diff --git a/cfz/cfz_cudnn.toggle.py b/cfz/cfz_cudnn.toggle.py
index 3c99e333c..3886633e5 100644
--- a/cfz/cfz_cudnn.toggle.py
+++ b/cfz/cfz_cudnn.toggle.py
@@ -1,5 +1,13 @@
 import torch
 
+class AnyType(str):
+    """A special class that is always equal in not equal comparisons. Credit to pythongosssss"""
+
+    def __ne__(self, __value: object) -> bool:
+        return False
+
+anyType = AnyType("*")
+
 class CUDNNToggleAutoPassthrough:
     @classmethod
     def INPUT_TYPES(cls):
@@ -10,34 +18,36 @@ class CUDNNToggleAutoPassthrough:
                 "latent": ("LATENT",),
                 "audio": ("AUDIO",),
                 "image": ("IMAGE",),
+                "wan_model": ("WANVIDEOMODEL",),
+                "any_input": (anyType, {}),
             },
             "required": {
                 "enable_cudnn": ("BOOLEAN", {"default": True}),
+                "cudnn_benchmark": ("BOOLEAN", {"default": False}),
             },
         }
 
-    RETURN_TYPES = ("MODEL", "CONDITIONING", "LATENT", "AUDIO", "IMAGE")
-    RETURN_NAMES = ("model", "conditioning", "latent", "audio", "image")
+    RETURN_TYPES = ("MODEL", "CONDITIONING", "LATENT", "AUDIO", "IMAGE", "WANVIDEOMODEL", anyType, "BOOLEAN", "BOOLEAN")
+    RETURN_NAMES = ("model", "conditioning", "latent", "audio", "image", "wan_model", "any_output", "prev_cudnn", "prev_benchmark")
     FUNCTION = "toggle"
     CATEGORY = "utils"
 
-    def toggle(self, enable_cudnn, model=None, conditioning=None, latent=None, audio=None, image=None):
+    def toggle(self, enable_cudnn, cudnn_benchmark, any_input=None, wan_model=None, model=None, conditioning=None, latent=None, audio=None, image=None):
+        prev_cudnn = torch.backends.cudnn.enabled
+        prev_benchmark = torch.backends.cudnn.benchmark
         torch.backends.cudnn.enabled = enable_cudnn
-        torch.backends.cudnn.benchmark = enable_cudnn
-        print(f"[CUDNN_TOGGLE] torch.backends.cudnn.enabled set to {enable_cudnn}")
+        torch.backends.cudnn.benchmark = cudnn_benchmark
+        if enable_cudnn != prev_cudnn:
+            print(f"[CUDNN_TOGGLE] torch.backends.cudnn.enabled set to {enable_cudnn} (was {prev_cudnn})")
+        else:
+            print(f"[CUDNN_TOGGLE] torch.backends.cudnn.enabled still set to {enable_cudnn}")
 
-        return_tuple = (None, None, None, None, None)
-        if model is not None:
-            return_tuple = (model, None, None, None, None)
-        elif conditioning is not None:
-            return_tuple = (None, conditioning, None, None, None)
-        elif latent is not None:
-            return_tuple = (None, None, latent, None, None)
-        elif audio is not None:
-            return_tuple = (None, None, None, audio, None)
-        elif image is not None:
-            return_tuple = (None, None, None, None, image)
+        if cudnn_benchmark != prev_benchmark:
+            print(f"[CUDNN_TOGGLE] torch.backends.cudnn.benchmark set to {cudnn_benchmark} (was {prev_benchmark})")
+        else:
+            print(f"[CUDNN_TOGGLE] torch.backends.cudnn.benchmark still set to {cudnn_benchmark}")
 
+        return_tuple = (model, conditioning, latent, audio, image, wan_model, any_input, prev_cudnn, prev_benchmark)
         return return_tuple
 
 NODE_CLASS_MAPPINGS = {