diff --git a/comfy/sd.py b/comfy/sd.py
index 12f1373c5..2acb50e53 100644
--- a/comfy/sd.py
+++ b/comfy/sd.py
@@ -290,6 +290,16 @@ class CLIP:
         if full_model:
             return self.cond_stage_model.load_state_dict(sd, strict=False, assign=self.patcher.is_dynamic())
         else:
+            can_assign = self.patcher.is_dynamic()
+            self.cond_stage_model.can_assign_sd = can_assign
+
+            # The CLIP models are a pretty complex web of wrappers and its
+            # a bit of an API change to plumb this all the way through.
+            # So spray paint the model with this flag that the loading
+            # nn.Module can then inspect for itself.
+            for m in self.cond_stage_model.modules():
+                m.can_assign_sd = can_assign
+
             return self.cond_stage_model.load_sd(sd)
 
     def get_sd(self):
diff --git a/comfy/sd1_clip.py b/comfy/sd1_clip.py
index c512ca5d0..b9380e021 100644
--- a/comfy/sd1_clip.py
+++ b/comfy/sd1_clip.py
@@ -297,7 +297,7 @@ class SDClipModel(torch.nn.Module, ClipTokenWeightEncoder):
         return self(tokens)
 
     def load_sd(self, sd):
-        return self.transformer.load_state_dict(sd, strict=False)
+        return self.transformer.load_state_dict(sd, strict=False, assign=getattr(self, "can_assign_sd", False))
 
 def parse_parentheses(string):
     result = []
diff --git a/comfy/text_encoders/lt.py b/comfy/text_encoders/lt.py
index 776e25e97..145c4e2ac 100644
--- a/comfy/text_encoders/lt.py
+++ b/comfy/text_encoders/lt.py
@@ -119,7 +119,7 @@ class LTXAVTEModel(torch.nn.Module):
             if len(sdo) == 0:
                 sdo = sd
 
-            return self.load_state_dict(sdo, strict=False)
+            return self.load_state_dict(sdo, strict=False, assign=getattr(self, "can_assign_sd", False))
 
     def memory_estimation_function(self, token_weight_pairs, device=None):
         constant = 6.0