diff --git a/comfy/sample.py b/comfy/sample.py
index 2be0cae5f..617816882 100644
--- a/comfy/sample.py
+++ b/comfy/sample.py
@@ -37,6 +37,11 @@ def prepare_noise(latent_image, seed, noise_inds=None):
 
     return noises
 
+def prepare_empty_noise(latent_image):
+    if latent_image.is_nested:
+        return comfy.nested_tensor.NestedTensor([torch.zeros_like(t, device="cpu") for t in latent_image.unbind()])
+    return torch.zeros_like(latent_image, device="cpu")
+
 def fix_empty_latent_channels(model, latent_image, downscale_ratio_spacial=None, downscale_ratio_temporal=None):
     if latent_image.is_nested:
         return latent_image
diff --git a/comfy_extras/nodes_custom_sampler.py b/comfy_extras/nodes_custom_sampler.py
index d5aa730d2..c73a8f6dc 100644
--- a/comfy_extras/nodes_custom_sampler.py
+++ b/comfy_extras/nodes_custom_sampler.py
@@ -718,15 +718,7 @@ class Noise_EmptyNoise:
         self.seed = 0
 
     def generate_noise(self, input_latent):
-        latent_image = input_latent["samples"]
-        if latent_image.is_nested:
-            tensors = latent_image.unbind()
-            zeros = []
-            for t in tensors:
-                zeros.append(torch.zeros(t.shape, dtype=t.dtype, layout=t.layout, device="cpu"))
-            return comfy.nested_tensor.NestedTensor(zeros)
-        else:
-            return torch.zeros(latent_image.shape, dtype=latent_image.dtype, layout=latent_image.layout, device="cpu")
+        return comfy.sample.prepare_empty_noise(input_latent["samples"])
 
 
 class Noise_RandomNoise:
diff --git a/nodes.py b/nodes.py
index a7f91720f..ec298e1de 100644
--- a/nodes.py
+++ b/nodes.py
@@ -1570,7 +1570,7 @@ def common_ksampler(model, seed, steps, cfg, sampler_name, scheduler, positive,
     latent_image = comfy.sample.fix_empty_latent_channels(model, latent_image, latent.get("downscale_ratio_spacial", None), latent.get("downscale_ratio_temporal", None))
 
     if disable_noise:
-        noise = torch.zeros(latent_image.size(), dtype=latent_image.dtype, layout=latent_image.layout, device="cpu")
+        noise = comfy.sample.prepare_empty_noise(latent_image)
     else:
         batch_inds = latent["batch_index"] if "batch_index" in latent else None
         noise = comfy.sample.prepare_noise(latent_image, seed, batch_inds)