diff --git a/comfy/ldm/supir/supir_patch.py b/comfy/ldm/supir/supir_patch.py
index d1f17d982..b67ab4cd8 100644
--- a/comfy/ldm/supir/supir_patch.py
+++ b/comfy/ldm/supir/supir_patch.py
@@ -27,10 +27,10 @@ class SUPIRPatch:
         if self.cached_features is not None:
             return
         x = kwargs["x"]
-        batch_size = x.shape[0]
+        b = x.shape[0]
         hint = self.hint_latent.to(device=x.device, dtype=x.dtype)
-        if hint.shape[0] < batch_size:
-            hint = hint.repeat(batch_size // hint.shape[0], 1, 1, 1)[:batch_size]
+        if hint.shape[0] != b:
+            hint = hint.expand(b, -1, -1, -1) if hint.shape[0] == 1 else hint.repeat((b + hint.shape[0] - 1) // hint.shape[0], 1, 1, 1)[:b]
         self.cached_features = self.model_patch.model.control_model(
             hint, kwargs["timesteps"], x,
             kwargs["context"], kwargs["y"]
diff --git a/comfy_extras/nodes_model_patch.py b/comfy_extras/nodes_model_patch.py
index 6d77a0788..748559a6b 100644
--- a/comfy_extras/nodes_model_patch.py
+++ b/comfy_extras/nodes_model_patch.py
@@ -271,10 +271,12 @@ class ModelPatchLoader:
                     operations=comfy.ops.manual_cast)
         elif 'model.control_model.input_hint_block.0.weight' in sd or 'control_model.input_hint_block.0.weight' in sd:
             prefix_replace = {}
-            has_full_prefix = 'model.control_model.input_hint_block.0.weight' in sd
-            if has_full_prefix:
+            if 'model.control_model.input_hint_block.0.weight' in sd:
                 prefix_replace["model.control_model."] = "control_model."
                 prefix_replace["model.diffusion_model.project_modules."] = "project_modules."
+            else:
+                prefix_replace["control_model."] = "control_model."
+                prefix_replace["project_modules."] = "project_modules."
 
             # Extract denoise_encoder weights before filter_keys discards them
             de_prefix = "first_stage_model.denoise_encoder."
@@ -618,13 +620,15 @@ class SUPIRApply(io.ComfyNode):
         if not denoise_sd:
             return vae.encode(image)
 
-        # Patch VAE encoder with denoise_encoder weights, encode, then unpatch
+        # Clone VAE patcher, apply denoise_encoder weights to clone, encode
+        orig_patcher = vae.patcher
+        vae.patcher = orig_patcher.clone()
         patches = {f"encoder.{k}": (v,) for k, v in denoise_sd.items()}
         vae.patcher.add_patches(patches, strength_patch=1.0, strength_model=0.0)
         try:
             return vae.encode(image)
         finally:
-            vae.patcher.unpatch_model()
+            vae.patcher = orig_patcher
 
     @classmethod
     def execute(cls, *, model: io.Model.Type, model_patch: io.ModelPatch.Type, vae: io.Vae.Type, image: io.Image.Type,
@@ -651,8 +655,9 @@ class SUPIRApply(io.ComfyNode):
                     s = sigma.item()
                 if s > restore_cfg_s_tmin:
                     ref = x_center.to(device=denoised.device, dtype=denoised.dtype)
-                    if ref.shape[0] < denoised.shape[0]:
-                        ref = ref.repeat(denoised.shape[0] // ref.shape[0], 1, 1, 1)[:denoised.shape[0]]
+                    b = denoised.shape[0]
+                    if ref.shape[0] != b:
+                        ref = ref.expand(b, -1, -1, -1) if ref.shape[0] == 1 else ref.repeat((b + ref.shape[0] - 1) // ref.shape[0], 1, 1, 1)[:b]
                     sigma_val = sigma.view(-1, 1, 1, 1) if sigma.dim() > 0 else sigma
                     d_center = denoised - ref
                     denoised = denoised - d_center * ((sigma_val / sigma_max) ** restore_cfg)