diff --git a/src/diffusers/pipeline_utils.py b/src/diffusers/pipeline_utils.py
index 17560055..01ba4eef 100644
--- a/src/diffusers/pipeline_utils.py
+++ b/src/diffusers/pipeline_utils.py
@@ -166,6 +166,12 @@ class DiffusionPipeline(ConfigMixin):
         for name in module_names.keys():
             module = getattr(self, name)
             if isinstance(module, torch.nn.Module):
+                if module.dtype == torch.float16 and str(torch_device) in ["cpu", "mps"]:
+                    raise ValueError(
+                        "Pipelines loaded with `torch_dtype=torch.float16` cannot be moved to `cpu` or `mps` "
+                        "due to the lack of support for `float16` operations on those devices in PyTorch. "
+                        "Please remove the `torch_dtype=torch.float16` argument, or use a `cuda` device."
+                    )
                 module.to(torch_device)
         return self
 
diff --git a/tests/test_pipelines.py b/tests/test_pipelines.py
index e6cc37ad..69301e97 100644
--- a/tests/test_pipelines.py
+++ b/tests/test_pipelines.py
@@ -188,6 +188,17 @@ class PipelineFastTests(unittest.TestCase):
 
         return extract
 
+    def test_pipeline_fp16_cpu_error(self):
+        model = self.dummy_uncond_unet
+        scheduler = DDPMScheduler(num_train_timesteps=10)
+        pipe = DDIMPipeline(model.half(), scheduler)
+
+        if str(torch_device) in ["cpu", "mps"]:
+            self.assertRaises(ValueError, pipe.to, torch_device)
+        else:
+            # moving the pipeline to GPU should work
+            pipe.to(torch_device)
+
     def test_ddim(self):
         unet = self.dummy_uncond_unet
         scheduler = DDIMScheduler()