diff --git a/control/control.py b/control/control.py
index 18fff63..c851fd2 100644
--- a/control/control.py
+++ b/control/control.py
@@ -204,10 +204,11 @@ class ControlNetAdvanced(ControlNet):
             if self.cond_hint is not None:
                 del self.cond_hint
             self.cond_hint = None
-            self.cond_hint = comfy.utils.common_upscale(self.cond_hint_original, x_noisy.shape[3] * 8, x_noisy.shape[2] * 8, 'nearest-exact', "center").to(self.control_model.dtype).to(self.device)
-            # if self.cond_hint length matches real latent count, need to subdivide it
-            if self.cond_hint.size(0) == self.full_latent_length:
-                self.cond_hint = self.cond_hint[self.sub_idxs]
+            # if self.cond_hint_original length matches real latent count, need to subdivide it
+            if self.cond_hint_original.size(0) == self.full_latent_length:
+                self.cond_hint = comfy.utils.common_upscale(self.cond_hint_original[self.sub_idxs], x_noisy.shape[3] * 8, x_noisy.shape[2] * 8, 'nearest-exact', "center").to(self.control_model.dtype).to(self.device)
+            else:
+                self.cond_hint = comfy.utils.common_upscale(self.cond_hint_original, x_noisy.shape[3] * 8, x_noisy.shape[2] * 8, 'nearest-exact', "center").to(self.control_model.dtype).to(self.device)
         if x_noisy.shape[0] != self.cond_hint.shape[0]:
             self.cond_hint = broadcast_image_to(self.cond_hint, x_noisy.shape[0], batched_number)
 
@@ -217,6 +218,7 @@ class ControlNetAdvanced(ControlNet):
                 if self.mask_cond_hint is not None:
                     del self.mask_cond_hint
                 self.mask_cond_hint = None
+                # TODO: perform upscale on only the sub_idxs masks at a time instead of all to conserve RAM
                 # resize mask and match batch count
                 self.mask_cond_hint = prepare_mask_batch(self.mask_cond_hint_original, x_noisy.shape, multiplier=8)
                 actual_latent_length = x_noisy.shape[0] // batched_number