diff --git a/libs/langchain_v1/langchain/agents/factory.py b/libs/langchain_v1/langchain/agents/factory.py
index be891cfafd4..679f207a0d0 100644
--- a/libs/langchain_v1/langchain/agents/factory.py
+++ b/libs/langchain_v1/langchain/agents/factory.py
@@ -3,6 +3,7 @@
 from __future__ import annotations
 
 import functools
+import importlib
 import itertools
 import re
 from dataclasses import dataclass, field, fields
@@ -572,6 +573,26 @@ def _supports_provider_strategy(
     )
 
 
+def _is_openai_compatible_model(model: BaseChatModel) -> bool:
+    """Check if a model inherits from `BaseChatOpenAI`.
+
+    Used to redundantly set `strict=True` on tools when `response_format` is
+    provided, as older versions of `langchain-openai` do not auto-set it.
+    Covers `ChatOpenAI`, `ChatDeepSeek`, `ChatXAI`, etc.
+
+    Args:
+        model: The chat model to check.
+
+    Returns:
+        `True` if the model inherits from `BaseChatOpenAI`, `False` otherwise.
+    """
+    try:
+        base_chat_openai = importlib.import_module("langchain_openai.chat_models.base")
+    except ImportError:
+        return False
+    return isinstance(model, base_chat_openai.BaseChatOpenAI)
+
+
 def _handle_structured_output_error(
     exception: Exception,
     response_format: ResponseFormat[Any],
@@ -1334,11 +1355,16 @@ def create_agent(
         # Bind model based on effective response format
         if isinstance(effective_response_format, ProviderStrategy):
             # (Backward compatibility) Use OpenAI format structured output
+            # Redundantly set strict=True on tools for OpenAI-compatible models, as older
+            # versions of langchain-openai do not auto-set it in bind_tools.
             kwargs = effective_response_format.to_model_kwargs()
+            bind_kwargs: dict[str, Any] = {**kwargs, **request.model_settings}
+            if _is_openai_compatible_model(request.model) and not getattr(
+                request.model, "use_responses_api", False
+            ):
+                bind_kwargs["strict"] = True
             return (
-                request.model.bind_tools(
-                    final_tools, strict=True, **kwargs, **request.model_settings
-                ),
+                request.model.bind_tools(final_tools, **bind_kwargs),
                 effective_response_format,
             )
 
diff --git a/libs/langchain_v1/tests/cassettes/test_inference_to_native_output[True].yaml.gz b/libs/langchain_v1/tests/cassettes/test_inference_to_native_output[True].yaml.gz
index f2a20a6afa0..c1e97be9f0b 100644
Binary files a/libs/langchain_v1/tests/cassettes/test_inference_to_native_output[True].yaml.gz and b/libs/langchain_v1/tests/cassettes/test_inference_to_native_output[True].yaml.gz differ
diff --git a/libs/langchain_v1/tests/cassettes/test_strict_mode[True].yaml.gz b/libs/langchain_v1/tests/cassettes/test_strict_mode[True].yaml.gz
index dbe8be819c7..bf7509001ee 100644
Binary files a/libs/langchain_v1/tests/cassettes/test_strict_mode[True].yaml.gz and b/libs/langchain_v1/tests/cassettes/test_strict_mode[True].yaml.gz differ
diff --git a/libs/partners/openai/langchain_openai/chat_models/base.py b/libs/partners/openai/langchain_openai/chat_models/base.py
index af5f49abfd0..ff72f66ed30 100644
--- a/libs/partners/openai/langchain_openai/chat_models/base.py
+++ b/libs/partners/openai/langchain_openai/chat_models/base.py
@@ -2193,6 +2193,12 @@ class BaseChatOpenAI(BaseChatModel):
         """  # noqa: E501
         if parallel_tool_calls is not None:
             kwargs["parallel_tool_calls"] = parallel_tool_calls
+        # When response_format is provided via the Chat Completions API, OpenAI
+        # requires all function tools to be strict. Default strict=True unless
+        # the caller explicitly passed strict=False. The Responses API does not
+        # require this.
+        if response_format and strict is not False and not self.use_responses_api:
+            strict = True
         formatted_tools = [
             convert_to_openai_tool(tool, strict=strict) for tool in tools
         ]
diff --git a/libs/partners/openai/tests/unit_tests/chat_models/test_base.py b/libs/partners/openai/tests/unit_tests/chat_models/test_base.py
index 92af400e982..594346ef46f 100644
--- a/libs/partners/openai/tests/unit_tests/chat_models/test_base.py
+++ b/libs/partners/openai/tests/unit_tests/chat_models/test_base.py
@@ -943,6 +943,37 @@ def test_bind_tools_tool_choice(tool_choice: Any, strict: bool | None) -> None:
     )
 
 
+def test_bind_tools_response_format_defaults_strict() -> None:
+    """Test that strict defaults to True when response_format is provided."""
+    llm = ChatOpenAI(model=OPENAI_TEST_MODEL, temperature=0)
+    bound = llm.bind_tools(
+        tools=[GenerateUsername],
+        response_format=MakeASandwich,
+    )
+    tools = bound.kwargs["tools"]  # type: ignore[attr-defined]
+    assert tools[0]["function"]["strict"] is True
+
+
+def test_bind_tools_response_format_respects_strict_false() -> None:
+    """Test that strict=False is respected even when response_format is provided."""
+    llm = ChatOpenAI(model=OPENAI_TEST_MODEL, temperature=0)
+    bound = llm.bind_tools(
+        tools=[GenerateUsername],
+        response_format=MakeASandwich,
+        strict=False,
+    )
+    tools = bound.kwargs["tools"]  # type: ignore[attr-defined]
+    assert tools[0]["function"]["strict"] is False
+
+
+def test_bind_tools_no_response_format_keeps_strict_none() -> None:
+    """Test that strict stays None when response_format is not provided."""
+    llm = ChatOpenAI(model=OPENAI_TEST_MODEL, temperature=0)
+    bound = llm.bind_tools(tools=[GenerateUsername])
+    tools = bound.kwargs["tools"]  # type: ignore[attr-defined]
+    assert "strict" not in tools[0]["function"]
+
+
 @pytest.mark.parametrize(
     "schema", [GenerateUsername, GenerateUsername.model_json_schema()]
 )