fix(ollama): report prompt cache hits as cached_tokens

Map prompt_eval_cached_count to prompt_tokens_details.cached_tokens for chat and completion, streaming and non-streaming, so cached prompt tokens are accounted without double billing.

litellm/llms/ollama/chat/transformation.py

@@ -388,6 +388,7 @@ class OllamaChatConfig(BaseConfig):
             "eval_count",
             litellm.token_counter(text=response_json["message"]["content"]),
         )
+        cached_tokens: Final = response_json.get("prompt_eval_cached_count", 0)
         setattr(
             model_response,
             "usage",
@@ -395,6 +396,7 @@ class OllamaChatConfig(BaseConfig):
                 prompt_tokens=prompt_tokens,
                 completion_tokens=completion_tokens,
                 total_tokens=prompt_tokens + completion_tokens,
+                prompt_tokens_details={"cached_tokens": cached_tokens},
             ),
         )
         return model_response
@@ -420,10 +422,12 @@ def _done_chunk_usage(chunk: Mapping[str, object]) -> ChatCompletionUsageBlock |
     eval_count: Final = chunk.get("eval_count")
     if chunk.get("done") is not True or not isinstance(prompt_eval_count, int) or not isinstance(eval_count, int):
         return None
+    cached_tokens: Final = chunk.get("prompt_eval_cached_count", 0)
     return ChatCompletionUsageBlock(
         prompt_tokens=prompt_eval_count,
         completion_tokens=eval_count,
         total_tokens=prompt_eval_count + eval_count,
+        prompt_tokens_details={"cached_tokens": cached_tokens},
     )
 
 

litellm/llms/ollama/completion/transformation.py

@@ -392,6 +392,7 @@ class OllamaConfig(BaseConfig):
         completion_tokens: Final = response_json.get(
             "eval_count", len((response_json.get("message") or {}).get("content", ""))
         )
+        cached_tokens: Final = response_json.get("prompt_eval_cached_count", 0)
         setattr(
             model_response,
             "usage",
@@ -399,6 +400,7 @@ class OllamaConfig(BaseConfig):
                 prompt_tokens=prompt_tokens,
                 completion_tokens=completion_tokens,
                 total_tokens=prompt_tokens + completion_tokens,
+                prompt_tokens_details={"cached_tokens": cached_tokens},
             ),
         )
         return model_response
@@ -589,10 +591,12 @@ class OllamaTextCompletionResponseIterator(BaseModelResponseIterator):
 
                 usage: ChatCompletionUsageBlock | None = None
                 if prompt_eval_count is not None and eval_count is not None:
+                    cached_tokens: Final = chunk.get("prompt_eval_cached_count", 0)
                     usage = ChatCompletionUsageBlock(
                         prompt_tokens=prompt_eval_count,
                         completion_tokens=eval_count,
                         total_tokens=prompt_eval_count + eval_count,
+                        prompt_tokens_details={"cached_tokens": cached_tokens},
                     )
                 if self.held_content:
                     return self._flush_held_content(usage)

tests/unit/llms/ollama/test_ollama_chat_transformation.py

@@ -969,6 +969,24 @@ class TestOllamaStreamingUsage:
         assert result.usage is not None
         assert (result.usage.prompt_tokens, result.usage.completion_tokens, result.usage.total_tokens) == (100, 50, 150)
 
+    def test_done_chunk_reports_cached_tokens_ollama_sent(self):
+        result: Final = self._parse(
+            {
+                "model": "qwen3:0.6b",
+                "message": {"role": "assistant", "content": ""},
+                "done": True,
+                "done_reason": "stop",
+                "prompt_eval_count": 6024,
+                "prompt_eval_cached_count": 6016,
+                "eval_count": 50,
+            }
+        )
+
+        assert result.usage is not None
+        assert result.usage.prompt_tokens == 6024
+        assert result.usage.prompt_tokens_details is not None
+        assert result.usage.prompt_tokens_details.cached_tokens == 6016
+
     def test_done_chunk_without_counts_reports_no_usage_instead_of_zeros(self):
         result = self._parse(
             {
@@ -993,6 +1011,42 @@ class TestOllamaStreamingUsage:
         assert result.usage is None
 
