diff --git a/modules/models/flux/flux.py b/modules/models/flux/flux.py
index eb17a31c7..14fa4e255 100644
--- a/modules/models/flux/flux.py
+++ b/modules/models/flux/flux.py
@@ -270,7 +270,8 @@ class FLUX1Inferencer(torch.nn.Module):
         with torch.no_grad():
             self.model = BaseModel(state_dict=state_dict, prefix=diffusion_model_prefix, device="cpu", dtype=devices.dtype)
             self.first_stage_model = SDVAE(device="cpu", dtype=devices.dtype_vae)
-            self.first_stage_model.dtype = self.model.diffusion_model.dtype
+            self.first_stage_model.dtype = devices.dtype_vae
+            self.vae = self.first_stage_model # real vae
 
         self.alphas_cumprod = 1 / (self.model.model_sampling.sigmas ** 2 + 1)
 
diff --git a/modules/sd_models.py b/modules/sd_models.py
index 41649970b..b4702151a 100644
--- a/modules/sd_models.py
+++ b/modules/sd_models.py
@@ -956,6 +956,8 @@ def load_model(checkpoint_info=None, already_loaded_state_dict=None, checkpoint_
     else:
         weight_dtype_conversion = {
             'first_stage_model': None,
+            'text_encoders': None,
+            'vae': None,
             'alphas_cumprod': None,
             '': torch.float16 if loadable_unet_dtype in (torch.float16, torch.float32, torch.bfloat16) else None,
         }