diff --git a/cfz/nodes/cfz_vae_loader.py b/cfz/nodes/cfz_vae_loader.py
index 1298376c0..d3de746cb 100644
--- a/cfz/nodes/cfz_vae_loader.py
+++ b/cfz/nodes/cfz_vae_loader.py
@@ -1,6 +1,6 @@
 import torch
 import folder_paths
-from comfy import model_management
+from comfy import model_management, model_base
 from nodes import VAELoader
 
 class CFZVAELoader:
@@ -15,7 +15,7 @@ class CFZVAELoader:
     
     RETURN_TYPES = ("VAE",)
     FUNCTION = "load_vae"
-    CATEGORY = "CFZ/loaders"
+    CATEGORY = "loaders"
     TITLE = "CFZ VAE Loader"
 
     def load_vae(self, vae_name, precision):
@@ -27,30 +27,58 @@ class CFZVAELoader:
         }
         target_dtype = dtype_map[precision]
         
-        # Temporarily patch model_management functions
-        original_should_use_bf16 = model_management.should_use_bf16
-        original_should_use_fp16 = model_management.should_use_fp16
-        
-        def custom_should_use_bf16(*args, **kwargs):
-            return precision == "bf16"
-        
-        def custom_should_use_fp16(*args, **kwargs):
-            return precision == "fp16"
-        
-        # Apply patches
-        model_management.should_use_bf16 = custom_should_use_bf16
-        model_management.should_use_fp16 = custom_should_use_fp16
+        # Patch vae_dtype for loading
+        original_vae_dtype = model_management.vae_dtype
+        model_management.vae_dtype = lambda *args, **kwargs: target_dtype
         
         try:
-            # Load the VAE with patched precision functions
+            # Load VAE
             vae_loader = VAELoader()
             vae = vae_loader.load_vae(vae_name)[0]
-            print(f"[CFZ VAE] VAE loaded with precision {precision}")
-            return (vae,)
         finally:
-            # Restore original functions
-            model_management.should_use_bf16 = original_should_use_bf16
-            model_management.should_use_fp16 = original_should_use_fp16
+            model_management.vae_dtype = original_vae_dtype
+        
+        # Override VAE methods to maintain dtype
+        if hasattr(vae, 'patcher'):
+            # Override model_dtype
+            vae.patcher.model_dtype = lambda: target_dtype
+            
+            # Wrap the decode method to ensure proper dtype handling
+            if hasattr(vae, 'decode'):
+                original_decode = vae.decode
+                
+                def forced_dtype_decode(samples_in):
+                    # Ensure model is in correct dtype before decode
+                    if hasattr(vae, 'first_stage_model'):
+                        vae.first_stage_model = vae.first_stage_model.to(target_dtype)
+                    
+                    # Convert input to match model dtype
+                    if isinstance(samples_in, torch.Tensor):
+                        samples_in = samples_in.to(target_dtype)
+                    
+                    return original_decode(samples_in)
+                
+                vae.decode = forced_dtype_decode
+            
+            # Wrap encode similarly
+            if hasattr(vae, 'encode'):
+                original_encode = vae.encode
+                
+                def forced_dtype_encode(pixels):
+                    # Ensure model is in correct dtype
+                    if hasattr(vae, 'first_stage_model'):
+                        vae.first_stage_model = vae.first_stage_model.to(target_dtype)
+                    
+                    # Convert input to match model dtype
+                    if isinstance(pixels, torch.Tensor):
+                        pixels = pixels.to(target_dtype)
+                    
+                    return original_encode(pixels)
+                
+                vae.encode = forced_dtype_encode
+        
+        print(f"CFZ VAE: Loaded with precision {precision} (dtype: {target_dtype})")
+        return (vae,)
 
 # Node mappings for ComfyUI
 NODE_CLASS_MAPPINGS = {
@@ -59,5 +87,4 @@ NODE_CLASS_MAPPINGS = {
 
 NODE_DISPLAY_NAME_MAPPINGS = {
     "CFZVAELoader": "CFZ VAE Loader"
-
 }