diff --git a/comfy/model_patcher.py b/comfy/model_patcher.py
index 7540f697b..f69a7596f 100644
--- a/comfy/model_patcher.py
+++ b/comfy/model_patcher.py
@@ -127,11 +127,13 @@ class CallbacksMP:
 
 class WrappersMP:
     OUTER_SAMPLE = "outer_sample"
+    CALC_COND_BATCH = "calc_cond_batch"
 
     @classmethod
     def init_wrappers(cls):
         return {
             cls.OUTER_SAMPLE: [],
+            cls.CALC_COND_BATCH: [],
         }
 
 class WrapperExecutor:
@@ -141,16 +143,16 @@ class WrapperExecutor:
         self.idx = idx
         self.is_last = idx == len(wrappers)
     
-    def __call__(self, guider, *args, **kwargs):
+    def __call__(self, *args, **kwargs):
         new_executor = self._create_next_executor()
-        return new_executor._execute(guider, *args, **kwargs)
+        return new_executor._execute(*args, **kwargs)
     
-    def _execute(self, guider, *args, **kwargs):
+    def _execute(self, *args, **kwargs):
         args = list(args)
         kwargs = dict(kwargs)
         if self.is_last:
             return self.original(*args, **kwargs)
-        return self.wrappers[self.idx](self, guider, *args, **kwargs)
+        return self.wrappers[self.idx](self, *args, **kwargs)
 
     def _create_next_executor(self):
         new_idx = self.idx + 1
@@ -162,6 +164,34 @@ class WrapperExecutor:
     def new_executor(cls, original: Callable, wrappers: List[Callable]):
         return cls(original, wrappers, idx=0)
 
+class WrapperClassExecutor:
+    def __init__(self, original: Callable, wrappers: List[Callable], idx: int):
+        self.original = original
+        self.wrappers = wrappers.copy()
+        self.idx = idx
+        self.is_last = idx == len(wrappers)
+    
+    def __call__(self, class_inst, *args, **kwargs):
+        new_executor = self._create_next_executor()
+        return new_executor._execute(class_inst, *args, **kwargs)
+    
+    def _execute(self, class_inst, *args, **kwargs):
+        args = list(args)
+        kwargs = dict(kwargs)
+        if self.is_last:
+            return self.original(*args, **kwargs)
+        return self.wrappers[self.idx](self, class_inst, *args, **kwargs)
+
+    def _create_next_executor(self):
+        new_idx = self.idx + 1
+        if new_idx > len(self.wrappers):
+            raise Exception(f"Wrapper idx exceeded available wrappers; something went very wrong.")
+        return WrapperClassExecutor(self.original, self.wrappers, new_idx)
+
+    @classmethod
+    def new_executor(cls, original: Callable, wrappers: List[Callable]):
+        return cls(original, wrappers, idx=0)
+
 class AutoPatcherEjector:
     def __init__(self, model: 'ModelPatcher', skip_and_inject_on_exit_only=False):
         self.model = model
diff --git a/comfy/samplers.py b/comfy/samplers.py
index a7b59f433..31ffb8dde 100644
--- a/comfy/samplers.py
+++ b/comfy/samplers.py
@@ -183,6 +183,13 @@ def finalize_default_conds(hooked_to_run: Dict[comfy.hooks.HookGroup,List[Tuple[
             hooked_to_run[hook] += [(p, i)]
 
 def calc_cond_batch(model: 'BaseModel', conds: List[List[Dict]], x_in: torch.Tensor, timestep, model_options):
+    executor = comfy.model_patcher.WrapperExecutor.new_executor(
+        outer_calc_cond_batch,
+        model.current_patcher.get_wrappers(comfy.model_patcher.WrappersMP.CALC_COND_BATCH)
+    )
+    return executor._execute(model, conds, x_in, timestep, model_options)
+
+def outer_calc_cond_batch(model: 'BaseModel', conds: List[List[Dict]], x_in: torch.Tensor, timestep, model_options):
     out_conds = []
     out_counts = []
     # separate conds by matching hooks
@@ -799,9 +806,10 @@ class CFGGuider:
 
         try:
             comfy.sampler_helpers.prepare_model_patcher(self.model_patcher, self.conds)
-            executor = comfy.model_patcher.WrapperExecutor.new_executor(
+            executor = comfy.model_patcher.WrapperClassExecutor.new_executor(
                 self.outer_sample,
-                self.model_patcher.get_wrappers(comfy.model_patcher.WrappersMP.OUTER_SAMPLE))
+                self.model_patcher.get_wrappers(comfy.model_patcher.WrappersMP.OUTER_SAMPLE)
+            )
             output = executor._execute(self, noise, latent_image, sampler, sigmas, denoise_mask, callback, disable_pbar, seed)
         finally:
             self.model_patcher.restore_hook_patches()