diff --git a/litellm/llms/ollama/chat/transformation.py b/litellm/llms/ollama/chat/transformation.py
index fb2acc94122..cdc0ad00786 100644
--- a/litellm/llms/ollama/chat/transformation.py
+++ b/litellm/llms/ollama/chat/transformation.py
@@ -28,7 +28,7 @@ from litellm.types.llms.openai import (
 )
 from litellm.types.utils import ModelResponse, ModelResponseStream
 
-from ..common_utils import OllamaError
+from ..common_utils import OllamaError, think_from_reasoning_effort
 
 if TYPE_CHECKING:
     from litellm.litellm_core_utils.litellm_logging import Logging as _LiteLLMLoggingObj
@@ -170,13 +170,11 @@ class OllamaChatConfig(BaseConfig):
             if param == "response_format" and isinstance(value, dict) and value.get("type") == "json_schema":
                 if value.get("json_schema") and value["json_schema"].get("schema"):
                     optional_params["format"] = value["json_schema"]["schema"]
-            if param == "reasoning_effort" and value is not None:
-                effort: Final = value.get("effort") if isinstance(value, Mapping) else value
-                if effort is not None:
-                    if model.startswith("gpt-oss"):
-                        optional_params["think"] = effort
-                    else:
-                        optional_params["think"] = effort in {"low", "medium", "high"}
+            if (
+                param == "reasoning_effort"
+                and (think := think_from_reasoning_effort(model, cast(object, value))) is not None
+            ):
+                optional_params["think"] = think
             ### FUNCTION CALLING LOGIC ###
             # Ollama 0.4+ supports native tool calling - pass tools directly
             # and let Ollama handle model capability detection
diff --git a/litellm/llms/ollama/common_utils.py b/litellm/llms/ollama/common_utils.py
index 9f46cbc5cd5..96f28b1ed53 100644
--- a/litellm/llms/ollama/common_utils.py
+++ b/litellm/llms/ollama/common_utils.py
@@ -1,5 +1,6 @@
 import base64
 import io
+from collections.abc import Mapping
 from typing import Any, Final
 
 import httpx
@@ -8,6 +9,15 @@ from litellm import verbose_logger
 from litellm.llms.base_llm.chat.transformation import BaseLLMException
 
 
+def think_from_reasoning_effort(model: str, reasoning_effort: object) -> str | bool | None:
+    effort: Final = reasoning_effort.get("effort") if isinstance(reasoning_effort, Mapping) else reasoning_effort
+    if not isinstance(effort, str):
+        return None
+    if model.startswith("gpt-oss"):
+        return effort
+    return effort in {"low", "medium", "high"}
+
+
 class OllamaError(BaseLLMException):
     def __init__(self, status_code: int, message: str, headers: dict | httpx.Headers):
         super().__init__(status_code=status_code, message=message, headers=headers)
diff --git a/litellm/llms/ollama/completion/transformation.py b/litellm/llms/ollama/completion/transformation.py
index 7d2bb726f5a..b0cb2d4ed27 100644
--- a/litellm/llms/ollama/completion/transformation.py
+++ b/litellm/llms/ollama/completion/transformation.py
@@ -1,7 +1,7 @@
 import json
 import time
-from collections.abc import AsyncIterator, Iterator, Mapping
-from typing import TYPE_CHECKING, Any, Final
+from collections.abc import AsyncIterator, Iterator
+from typing import TYPE_CHECKING, Any, Final, cast
 
 from httpx._models import Headers, Response
 from pydantic import BaseModel, ConfigDict, ValidationError
@@ -33,7 +33,7 @@ from litellm.types.utils import (
     StreamingChoices,
 )
 
-from ..common_utils import OllamaError, OllamaModelInfo, _convert_image
+from ..common_utils import OllamaError, OllamaModelInfo, _convert_image, think_from_reasoning_effort
 
 if TYPE_CHECKING:
     from litellm.litellm_core_utils.litellm_logging import Logging as _LiteLLMLoggingObj
@@ -214,13 +214,11 @@ class OllamaConfig(BaseConfig):
                 optional_params["frequency_penalty"] = value
             elif param == "stop":
                 optional_params["stop"] = value
-            elif param == "reasoning_effort" and value is not None:
-                effort: Final = value.get("effort") if isinstance(value, Mapping) else value
-                if effort is not None:
-                    if model.startswith("gpt-oss"):
-                        optional_params["think"] = effort
-                    else:
-                        optional_params["think"] = effort in {"low", "medium", "high"}
+            elif (
+                param == "reasoning_effort"
+                and (think := think_from_reasoning_effort(model, cast(object, value))) is not None
+            ):
+                optional_params["think"] = think
             elif param == "response_format" and isinstance(value, dict):
                 if value["type"] == "json_object":
                     optional_params["format"] = "json"