diff --git a/libs/partners/openai/tests/integration_tests/chat_models/test_base.py b/libs/partners/openai/tests/integration_tests/chat_models/test_base.py
index 02475b5a8be40..26a8bb787a207 100644
--- a/libs/partners/openai/tests/integration_tests/chat_models/test_base.py
+++ b/libs/partners/openai/tests/integration_tests/chat_models/test_base.py
@@ -9,7 +9,6 @@
 from typing import Any, Literal, cast
 
 import httpx
-import openai
 import pytest
 from langchain_core.callbacks import CallbackManager
 from langchain_core.messages import (
@@ -23,11 +22,7 @@
     ToolMessage,
 )
 from langchain_core.outputs import ChatGeneration, ChatResult, LLMResult
-from langchain_tests.integration_tests.chat_models import (
-    _validate_tool_call_message,
-    magic_function,
-)
-from pydantic import BaseModel, Field, field_validator
+from pydantic import BaseModel, field_validator
 from typing_extensions import TypedDict
 
 from langchain_openai import ChatOpenAI
@@ -772,49 +767,6 @@ def test_image_token_counting_png() -> None:
     assert expected == actual
 
 
-@pytest.mark.parametrize("use_responses_api", [False, True])
-def test_tool_calling_strict(use_responses_api: bool) -> None:
-    """Test tool calling with strict=True.
-
-    Responses API appears to have fewer constraints on schema when strict=True.
-    """
-
-    class magic_function_notrequired_arg(BaseModel):  # noqa: N801
-        """Applies a magic function to an input."""
-
-        input: int | None = Field(default=None)
-
-    model = ChatOpenAI(
-        model="gpt-5-nano", temperature=0, use_responses_api=use_responses_api
-    )
-    # N.B. magic_function adds metadata to schema (min/max for number fields)
-    model_with_tools = model.bind_tools([magic_function], strict=True)
-    # Having a not-required argument in the schema remains invalid.
-    model_with_invalid_tool_schema = model.bind_tools(
-        [magic_function_notrequired_arg], strict=True
-    )
-
-    # Test invoke
-    query = "What is the value of magic_function(3)? Use the tool."
-    response = model_with_tools.invoke(query)
-    _validate_tool_call_message(response)
-
-    # Test invalid tool schema
-    with pytest.raises(openai.BadRequestError):
-        model_with_invalid_tool_schema.invoke(query)
-
-    # Test stream
-    full: BaseMessageChunk | None = None
-    for chunk in model_with_tools.stream(query):
-        full = chunk if full is None else full + chunk  # type: ignore
-    assert isinstance(full, AIMessage)
-    _validate_tool_call_message(full)
-
-    # Test invalid tool schema
-    with pytest.raises(openai.BadRequestError):
-        next(model_with_invalid_tool_schema.stream(query))
-
-
 @pytest.mark.parametrize("use_responses_api", [False, True])
 @pytest.mark.parametrize(
     ("model", "method"),