diff --git a/src/diffusers/models/autoencoders/autoencoder_kl_wan.py b/src/diffusers/models/autoencoders/autoencoder_kl_wan.py
index d84a0861e984..c450eaf8a79f 100644
--- a/src/diffusers/models/autoencoders/autoencoder_kl_wan.py
+++ b/src/diffusers/models/autoencoders/autoencoder_kl_wan.py
@@ -1289,6 +1289,10 @@ def tiled_encode(self, x: torch.Tensor) -> AutoencoderKLOutput:
         blend_height = tile_latent_min_height - tile_latent_stride_height
         blend_width = tile_latent_min_width - tile_latent_stride_width
 
+        # Apply patchify if patch_size is specified
+        if self.config.patch_size is not None:
+            x = patchify(x, patch_size=self.config.patch_size)
+
         # Split x into overlapping tiles and encode them separately.
         # The tiles have an overlap to avoid seams between tiles.
         rows = []
@@ -1392,6 +1396,10 @@ def tiled_decode(self, z: torch.Tensor, return_dict: bool = True) -> Union[Decod
 
         dec = torch.cat(result_rows, dim=3)[:, :, :, :sample_height, :sample_width]
 
+        # Apply unpatchify if patch_size is specified
+        if self.config.patch_size is not None:
+            dec = unpatchify(dec, patch_size=self.config.patch_size)
+
         if not return_dict:
             return (dec,)
         return DecoderOutput(sample=dec)