@ -18,6 +18,22 @@ TOOL_NAME_PREFIX_LENGTH: Final = OPENAI_MAX_TOOL_NAME_LENGTH - TOOL_NAME_HASH_LE
 PROVIDERS_PROXYING_AN_UNKNOWN_BACKEND: Final = frozenset({"litellm_proxy"})
 
 
+_ANTHROPIC_TOOL_SCHEMA_KEYS: Final = frozenset(
+    {"name", "type", "input_schema", "description", "cache_control", "strict"}
+)
+
+
+def _is_openai_function_tool(tool: Mapping[str, object]) -> bool:
+    return tool.get("type") == "function" and "function" in tool
+
+
+def _is_provider_native_tool_dict(tool: Mapping[str, object]) -> bool:
+    if len(tool) != 1:
+        return False
+    key, value = next(iter(tool.items()))
+    return key not in _ANTHROPIC_TOOL_SCHEMA_KEYS and isinstance(value, dict)
+
+
 def truncate_tool_name(name: str) -> str:
     """
     Truncate tool names that exceed OpenAI's 64-character limit.
@@ -770,6 +786,10 @@ class LiteLLMAnthropicMessagesAdapter:
                 new_tools.append(tool)
                 continue
 
+            if _is_openai_function_tool(tool) or _is_provider_native_tool_dict(tool):
+                new_tools.append(cast(ChatCompletionToolParam, tool))  # cast-ok: passed through verbatim to provider
+                continue
+
             raw_name = tool.get("name")
             if raw_name is None or (isinstance(raw_name, str) and not str(raw_name).strip()):
                 original_name = f"litellm_unnamed_tool_{idx}"
diff --git a/tests/test_litellm/llms/anthropic/experimental_pass_through/adapters/test_anthropic_experimental_pass_through_adapters_transformation.py b/tests/test_litellm/llms/anthropic/experimental_pass_through/adapters/test_anthropic_experimental_pass_through_adapters_transformation.py
index ee09baf28b6..7073d702db4 100644
--- a/tests/test_litellm/llms/anthropic/experimental_pass_through/adapters/test_anthropic_experimental_pass_through_adapters_transformation.py
+++ b/tests/test_litellm/llms/anthropic/experimental_pass_through/adapters/test_anthropic_experimental_pass_through_adapters_transformation.py
@@ -16,6 +16,7 @@ from litellm.litellm_core_utils.prompt_templates.factory import (
 )
 from litellm.llms.anthropic.experimental_pass_through.adapters.transformation import (
     OPENAI_MAX_TOOL_NAME_LENGTH,
+    AnthropicAdapter,
     LiteLLMAnthropicMessagesAdapter,
     create_tool_name_mapping,
     truncate_tool_name,
@@ -2307,6 +2308,53 @@ def test_translate_anthropic_tools_to_openai_fills_missing_tool_name():
     assert result[1]["function"]["name"] == "litellm_unnamed_tool_1"
 
 
+def test_translate_anthropic_tools_to_openai_passes_provider_native_tool_dicts_through():
+    """Deployment-level provider-native tools (e.g. Gemini googleMaps) must reach the provider transformation verbatim (LIT-6286)."""
+    tools = [
+        {"googleMaps": {}},
+        {"googleSearch": {}},
+        {
+            "name": "get_weather",
+            "input_schema": {"type": "object", "properties": {"location": {"type": "string"}}},
+        },
+    ]
+    adapter = LiteLLMAnthropicMessagesAdapter()
+    result, tool_name_mapping = adapter.translate_anthropic_tools_to_openai(tools=tools, model=None)
+    assert result[0] == {"googleMaps": {}}
+    assert result[1] == {"googleSearch": {}}
+    assert result[2]["function"]["name"] == "get_weather"
+    assert tool_name_mapping == {}
+
+
+def test_translate_anthropic_tools_to_openai_passes_openai_function_tools_through():
+    """A tool already in OpenAI function format must pass through unchanged instead of becoming litellm_unnamed_tool_N."""
+    openai_tool = {
+        "type": "function",
+        "function": {
+            "name": "get_weather",
+            "parameters": {"type": "object", "properties": {"location": {"type": "string"}}},
+        },
+    }
+    adapter = LiteLLMAnthropicMessagesAdapter()
+    result, _ = adapter.translate_anthropic_tools_to_openai(tools=[openai_tool], model=None)
+    assert result == [openai_tool]
+
+
+def test_translate_completion_input_params_keeps_provider_native_tools():
+    """/v1/messages request translation must keep router-merged provider-native tools in kwargs['tools'] (LIT-6286)."""
+    adapter = AnthropicAdapter()
+    translated = adapter.translate_completion_input_params(
+        {
+            "model": "gemini/gemini-2.5-flash",
+            "max_tokens": 1024,
+            "messages": [{"role": "user", "content": "coffee shops near Union Square"}],
+            "tools": [{"googleMaps": {}}],
+        }
+    )
+    assert translated is not None
+    assert translated["tools"] == [{"googleMaps": {}}]
+
+
 def test_translate_openai_content_to_anthropic_reasoning_content_without_thinking_blocks():
     """
     Test that reasoning_content is converted to thinking block when thinking_blocks is not present.