diff --git a/comfy/model_base.py b/comfy/model_base.py
index 9d73fa460..2a4303620 100644
--- a/comfy/model_base.py
+++ b/comfy/model_base.py
@@ -1001,7 +1001,6 @@ class WAN21(BaseModel):
         device = kwargs["device"]
 
         if image is None:
-            image = torch.zeros_like(noise)
             shape_image = list(noise.shape)
             shape_image[1] = extra_channels
             image = torch.zeros(shape_image, dtype=noise.dtype, layout=noise.layout, device=noise.device)
@@ -1014,6 +1013,9 @@ class WAN21(BaseModel):
         if not self.image_to_video or extra_channels == image.shape[1]:
             return image
 
+        if image.shape[1] > (extra_channels - 4):
+            image = image[:, :(extra_channels - 4)]
+
         mask = kwargs.get("concat_mask", kwargs.get("denoise_mask", None))
         if mask is None:
             mask = torch.zeros_like(noise)[:, :4]
diff --git a/comfy_extras/nodes_lt.py b/comfy_extras/nodes_lt.py
index fdc6c7c13..525889200 100644
--- a/comfy_extras/nodes_lt.py
+++ b/comfy_extras/nodes_lt.py
@@ -446,10 +446,9 @@ class LTXVPreprocess:
     CATEGORY = "image"
 
     def preprocess(self, image, img_compression):
-        if img_compression > 0:
-            output_images = []
-            for i in range(image.shape[0]):
-                output_images.append(preprocess(image[i], img_compression))
+        output_images = []
+        for i in range(image.shape[0]):
+            output_images.append(preprocess(image[i], img_compression))
         return (torch.stack(output_images),)
 
 
diff --git a/comfy_extras/nodes_mask.py b/comfy_extras/nodes_mask.py
index 63fd13b9a..e1f0c8225 100644
--- a/comfy_extras/nodes_mask.py
+++ b/comfy_extras/nodes_mask.py
@@ -87,6 +87,11 @@ class ImageCompositeMasked:
     CATEGORY = "image"
 
     def composite(self, destination, source, x, y, resize_source, mask = None):
+        if destination.shape[-1] < source.shape[-1]:
+            source = source[...,:destination.shape[-1]]
+        elif destination.shape[-1] > source.shape[-1]:
+            destination = torch.nn.functional.pad(destination, (0, 1))
+            destination[..., -1] = source[..., -1]
         destination = destination.clone().movedim(-1, 1)
         output = composite(destination, source.movedim(-1, 1), x, y, mask, 1, resize_source).movedim(1, -1)
         return (output,)
diff --git a/requirements.txt b/requirements.txt
index c78d3c228..806fbc751 100644
--- a/requirements.txt
+++ b/requirements.txt
@@ -1,4 +1,4 @@
-comfyui-frontend-package==1.14.5
+comfyui-frontend-package==1.14.6
 torch
 torchsde
 torchvision