diff --git a/src/diffusers/schedulers/scheduling_lms_discrete.py b/src/diffusers/schedulers/scheduling_lms_discrete.py
index 8b371703ec84..6157f4b4dc65 100644
--- a/src/diffusers/schedulers/scheduling_lms_discrete.py
+++ b/src/diffusers/schedulers/scheduling_lms_discrete.py
@@ -252,9 +252,13 @@ def add_noise(
     ) -> torch.FloatTensor:
         # Make sure sigmas and timesteps have the same device and dtype as original_samples
         self.sigmas = self.sigmas.to(device=original_samples.device, dtype=original_samples.dtype)
-        dtype = torch.float32 if original_samples.device.type == "mps" else timesteps.dtype
-        self.timesteps = self.timesteps.to(original_samples.device, dtype=dtype)
-        timesteps = timesteps.to(original_samples.device)
+        if original_samples.device.type == "mps" and torch.is_floating_point(timesteps):
+            # mps does not support float64
+            self.timesteps = self.timesteps.to(original_samples.device, dtype=torch.float32)
+            timesteps = timesteps.to(original_samples.device, dtype=torch.float32)
+        else:
+            self.timesteps = self.timesteps.to(original_samples.device)
+            timesteps = timesteps.to(original_samples.device)
 
         schedule_timesteps = self.timesteps
 
diff --git a/tests/test_scheduler.py b/tests/test_scheduler.py
index 6f86ffc85e05..194fb66f663f 100755
--- a/tests/test_scheduler.py
+++ b/tests/test_scheduler.py
@@ -266,13 +266,14 @@ def test_add_noise_device(self):
                 continue
             scheduler_config = self.get_scheduler_config()
             scheduler = scheduler_class(**scheduler_config)
+            scheduler.set_timesteps(100)
 
             sample = self.dummy_sample.to(torch_device)
             scaled_sample = scheduler.scale_model_input(sample, 0.0)
             self.assertEqual(sample.shape, scaled_sample.shape)
 
             noise = torch.randn_like(scaled_sample).to(torch_device)
-            t = torch.tensor([10]).to(torch_device)
+            t = scheduler.timesteps[5][None]
             noised = scheduler.add_noise(scaled_sample, noise, t)
             self.assertEqual(noised.shape, scaled_sample.shape)