diff --git a/delete_model_passthrough.py b/delete_model_passthrough.py
index 38562e1..1715dcd 100644
--- a/delete_model_passthrough.py
+++ b/delete_model_passthrough.py
@@ -1,32 +1,91 @@
-import torch
-import gc
-import psutil
-import os
-import ctypes
+import torch, gc, psutil
+import comfy.model_management as mm
 
 class AnyType(str):
-    def __ne__(self, __value: object) -> bool:
-        return False
-
+    def __ne__(self, __value: object) -> bool: return False
 any_typ = AnyType("*")
 
 
+def hard_free(model):
+    try:
+        # Explicitly nuke parameters and buffers
+        if hasattr(model, "parameters"):
+            for p in model.parameters():
+                if p is not None:
+                    p.detach_()
+                    del p
+        if hasattr(model, "buffers"):
+            for b in model.buffers():
+                if b is not None:
+                    del b
+        # Clear state_dict if exists
+        if hasattr(model, "state_dict"):
+            sd = model.state_dict()
+            for k in list(sd.keys()):
+                del sd[k]
+            del sd
+    except Exception as e:
+        print(f"Hard free error: {e}")
+
+    try:
+        del model
+    except:
+        pass
+
+    gc.collect()
+    if torch.cuda.is_available():
+        torch.cuda.empty_cache()
+        torch.cuda.ipc_collect()
+
+
+def purge_specific_from_comfy(model):
+    """
+    Surgically remove THIS model object from ComfyUI's caches
+    without touching unrelated ones. Returns a type string.
+    """
+    deleted_type = "Unknown"
+
+    try:
+        if mm.current_model == model:
+            mm.current_model = None
+            deleted_type = "Diffusion/UNet"
+
+        if hasattr(mm, "loaded_models"):
+            for k, v in list(mm.loaded_models.items()):
+                if v is model:
+                    del mm.loaded_models[k]
+                    deleted_type = "Diffusion/UNet"
+
+        if hasattr(mm, "loaded_clip"):
+            for k, v in list(mm.loaded_clip.items()):
+                if v is model:
+                    del mm.loaded_clip[k]
+                    deleted_type = "CLIP"
+
+        if hasattr(mm, "loaded_vae"):
+            for k, v in list(mm.loaded_vae.items()):
+                if v is model:
+                    del mm.loaded_vae[k]
+                    deleted_type = "VAE"
+
+    except Exception as e:
+        print(f"Cache purge error: {e}")
+
+    return deleted_type
+
+
 class DeleteModelPassthrough:
     """
-    ComfyUI Custom Node that:
-      - Accepts any input (data) and a MODEL (`model`).
-      - Deletes the MODEL completely (VRAM + RAM).
-      - Passes through the data unchanged.
+    ComfyUI Custom Node:
+      - Accepts any input + a model (UNet/CLIP/VAE/latent).
+      - Deletes ONLY that model from VRAM, RAM, and ComfyUI cache.
+      - Auto-detects the model type and logs it.
+      - Passes the data unchanged.
     """
 
     @classmethod
     def INPUT_TYPES(cls):
-        return {
-            "required": {
-                "data": (any_typ,),
-                "model": (any_typ,),
-            },
-        }
+        return {"required": {"data": (any_typ,), "model": (any_typ,)}}
  
     RETURN_TYPES = (any_typ,)
     RETURN_NAMES = ("output",)
@@ -34,38 +93,24 @@ class DeleteModelPassthrough:
     CATEGORY = "Memory Management"
 
     def run(self, data, model):
+        before_vram = torch.cuda.memory_allocated() if torch.cuda.is_available() else 0
+        before_res  = torch.cuda.memory_reserved() if torch.cuda.is_available() else 0
+        before_ram  = psutil.virtual_memory().percent
 
-        before = psutil.virtual_memory().percent
-        collected = gc.collect()
-        after = psutil.virtual_memory().percent
-        freedr = before - after
-        print(f"System RAM freed: {freedr:.2f}%, GC collected {collected} objects.")
+        deleted_type = purge_specific_from_comfy(model)
+        hard_free(model)
 
-        if not torch.cuda.is_available():
-            return "CUDA not available."
-        initial = torch.cuda.memory_allocated()
-        print(f"Initial GPU memory: {initial}")
-        
-        try:
-            del model
-            torch.cuda.empty_cache()
-            gc.collect()
-            print("Deleted MODEL completely from VRAM.")
-        except Exception as e:
-            print(f"Failed to delete model: {e}")
+        after_vram = torch.cuda.memory_allocated() if torch.cuda.is_available() else 0
+        after_res  = torch.cuda.memory_reserved() if torch.cuda.is_available() else 0
+        after_ram  = psutil.virtual_memory().percent
 
-        final = torch.cuda.memory_allocated()
-        print(f"Final GPU memory: {final}")
-        freed = max(0, initial - final)
-        print(f"GPU VRAM freed: {freed/1e9:.2f} GB")
+        print(f"🗑️ Deleted model type: {deleted_type}")
+        print(f"System RAM change: {before_ram - after_ram:.2f}%")
+        print(f"GPU allocated freed: {(before_vram - after_vram)/1e9:.2f} GB")
+        print(f"GPU reserved freed: {(before_res - after_res)/1e9:.2f} GB")
 
         return (data,)
 
 
-NODE_CLASS_MAPPINGS = {
-    "DeleteModelPassthrough": DeleteModelPassthrough,
-}
-
-NODE_DISPLAY_NAME_MAPPINGS = {
-    "DeleteModelPassthrough": "Delete Model (Passthrough Any)",
-}
+NODE_CLASS_MAPPINGS = {"DeleteModelPassthrough": DeleteModelPassthrough}
+NODE_DISPLAY_NAME_MAPPINGS = {"DeleteModelPassthrough": "Delete Model (Passthrough Any)"}