diff --git a/comfy_extras/nodes_post_processing.py b/comfy_extras/nodes_post_processing.py
index 90090b104..10fbd77a6 100644
--- a/comfy_extras/nodes_post_processing.py
+++ b/comfy_extras/nodes_post_processing.py
@@ -290,13 +290,6 @@ class Rotate:
             "bilinear": Image.Resampling.BILINEAR,
             "bicubic": Image.Resampling.BICUBIC,
         }
-
-        tensor_image = image[0]
-        img = (tensor_image * 255).to(torch.uint8).numpy()
-        pil_image = Image.fromarray(img, mode='RGB')
-        
-        expand = True if expand == "enabled" else False
-        fill_color = fill_color or "#000000"
         
         def parse_palette(color_str):
             if re.match(r'^#[a-fA-F0-9]{6}$', color_str) or color_str.lower() in ImageColor.colormap:
@@ -308,16 +301,24 @@ class Rotate:
             else:
                 raise ValueError(f"Invalid color format: {color_str}")
 
+        expand = True if expand == "enabled" else False
+        fill_color = fill_color or "#000000"
         center = (width / 2, height / 2) if center_of_image == "enabled" else (center_x, center_y)
         translate = (translate_x, translate_y)
 
         color = fill_color.replace(" ", "")
         color = parse_palette(color)
-        rotated_image = pil_image.rotate(angle=angle, resample=resamplers[resample], expand=expand, center=center, translate=translate, fillcolor=color)
-        result_width, result_height = rotated_image.size
+        
+        result_width, result_height = Image.new("RGB", (width, height)).rotate(angle=angle, expand=expand, center=center, translate=translate).size
         result = torch.zeros(batch_size, result_height, result_width, 3)
-        rotated_array = torch.tensor(np.array(rotated_image.convert("RGB"))).float() / 255
-        result[0] = rotated_array
+        
+        for b in range(batch_size):
+            tensor_image = image[b]
+            img = (tensor_image * 255).to(torch.uint8).numpy()
+            pil_image = Image.fromarray(img, mode='RGB')
+            rotated_image = pil_image.rotate(angle=angle, resample=resamplers[resample], expand=expand, center=center, translate=translate, fillcolor=color)
+            rotated_array = torch.tensor(np.array(rotated_image.convert("RGB"))).float() / 255
+            result[b] = rotated_array
 
         return (result,)