diff --git a/comfy/model_management.py b/comfy/model_management.py
index 304931eb0..d59d6b354 100644
--- a/comfy/model_management.py
+++ b/comfy/model_management.py
@@ -1213,7 +1213,8 @@ def cast_to(weight, dtype=None, device=None, non_blocking=False, copy=False, str
 
         signature = comfy_aimdo.model_vbar.vbar_fault(weight._v)
         if signature is not None:
-            v_tensor = comfy.memory_management.interpret_gathered_like(cast_geometry, weight._v_tensor)[0]
+            raw_tensor = comfy_aimdo.torch.aimdo_to_tensor(weight._v, device)
+            v_tensor = comfy.memory_management.interpret_gathered_like(cast_geometry, raw_tensor)[0]
             if not comfy_aimdo.model_vbar.vbar_signature_compare(signature, weight._v_signature):
                 weight._v_signature = signature
                 #Send it over
diff --git a/comfy/model_patcher.py b/comfy/model_patcher.py
index 19c9031ea..224e218e3 100644
--- a/comfy/model_patcher.py
+++ b/comfy/model_patcher.py
@@ -1542,7 +1542,6 @@ class ModelPatcherDynamic(ModelPatcher):
 
                     if vbar is not None and not hasattr(m, "_v"):
                         m._v = vbar.alloc(v_weight_size)
-                        m._v_tensor = comfy_aimdo.torch.aimdo_to_tensor(m._v, device_to)
                     allocated_size += v_weight_size
 
                 else:
@@ -1557,7 +1556,6 @@ class ModelPatcherDynamic(ModelPatcher):
                         weight_size = geometry.numel() * geometry.element_size()
                         if vbar is not None and not hasattr(weight, "_v"):
                             weight._v = vbar.alloc(weight_size)
-                            weight._v_tensor = comfy_aimdo.torch.aimdo_to_tensor(weight._v, device_to)
                             weight._model_dtype = model_dtype
                         allocated_size += weight_size
                     vbar.set_watermark_limit(allocated_size)
diff --git a/comfy/ops.py b/comfy/ops.py
index 33803b223..057535c8c 100644
--- a/comfy/ops.py
+++ b/comfy/ops.py
@@ -87,7 +87,7 @@ def cast_bias_weight_with_vbar(s, dtype, device, bias_dtype, non_blocking, compu
 
     signature = comfy_aimdo.model_vbar.vbar_fault(s._v)
     if signature is not None:
-        xfer_dest = s._v_tensor
+        xfer_dest = comfy_aimdo.torch.aimdo_to_tensor(s._v, device)
     resident = comfy_aimdo.model_vbar.vbar_signature_compare(signature, s._v_signature)
 
     if not resident: