diff --git a/litellm/constants.py b/litellm/constants.py
index 871b7e5a80b..9a10a8b6f3a 100644
--- a/litellm/constants.py
+++ b/litellm/constants.py
@@ -177,6 +177,9 @@ DEFAULT_REASONING_EFFORT_MEDIUM_THINKING_BUDGET = int(
 DEFAULT_REASONING_EFFORT_HIGH_THINKING_BUDGET = int(
     os.getenv("DEFAULT_REASONING_EFFORT_HIGH_THINKING_BUDGET", 4096)
 )
+DEFAULT_REASONING_EFFORT_XHIGH_THINKING_BUDGET = int(
+    os.getenv("DEFAULT_REASONING_EFFORT_XHIGH_THINKING_BUDGET", 10000)
+)
 MAX_TOKEN_TRIMMING_ATTEMPTS = int(
     os.getenv("MAX_TOKEN_TRIMMING_ATTEMPTS", 10)
 )  # Maximum number of attempts to trim the message
diff --git a/litellm/llms/anthropic/chat/transformation.py b/litellm/llms/anthropic/chat/transformation.py
index c5041e21c4a..4e5a7d69043 100644
--- a/litellm/llms/anthropic/chat/transformation.py
+++ b/litellm/llms/anthropic/chat/transformation.py
@@ -13,6 +13,7 @@ from litellm.constants import (
     DEFAULT_REASONING_EFFORT_LOW_THINKING_BUDGET,
     DEFAULT_REASONING_EFFORT_MEDIUM_THINKING_BUDGET,
     DEFAULT_REASONING_EFFORT_MINIMAL_THINKING_BUDGET,
+    DEFAULT_REASONING_EFFORT_XHIGH_THINKING_BUDGET,
     RESPONSE_FORMAT_TOOL_NAME,
 )
 from litellm.litellm_core_utils.core_helpers import map_finish_reason
@@ -55,7 +56,10 @@ from litellm.types.utils import (
     CompletionTokensDetailsWrapper,
 )
 from litellm.types.utils import Message as LitellmMessage
-from litellm.types.utils import PromptTokensDetailsWrapper, ServerToolUse
+from litellm.types.utils import (
+    PromptTokensDetailsWrapper,
+    ServerToolUse,
+)
 from litellm.utils import (
     ModelResponse,
     Usage,
@@ -729,32 +733,30 @@ class AnthropicConfig(AnthropicModelInfo, BaseConfig):
     ) -> Optional[AnthropicThinkingParam]:
         if reasoning_effort is None or reasoning_effort == "none":
             return None
+        effort_to_budget = {
+            "minimal": DEFAULT_REASONING_EFFORT_MINIMAL_THINKING_BUDGET,
+            "low": DEFAULT_REASONING_EFFORT_LOW_THINKING_BUDGET,
+            "medium": DEFAULT_REASONING_EFFORT_MEDIUM_THINKING_BUDGET,
+            "high": DEFAULT_REASONING_EFFORT_HIGH_THINKING_BUDGET,
+            "xhigh": DEFAULT_REASONING_EFFORT_XHIGH_THINKING_BUDGET,
+        }
         if AnthropicConfig._is_claude_4_6_model(model):
+            budget_tokens = effort_to_budget.get(reasoning_effort)
+            if budget_tokens is not None:
+                return AnthropicThinkingParam(
+                    type="adaptive",
+                    budget_tokens=budget_tokens,
+                )
             return AnthropicThinkingParam(
                 type="adaptive",
             )
-        elif reasoning_effort == "low":
+        budget_tokens = effort_to_budget.get(reasoning_effort)
+        if budget_tokens is not None:
             return AnthropicThinkingParam(
                 type="enabled",
-                budget_tokens=DEFAULT_REASONING_EFFORT_LOW_THINKING_BUDGET,
+                budget_tokens=budget_tokens,
             )
-        elif reasoning_effort == "medium":
-            return AnthropicThinkingParam(
-                type="enabled",
-                budget_tokens=DEFAULT_REASONING_EFFORT_MEDIUM_THINKING_BUDGET,
-            )
-        elif reasoning_effort == "high":
-            return AnthropicThinkingParam(
-                type="enabled",
-                budget_tokens=DEFAULT_REASONING_EFFORT_HIGH_THINKING_BUDGET,
-            )
-        elif reasoning_effort == "minimal":
-            return AnthropicThinkingParam(
-                type="enabled",
-                budget_tokens=DEFAULT_REASONING_EFFORT_MINIMAL_THINKING_BUDGET,
-            )
-        else:
-            raise ValueError(f"Unmapped reasoning effort: {reasoning_effort}")
+        raise ValueError(f"Unmapped reasoning effort: {reasoning_effort}")
 
     def _extract_json_schema_from_response_format(
         self, value: Optional[dict]
@@ -1014,6 +1016,7 @@ class AnthropicConfig(AnthropicModelInfo, BaseConfig):
                         "minimal": "low",
                         "medium": "medium",
                         "high": "high",
+                        "xhigh": "max",
                         "max": "max",
                     }
                     mapped_effort = effort_map.get(value, value)
diff --git a/litellm/model_prices_and_context_window_backup.json b/litellm/model_prices_and_context_window_backup.json
index f52288ea72a..cbd64a178b8 100644
--- a/litellm/model_prices_and_context_window_backup.json
+++ b/litellm/model_prices_and_context_window_backup.json
@@ -16289,7 +16289,7 @@
         "cache_read_input_token_cost": 3e-08,
         "input_cost_per_audio_token": 1e-06,
         "input_cost_per_token": 3e-07,
-        "litellm_provider": "vertex_ai-language-models",
+        "litellm_provider": "gemini",
         "max_audio_length_hours": 8.4,
         "max_audio_per_prompt": 1,
         "supports_reasoning": false,
diff --git a/tests/litellm/llms/anthropic/test_anthropic_reasoning_effort.py b/tests/litellm/llms/anthropic/test_anthropic_reasoning_effort.py
index 98ae7148c77..305555de0d5 100644
--- a/tests/litellm/llms/anthropic/test_anthropic_reasoning_effort.py
+++ b/tests/litellm/llms/anthropic/test_anthropic_reasoning_effort.py
@@ -28,12 +28,28 @@ class TestMapReasoningEffort:
             reasoning_effort="low", model="claude-opus-4-6"
         )
         assert result["type"] == "adaptive"
+        assert result["budget_tokens"] == 1024
 
     def test_opus_4_6_returns_adaptive_for_high(self):
         result = AnthropicConfig._map_reasoning_effort(
             reasoning_effort="high", model="claude-opus-4-6"
         )
         assert result["type"] == "adaptive"
+        assert result["budget_tokens"] == 4096
+
+    def test_opus_4_6_returns_adaptive_for_medium(self):
+        result = AnthropicConfig._map_reasoning_effort(
+            reasoning_effort="medium", model="claude-opus-4-6"
+        )
+        assert result["type"] == "adaptive"
+        assert result["budget_tokens"] == 2048
+
+    def test_opus_4_6_returns_adaptive_for_minimal(self):
+        result = AnthropicConfig._map_reasoning_effort(
+            reasoning_effort="minimal", model="claude-opus-4-6"
+        )
+        assert result["type"] == "adaptive"
+        assert result["budget_tokens"] == 128
 
     def test_other_model_low_returns_enabled_with_budget(self):
         result = AnthropicConfig._map_reasoning_effort(
@@ -62,3 +78,17 @@ class TestMapReasoningEffort:
             reasoning_effort="none", model="claude-4-sonnet-20250514"
         )
         assert result is None
+
+    def test_opus_4_6_returns_adaptive_with_budget_for_xhigh(self):
+        result = AnthropicConfig._map_reasoning_effort(
+            reasoning_effort="xhigh", model="claude-opus-4-6"
+        )
+        assert result["type"] == "adaptive"
+        assert result["budget_tokens"] == 10000
+
+    def test_other_model_xhigh_returns_enabled_with_budget(self):
+        result = AnthropicConfig._map_reasoning_effort(
+            reasoning_effort="xhigh", model="claude-4-sonnet-20250514"
+        )
+        assert result["type"] == "enabled"
+        assert result["budget_tokens"] == 10000