diff --git a/src/diffusers/models/modeling_utils.py b/src/diffusers/models/modeling_utils.py
index 814547d82be4..19ac868cdae0 100644
--- a/src/diffusers/models/modeling_utils.py
+++ b/src/diffusers/models/modeling_utils.py
@@ -714,10 +714,7 @@ def save_pretrained(
             if safe_serialization:
                 # At some point we will need to deal better with save_function (used for TPU and other distributed
                 # joyfulness), but for now this enough.
-                try:
-                    safetensors.torch.save_file(shard, filepath, metadata={"format": "pt"})
-                except RuntimeError:
-                    safetensors.torch.save_model(model_to_save, filepath, metadata={"format": "pt"})
+                safetensors.torch.save_file(shard, filepath, metadata={"format": "pt"})
             else:
                 torch.save(shard, filepath)
 
diff --git a/tests/pipelines/test_pipelines_common.py b/tests/pipelines/test_pipelines_common.py
index cc5008e37292..d3e39e363f91 100644
--- a/tests/pipelines/test_pipelines_common.py
+++ b/tests/pipelines/test_pipelines_common.py
@@ -2293,7 +2293,7 @@ def test_torch_dtype_dict(self):
         specified_key = next(iter(components.keys()))
 
         with tempfile.TemporaryDirectory(ignore_cleanup_errors=True) as tmpdirname:
-            pipe.save_pretrained(tmpdirname)
+            pipe.save_pretrained(tmpdirname, safe_serialization=False)
             torch_dtype_dict = {specified_key: torch.bfloat16, "default": torch.float16}
             loaded_pipe = self.pipeline_class.from_pretrained(tmpdirname, torch_dtype=torch_dtype_dict)