diff --git a/modules/sd_models.py b/modules/sd_models.py
index e4dba62c..cd7fe37a 100644
--- a/modules/sd_models.py
+++ b/modules/sd_models.py
@@ -220,6 +220,7 @@ def load_model_weights(model, checkpoint_info, vae_file="auto"):
     model.sd_model_checkpoint = checkpoint_file
     model.sd_checkpoint_info = checkpoint_info
 
+    sd_vae.delete_base_vae()
     sd_vae.clear_loaded_vae()
     sd_vae.load_vae(model, vae_file)
 
diff --git a/modules/sd_vae.py b/modules/sd_vae.py
index dd69a5e6..13bf3d31 100644
--- a/modules/sd_vae.py
+++ b/modules/sd_vae.py
@@ -154,8 +154,7 @@ def load_vae(model, vae_file=None):
         if vae_opt not in vae_dict:
             vae_dict[vae_opt] = vae_file
             vae_list.append(vae_opt)
-            # shared.opts.data['sd_vae'] = vae_opt
-    else:
+    elif loaded_vae_file:
         restore_base_vae(model)
 
     loaded_vae_file = vae_file
diff --git a/modules/shared.py b/modules/shared.py
index 17132e42..a9daf800 100644
--- a/modules/shared.py
+++ b/modules/shared.py
@@ -335,7 +335,7 @@ options_templates.update(options_section(('training', "Training"), {
 options_templates.update(options_section(('sd', "Stable Diffusion"), {
     "sd_model_checkpoint": OptionInfo(None, "Stable Diffusion checkpoint", gr.Dropdown, lambda: {"choices": modules.sd_models.checkpoint_tiles()}, refresh=sd_models.list_models),
     "sd_checkpoint_cache": OptionInfo(0, "Checkpoints to cache in RAM", gr.Slider, {"minimum": 0, "maximum": 10, "step": 1}),
-    "sd_vae": OptionInfo("auto", "SD VAE", gr.Dropdown, lambda: {"choices": list(sd_vae.vae_list)}, refresh=sd_vae.refresh_vae_list),
+    "sd_vae": OptionInfo("auto", "SD VAE", gr.Dropdown, lambda: {"choices": sd_vae.vae_list}, refresh=sd_vae.refresh_vae_list),
     "sd_hypernetwork": OptionInfo("None", "Hypernetwork", gr.Dropdown, lambda: {"choices": ["None"] + [x for x in hypernetworks.keys()]}, refresh=reload_hypernetworks),
     "sd_hypernetwork_strength": OptionInfo(1.0, "Hypernetwork strength", gr.Slider, {"minimum": 0.0, "maximum": 1.0, "step": 0.001}),
     "inpainting_mask_weight": OptionInfo(1.0, "Inpainting conditioning mask strength", gr.Slider, {"minimum": 0.0, "maximum": 1.0, "step": 0.01}),