diff --git a/src/openai/_models.py b/src/openai/_models.py
index ed4c1f82d6..61cdcaf802 100644
--- a/src/openai/_models.py
+++ b/src/openai/_models.py
@@ -657,7 +657,8 @@ def construct_type(*, value: object, type_: object, metadata: Optional[List[Any]
         if not is_mapping(value):
             return value
 
-        _, items_type = get_args(type_)  # Dict[_, items_type]
+        _type_args = get_args(type_)
+        items_type = _type_args[1] if len(_type_args) >= 2 else Any  # bare dict has no type args
         return {key: construct_type(value=item, type_=items_type) for key, item in value.items()}
 
     if (
diff --git a/src/openai/_utils/_transform.py b/src/openai/_utils/_transform.py
index 414f38c340..3428ae1bf2 100644
--- a/src/openai/_utils/_transform.py
+++ b/src/openai/_utils/_transform.py
@@ -180,7 +180,8 @@ def _transform_recursive(
         return _transform_typeddict(data, stripped_type)
 
     if origin == dict and is_mapping(data):
-        items_type = get_args(stripped_type)[1]
+        _type_args = get_args(stripped_type)
+        items_type = _type_args[1] if len(_type_args) >= 2 else Any  # bare dict has no type args
         return {key: _transform_recursive(value, annotation=items_type) for key, value in data.items()}
 
     if (
@@ -346,7 +347,8 @@ async def _async_transform_recursive(
         return await _async_transform_typeddict(data, stripped_type)
 
     if origin == dict and is_mapping(data):
-        items_type = get_args(stripped_type)[1]
+        _type_args = get_args(stripped_type)
+        items_type = _type_args[1] if len(_type_args) >= 2 else Any  # bare dict has no type args
         return {key: _transform_recursive(value, annotation=items_type) for key, value in data.items()}
 
     if (
diff --git a/tests/test_models.py b/tests/test_models.py
index cc204bac1d..abe56d5258 100644
--- a/tests/test_models.py
+++ b/tests/test_models.py
@@ -1015,3 +1015,10 @@ class Model(BaseModel):
     # falls back to list of chars rather than calling str(["h", "e", "l", "l", "o"])
     assert m.data["items"] == ["h", "e", "l", "l", "o"]
     assert m.model_dump()["data"]["items"] == ["h", "e", "l", "l", "o"]
+
+
+def test_construct_type_bare_dict() -> None:
+    # Regression: bare `dict` annotation (no type args) crashed with ValueError
+    # because get_args(dict) returns () and the old code did `_, v = get_args(dict)`.
+    result = construct_type(value={"key": "value"}, type_=dict)
+    assert result == {"key": "value"}
diff --git a/tests/test_transform.py b/tests/test_transform.py
index 5af84df7fd..5f7f064790 100644
--- a/tests/test_transform.py
+++ b/tests/test_transform.py
@@ -458,3 +458,16 @@ async def test_strips_notgiven(use_async: bool) -> None:
 async def test_strips_omit(use_async: bool) -> None:
     assert await transform({"foo_bar": "bar"}, Foo1, use_async) == {"fooBar": "bar"}
     assert await transform({"foo_bar": omit}, Foo1, use_async) == {}
+
+
+class BareDict(TypedDict, total=False):
+    metadata: dict  # bare dict, no type parameters
+
+
+@parametrize
+@pytest.mark.asyncio
+async def test_bare_dict_annotation(use_async: bool) -> None:
+    # Regression: bare `dict` TypedDict field crashed with IndexError because
+    # get_args(dict) returns () and the old code did get_args(dict)[1].
+    result = await transform({"metadata": {"key": "value"}}, BareDict, use_async)
+    assert result == {"metadata": {"key": "value"}}