diff --git a/libs/community/langchain_community/chat_models/litellm.py b/libs/community/langchain_community/chat_models/litellm.py
index 36335afbd9b..c9f588b3d49 100644
--- a/libs/community/langchain_community/chat_models/litellm.py
+++ b/libs/community/langchain_community/chat_models/litellm.py
@@ -452,6 +452,7 @@ class ChatLiteLLM(BaseChatModel):
         params = {**params, **kwargs, "stream": True}
 
         default_chunk_class = AIMessageChunk
+        added_model_name = False
         for chunk in self.completion_with_retry(
             messages=message_dicts, run_manager=run_manager, **params
         ):
@@ -460,7 +461,15 @@ class ChatLiteLLM(BaseChatModel):
             if len(chunk["choices"]) == 0:
                 continue
             delta = chunk["choices"][0]["delta"]
+            usage = chunk.get("usage", {})
             chunk = _convert_delta_to_message_chunk(delta, default_chunk_class)
+            if isinstance(chunk, AIMessageChunk):
+                if not added_model_name:
+                    chunk.response_metadata = {
+                        "model_name": self.model_name or self.model
+                    }
+                    added_model_name = True
+                chunk.usage_metadata = _create_usage_metadata(usage)
             default_chunk_class = chunk.__class__
             cg_chunk = ChatGenerationChunk(message=chunk)
             if run_manager:
@@ -478,6 +487,7 @@ class ChatLiteLLM(BaseChatModel):
         params = {**params, **kwargs, "stream": True}
 
         default_chunk_class = AIMessageChunk
+        added_model_name = False
         async for chunk in await acompletion_with_retry(
             self, messages=message_dicts, run_manager=run_manager, **params
         ):
@@ -486,7 +496,15 @@ class ChatLiteLLM(BaseChatModel):
             if len(chunk["choices"]) == 0:
                 continue
             delta = chunk["choices"][0]["delta"]
+            usage = chunk.get("usage", {})
             chunk = _convert_delta_to_message_chunk(delta, default_chunk_class)
+            if isinstance(chunk, AIMessageChunk):
+                if not added_model_name:
+                    chunk.response_metadata = {
+                        "model_name": self.model_name or self.model
+                    }
+                    added_model_name = True
+                chunk.usage_metadata = _create_usage_metadata(usage)
             default_chunk_class = chunk.__class__
             cg_chunk = ChatGenerationChunk(message=chunk)
             if run_manager:
diff --git a/libs/community/tests/integration_tests/chat_models/test_litellm_standard.py b/libs/community/tests/integration_tests/chat_models/test_litellm_standard.py
index e7b753acf3f..d034ece43e4 100644
--- a/libs/community/tests/integration_tests/chat_models/test_litellm_standard.py
+++ b/libs/community/tests/integration_tests/chat_models/test_litellm_standard.py
@@ -2,7 +2,6 @@
 
 from typing import Type
 
-import pytest
 from langchain_core.language_models import BaseChatModel
 from langchain_tests.integration_tests import ChatModelIntegrationTests
 
@@ -16,8 +15,8 @@ class TestLiteLLMStandard(ChatModelIntegrationTests):
 
     @property
     def chat_model_params(self) -> dict:
-        return {"model": "ollama/mistral"}
-
-    @pytest.mark.xfail(reason="Not yet implemented.")
-    def test_usage_metadata_streaming(self, model: BaseChatModel) -> None:
-        super().test_usage_metadata_streaming(model)
+        return {
+            "model": "ollama/mistral",
+            # Needed to get the usage object when streaming. See https://docs.litellm.ai/docs/completion/usage#streaming-usage
+            "model_kwargs": {"stream_options": {"include_usage": True}},
+        }