diff --git a/litellm/litellm_core_utils/llm_response_utils/convert_dict_to_response.py b/litellm/litellm_core_utils/llm_response_utils/convert_dict_to_response.py
index 9ea730a873f..0d4bb9c8351 100644
--- a/litellm/litellm_core_utils/llm_response_utils/convert_dict_to_response.py
+++ b/litellm/litellm_core_utils/llm_response_utils/convert_dict_to_response.py
@@ -231,15 +231,7 @@ async def convert_to_streaming_response_async(
     model_response_object.choices = choice_list
 
     if "usage" in response_object and response_object["usage"] is not None:
-        setattr(
-            model_response_object,
-            "usage",
-            Usage(
-                completion_tokens=response_object["usage"].get("completion_tokens", 0),
-                prompt_tokens=response_object["usage"].get("prompt_tokens", 0),
-                total_tokens=response_object["usage"].get("total_tokens", 0),
-            ),
-        )
+        setattr(model_response_object, "usage", Usage(**response_object["usage"]))
 
     if "id" in response_object:
         model_response_object.id = response_object["id"]
@@ -325,10 +317,7 @@ def convert_to_streaming_response(
     model_response_object.choices = choice_list
 
     if "usage" in response_object and response_object["usage"] is not None:
-        setattr(model_response_object, "usage", Usage())
-        model_response_object.usage.completion_tokens = response_object["usage"].get("completion_tokens", 0)
-        model_response_object.usage.prompt_tokens = response_object["usage"].get("prompt_tokens", 0)
-        model_response_object.usage.total_tokens = response_object["usage"].get("total_tokens", 0)
+        setattr(model_response_object, "usage", Usage(**response_object["usage"]))
 
     if "id" in response_object:
         model_response_object.id = response_object["id"]
diff --git a/tests/unit/litellm_core_utils/llm_response_utils/test_convert_dict_to_response.py b/tests/unit/litellm_core_utils/llm_response_utils/test_convert_dict_to_response.py
index 8e46ae21de6..557f3233dd1 100644
--- a/tests/unit/litellm_core_utils/llm_response_utils/test_convert_dict_to_response.py
+++ b/tests/unit/litellm_core_utils/llm_response_utils/test_convert_dict_to_response.py
@@ -1,12 +1,15 @@
 from typing import Final
 
 import pytest
+from pydantic import JsonValue
 
 from litellm.constants import RESPONSE_FORMAT_TOOL_NAME
 from litellm.litellm_core_utils.llm_response_utils.convert_dict_to_response import (
     _handle_invalid_parallel_tool_calls,
     _should_convert_tool_call_to_json_mode,
     convert_to_model_response_object,
+    convert_to_streaming_response,
+    convert_to_streaming_response_async,
 )
 from litellm.types.utils import (
     ChatCompletionMessageCustomToolCall,
@@ -15,6 +18,80 @@ from litellm.types.utils import (
     ModelResponse,
 )
 
+
+@pytest.mark.parametrize("use_async", (False, True), ids=("sync", "async"))
+@pytest.mark.parametrize("content", ("done", "cached response text"), ids=("single", "sliced"))
+@pytest.mark.asyncio
+async def test_cached_streaming_replay_preserves_complete_usage(content: str, use_async: bool) -> None:
+    usage: Final = {
+        "prompt_tokens": 100,
+        "completion_tokens": 40,
+        "total_tokens": 140,
+        "prompt_tokens_details": {"cached_tokens": 60, "audio_tokens": 5},
+        "completion_tokens_details": {
+            "reasoning_tokens": 20,
+            "audio_tokens": 3,
+            "accepted_prediction_tokens": 2,
+            "rejected_prediction_tokens": 1,
+        },
+        "server_tool_use": {"web_search_requests": 1},
+        "provider_usage": {"custom_units": 2},
+    }
+    response: Final = {
+        "id": "chatcmpl-cache-regression",
+        "created": 1,
+        "model": "cache-test-model",
+        "choices": [{"message": {"role": "assistant", "content": content}, "finish_reason": "stop"}],
+        "usage": usage,
+    }
+    chunks: Final = (
+        [chunk async for chunk in convert_to_streaming_response_async(response)]
+        if use_async
+        else list(convert_to_streaming_response(response))
+    )
+
+    assert "".join(chunk.choices[0].delta.content for chunk in chunks) == content
+    assert chunks[-1].model_dump(exclude_none=True)["usage"] == usage
+    assert all(getattr(chunk, "usage", None) is None for chunk in chunks[:-1])
+    assert chunks[-1].choices[0].finish_reason == "stop"
+
+
+@pytest.mark.parametrize("use_async", (False, True), ids=("sync", "async"))
+@pytest.mark.parametrize(
+    ("usage_fields", "expected_usage"),
+    (
+        ({}, None),
+        ({"usage": None}, None),
+        ({"usage": {}}, {"prompt_tokens": 0, "completion_tokens": 0, "total_tokens": 0}),
+        ({"usage": {"prompt_tokens": 5}}, {"prompt_tokens": 5, "completion_tokens": 0, "total_tokens": 0}),
+        (
+            {"usage": {"prompt_tokens": 5, "completion_tokens": 3, "total_tokens": 8}},
+            {"prompt_tokens": 5, "completion_tokens": 3, "total_tokens": 8},
+        ),
+    ),
+    ids=("missing", "null", "empty", "partial", "totals-only"),
+)
+@pytest.mark.asyncio
+async def test_cached_streaming_replay_preserves_legacy_usage(
+    usage_fields: dict[str, JsonValue], expected_usage: dict[str, int] | None, use_async: bool
+) -> None:
+    response: Final = {
+        "id": "chatcmpl-cache-regression",
+        "created": 1,
+        "model": "cache-test-model",
+        "choices": [{"message": {"role": "assistant", "content": "done"}, "finish_reason": "stop"}],
+        **usage_fields,
+    }
+    chunks: Final = (
+        [chunk async for chunk in convert_to_streaming_response_async(response)]
+        if use_async
+        else list(convert_to_streaming_response(response))
+    )
+
+    assert len(chunks) == 1
+    assert chunks[0].model_dump(exclude_none=True).get("usage") == expected_usage
+
+
 OPENAI_CUSTOM_TOOL_CALL_RESPONSE = {
     "id": "chatcmpl-abc",
     "created": 1784657740,
@@ -33,7 +110,7 @@ OPENAI_CUSTOM_TOOL_CALL_RESPONSE = {
                         "type": "custom",
                         "custom": {
                             "name": "ApplyPatch",
-                            "input": "*** Begin Patch\n*** Update File: main.py\n@@\n+def hello():\n+    print(\"Hello\")\n*** End Patch\n",
+                            "input": '*** Begin Patch\n*** Update File: main.py\n@@\n+def hello():\n+    print("Hello")\n*** End Patch\n',
                         },
                     }
                 ],