diff --git a/hyvideo/diffusion/pipelines/pipeline_hunyuan_video.py b/hyvideo/diffusion/pipelines/pipeline_hunyuan_video.py
index 02810dd..1ddf949 100644
--- a/hyvideo/diffusion/pipelines/pipeline_hunyuan_video.py
+++ b/hyvideo/diffusion/pipelines/pipeline_hunyuan_video.py
@@ -792,7 +792,7 @@ class HunyuanVideoPipeline(DiffusionPipeline):
                     if callback is not None:
                         callback(
                             i, 
-                            (latent_model_input - noise_pred).detach()[0].permute(1,0,2,3),
+                            (latent_model_input - noise_pred * t / 1000).detach()[0].permute(1,0,2,3),
                             None, 
                             num_inference_steps
                         )
diff --git a/nodes_rf_inversion.py b/nodes_rf_inversion.py
index ab99ef4..8dec9b4 100644
--- a/nodes_rf_inversion.py
+++ b/nodes_rf_inversion.py
@@ -252,7 +252,7 @@ class HyVideoInverseSampler:
                 
                 progress_bar.update()
                 if callback is not None:
-                    callback(idx, (latent_model_input - noise_pred).detach()[0].permute(1,0,2,3), None, steps)
+                    callback(idx, (latent_model_input - noise_pred * t / 1000).detach()[0].permute(1,0,2,3), None, steps)
                 else:
                     comfy_pbar.update(1)
                   
@@ -458,7 +458,7 @@ class HyVideoReSampler:
 
                     progress_bar.update()
                     if callback is not None:
-                        callback(idx, (latent_model_input - noise_pred).detach()[0].permute(1,0,2,3), None, steps)
+                        callback(idx, (latent_model_input - noise_pred * t / 1000).detach()[0].permute(1,0,2,3), None, steps)
                     else:
                         comfy_pbar.update(1)
 
@@ -695,7 +695,7 @@ class HyVideoPromptMixSampler:
 
                     progress_bar.update()
                     if callback is not None:
-                        callback(idx, (latent_model_input - noise_pred).detach()[0].permute(1,0,2,3), None, steps)
+                        callback(idx, (latent_model_input - noise_pred * t / 1000).detach()[0].permute(1,0,2,3), None, steps)
                     else:
                         comfy_pbar.update(1)