diff --git a/comfy/sd.py b/comfy/sd.py
index 58a858aa..cfbf8fa4 100644
--- a/comfy/sd.py
+++ b/comfy/sd.py
@@ -298,6 +298,17 @@ class VAE:
             / 3.0)
         return output
 
+    def decode_tiled_1d(self, samples, tile_x=128, overlap=64):
+        output = torch.empty((samples.shape[0], self.output_channels) + tuple(map(lambda a: a * self.upscale_ratio, samples.shape[2:])), device=self.output_device)
+
+        for j in range(samples.shape[0]):
+            for i in range(0, samples.shape[-1], tile_x - overlap):
+                f = i
+                t = i + tile_x
+                output[j:j+1,:,f * self.upscale_ratio:t * self.upscale_ratio] = self.first_stage_model.decode(samples[j:j+1,:,f:t].to(self.vae_dtype).to(self.device)).float()
+
+        return output
+
     def encode_tiled_(self, pixel_samples, tile_x=512, tile_y=512, overlap = 64):
         steps = pixel_samples.shape[0] * comfy.utils.get_tiled_scale_steps(pixel_samples.shape[3], pixel_samples.shape[2], tile_x, tile_y, overlap)
         steps += pixel_samples.shape[0] * comfy.utils.get_tiled_scale_steps(pixel_samples.shape[3], pixel_samples.shape[2], tile_x // 2, tile_y * 2, overlap)
@@ -325,7 +336,10 @@ class VAE:
                 pixel_samples[x:x+batch_number] = self.process_output(self.first_stage_model.decode(samples).to(self.output_device).float())
         except model_management.OOM_EXCEPTION as e:
             logging.warning("Warning: Ran out of memory when regular VAE decoding, retrying with tiled VAE decoding.")
-            pixel_samples = self.decode_tiled_(samples_in)
+            if len(samples_in.shape) == 3:
+                pixel_samples = self.decode_tiled_1d(samples_in)
+            else:
+                pixel_samples = self.decode_tiled_(samples_in)
 
         pixel_samples = pixel_samples.to(self.output_device).movedim(1,-1)
         return pixel_samples