diff --git a/libs/partners/ollama/langchain_ollama/v1/chat_models/base.py b/libs/partners/ollama/langchain_ollama/v1/chat_models/base.py
index e21bb38dad5..a68e46e40c6 100644
--- a/libs/partners/ollama/langchain_ollama/v1/chat_models/base.py
+++ b/libs/partners/ollama/langchain_ollama/v1/chat_models/base.py
@@ -275,6 +275,13 @@ class ChatOllama(BaseChatModel):
     model: str
     """Model name to use."""
 
+    streaming: bool = False
+    """Whether to use streaming for invocation.
+
+    If True, invoke will use streaming internally.
+
+    """
+
     reasoning: Optional[bool] = None
     """Controls the reasoning/thinking mode for supported models.
 
@@ -525,6 +532,8 @@ class ChatOllama(BaseChatModel):
         self,
         messages: list[MessageV1],
         stop: Optional[list[str]] = None,
+        *,
+        stream: bool = True,
         **kwargs: Any,
     ) -> dict[str, Any]:
         """Build parameters for Ollama chat API."""
@@ -560,7 +569,7 @@ class ChatOllama(BaseChatModel):
 
         params = {
             "messages": ollama_messages,
-            "stream": kwargs.pop("stream", True),
+            "stream": kwargs.pop("stream", stream),
             "model": kwargs.pop("model", self.model),
             "think": kwargs.pop("reasoning", self.reasoning),
             "format": kwargs.pop("format", self.format),
@@ -691,10 +700,15 @@ class ChatOllama(BaseChatModel):
             Complete AI message response.
 
         """
-        stream_iter = self._generate_stream(
-            messages, stop=stop, run_manager=run_manager, **kwargs
-        )
-        return generate_from_stream(stream_iter)
+        if self.streaming:
+            stream_iter = self._stream(
+                messages, stop=stop, run_manager=run_manager, **kwargs
+            )
+            return generate_from_stream(stream_iter)
+
+        chat_params = self._chat_params(messages, stop, stream=False, **kwargs)
+        response = self._client.chat(**chat_params)
+        return _convert_to_v1_from_ollama_format(response)
 
     async def _ainvoke(
         self,
@@ -715,10 +729,16 @@ class ChatOllama(BaseChatModel):
             Complete AI message response.
 
         """
-        stream_iter = self._agenerate_stream(
-            messages, stop=stop, run_manager=run_manager, **kwargs
-        )
-        return await agenerate_from_stream(stream_iter)
+        if self.streaming:
+            stream_iter = self._astream(
+                messages, stop=stop, run_manager=run_manager, **kwargs
+            )
+            return await agenerate_from_stream(stream_iter)
+
+        # Non-streaming case: direct API call
+        chat_params = self._chat_params(messages, stop, stream=False, **kwargs)
+        response = await self._async_client.chat(**chat_params)
+        return _convert_to_v1_from_ollama_format(response)
 
     def _stream(
         self,
diff --git a/libs/partners/ollama/tests/unit_tests/v1/test_chat_models.py b/libs/partners/ollama/tests/unit_tests/v1/test_chat_models.py
index 14f05d74272..e6b82b391c5 100644
--- a/libs/partners/ollama/tests/unit_tests/v1/test_chat_models.py
+++ b/libs/partners/ollama/tests/unit_tests/v1/test_chat_models.py
@@ -508,7 +508,7 @@ def test_load_response_with_empty_content_is_skipped(
         mock_client_class.return_value = mock_client
         mock_client.chat.return_value = iter(load_only_response)
 
-        llm = ChatOllama(model="test-model")
+        llm = ChatOllama(model="test-model", streaming=True)
 
         with (
             caplog.at_level(logging.WARNING),
@@ -539,7 +539,7 @@ def test_load_response_with_whitespace_content_is_skipped(
         mock_client_class.return_value = mock_client
         mock_client.chat.return_value = iter(load_whitespace_response)
 
-        llm = ChatOllama(model="test-model")
+        llm = ChatOllama(model="test-model", streaming=True)
 
         with (
             caplog.at_level(logging.WARNING),
@@ -579,7 +579,7 @@ def test_load_followed_by_content_response(
         mock_client_class.return_value = mock_client
         mock_client.chat.return_value = iter(load_then_content_response)
 
-        llm = ChatOllama(model="test-model")
+        llm = ChatOllama(model="test-model", streaming=True)
 
         with caplog.at_level(logging.WARNING):
             result = llm.invoke([HumanMessage("Hello")])
@@ -610,7 +610,7 @@ def test_load_response_with_actual_content_is_not_skipped(
         mock_client_class.return_value = mock_client
         mock_client.chat.return_value = iter(load_with_content_response)
 
-        llm = ChatOllama(model="test-model")
+        llm = ChatOllama(model="test-model", streaming=True)
 
         with caplog.at_level(logging.WARNING):
             result = llm.invoke([HumanMessage("Hello")])