diff --git a/src/diffusers/models/resnet.py b/src/diffusers/models/resnet.py
index c0b4ad40055a..a98cb491146b 100644
--- a/src/diffusers/models/resnet.py
+++ b/src/diffusers/models/resnet.py
@@ -366,7 +366,12 @@ def forward(self, input_tensor: torch.Tensor, temb: torch.Tensor, *args, **kwarg
         hidden_states = self.conv2(hidden_states)
 
         if self.conv_shortcut is not None:
-            input_tensor = self.conv_shortcut(input_tensor.contiguous())
+            # Only use contiguous() during training to avoid DDP gradient stride mismatch warning.
+            # In inference mode (eval or no_grad), skip contiguous() for better performance, especially on CPU.
+            # Issue: https://github.com/huggingface/diffusers/issues/12975
+            if self.training:
+                input_tensor = input_tensor.contiguous()
+            input_tensor = self.conv_shortcut(input_tensor)
 
         output_tensor = (input_tensor + hidden_states) / self.output_scale_factor
 
diff --git a/tests/pipelines/kandinsky2_2/test_kandinsky_inpaint.py b/tests/pipelines/kandinsky2_2/test_kandinsky_inpaint.py
index 8a693e9c2dd0..df1dd2d9872c 100644
--- a/tests/pipelines/kandinsky2_2/test_kandinsky_inpaint.py
+++ b/tests/pipelines/kandinsky2_2/test_kandinsky_inpaint.py
@@ -248,6 +248,9 @@ def test_inference_batch_single_identical(self):
     def test_float16_inference(self):
         super().test_float16_inference(expected_max_diff=5e-1)
 
+    def test_save_load_dduf(self):
+        super().test_save_load_dduf(atol=1e-3, rtol=1e-3)
+
     @is_flaky()
     def test_model_cpu_offload_forward_pass(self):
         super().test_inference_batch_single_identical(expected_max_diff=8e-4)
diff --git a/tests/pipelines/kandinsky3/test_kandinsky3_img2img.py b/tests/pipelines/kandinsky3/test_kandinsky3_img2img.py
index 503fdb242dff..d3bfa4b3082c 100644
--- a/tests/pipelines/kandinsky3/test_kandinsky3_img2img.py
+++ b/tests/pipelines/kandinsky3/test_kandinsky3_img2img.py
@@ -191,6 +191,9 @@ def test_float16_inference(self):
     def test_inference_batch_single_identical(self):
         super().test_inference_batch_single_identical(expected_max_diff=1e-2)
 
+    def test_save_load_dduf(self):
+        super().test_save_load_dduf(atol=1e-3, rtol=1e-3)
+
 
 @slow
 @require_torch_accelerator