 
+def test_non_streaming_reports_cached_tokens_ollama_sent() -> None:
+    config: Final = OllamaChatConfig()
+
+    mock_response: Final = MagicMock()
+    mock_response.json.return_value = {
+        "model": "qwen3:0.6b",
+        "message": {"role": "assistant", "content": "Hi"},
+        "done": True,
+        "prompt_eval_count": 6024,
+        "prompt_eval_cached_count": 6016,
+        "eval_count": 50,
+    }
+
+    model_response: Final = ModelResponse()
+    model_response.choices = [Choices(message=Message(content=""), index=0)]
+
+    result: Final = config.transform_response(
+        model="qwen3:0.6b",
+        raw_response=mock_response,
+        model_response=model_response,
+        logging_obj=MagicMock(),
+        request_data={},
+        messages=[{"role": "user", "content": "Hi"}],
+        optional_params={},
+        litellm_params={},
+        encoding=None,
+        api_key=None,
+        json_mode=False,
+    )
+
+    assert result.usage is not None
+    assert result.usage.prompt_tokens == 6024
+    assert result.usage.prompt_tokens_details is not None
+    assert result.usage.prompt_tokens_details.cached_tokens == 6016
+
+
 def test_get_ollama_params():
     try:
         converted_params = get_optional_params(

tests/unit/llms/ollama/test_ollama_completion_transformation.py

@@ -65,6 +65,38 @@ class TestOllamaConfig:
         assert result["usage"]["completion_tokens"] == 5
         assert result["usage"]["total_tokens"] == 15
 
+    def test_transform_response_reports_cached_tokens_ollama_sent(self):
+        config: Final = OllamaConfig()
+        raw_response: Final = MagicMock()
+        raw_response.json.return_value = {
+            "response": "Hello",
+            "prompt_eval_count": 6024,
+            "prompt_eval_cached_count": 6016,
+            "eval_count": 5,
+        }
+        model_response: Final = ModelResponse(
+            id="test_id",
+            choices=[{"message": Message(content="")}],
+        )
+        mock_encoding: Final = MagicMock()
+        mock_encoding.encode.return_value = [1, 2, 3]
+
+        result: Final = config.transform_response(
+            model="llama2",
+            raw_response=raw_response,
+            model_response=model_response,
+            logging_obj=MagicMock(),
+            request_data={},
+            messages=[],
+            optional_params={},
+            litellm_params={},
+            encoding=mock_encoding,
+        )
+
+        assert result["usage"]["prompt_tokens"] == 6024
+        assert result.usage.prompt_tokens_details is not None
+        assert result.usage.prompt_tokens_details.cached_tokens == 6016
+
     @patch("uuid.uuid4")
     def test_transform_response_json_function_call(self, mock_uuid4):
         # Setup mock UUID
@@ -711,6 +743,24 @@ class TestOllamaTextCompletionResponseIterator:
         assert result["usage"]["completion_tokens"] == 5
         assert result["usage"]["total_tokens"] == 15
 
+    def test_chunk_parser_done_chunk_reports_cached_tokens(self):
+        iterator: Final = OllamaTextCompletionResponseIterator(
+            streaming_response=iter([]), sync_stream=True, json_mode=False
+        )
+        done_chunk: Final = {
+            "model": "llama2",
+            "created_at": "2025-08-06T14:34:31.5276077Z",
+            "response": "",
+            "done": True,
+            "prompt_eval_count": 6024,
+            "prompt_eval_cached_count": 6016,
+            "eval_count": 5,
+        }
+        result: Final = iterator.chunk_parser(done_chunk)
+        assert result["usage"] is not None
+        assert result["usage"]["prompt_tokens"] == 6024
+        assert result["usage"]["prompt_tokens_details"]["cached_tokens"] == 6016
+
     @pytest.mark.parametrize(
         ("response_chunks", "expected_text", "expected_tool_name", "expected_finish_reason"),
         [