diff --git a/modules/sd_models.py b/modules/sd_models.py
index 6774918a..4de59bf4 100644
--- a/modules/sd_models.py
+++ b/modules/sd_models.py
@@ -641,53 +641,7 @@ def load_model(checkpoint_info=None, already_loaded_state_dict=None):
 
 
 def reuse_model_from_already_loaded(sd_model, checkpoint_info, timer):
-    """
-    Checks if the desired checkpoint from checkpoint_info is not already loaded in model_data.loaded_sd_models.
-    If it is loaded, returns that (moving it to GPU if necessary, and moving the currently loadded model to CPU if necessary).
-    If not, returns the model that can be used to load weights from checkpoint_info's file.
-    If no such model exists, returns None.
-    Additionaly deletes loaded models that are over the limit set in settings (sd_checkpoints_limit).
-    """
-
-    already_loaded = None
-    for i in reversed(range(len(model_data.loaded_sd_models))):
-        loaded_model = model_data.loaded_sd_models[i]
-        if loaded_model.sd_checkpoint_info.filename == checkpoint_info.filename:
-            already_loaded = loaded_model
-            continue
-
-        if len(model_data.loaded_sd_models) > shared.opts.sd_checkpoints_limit > 0:
-            print(f"Unloading model {len(model_data.loaded_sd_models)} over the limit of {shared.opts.sd_checkpoints_limit}: {loaded_model.sd_checkpoint_info.title}")
-            model_data.loaded_sd_models.pop()
-
-    if already_loaded is not None:
-        model_data.set_sd_model(already_loaded, already_loaded=True)
-
-        if not SkipWritingToConfig.skip:
-            shared.opts.data["sd_model_checkpoint"] = already_loaded.sd_checkpoint_info.title
-            shared.opts.data["sd_checkpoint_hash"] = already_loaded.sd_checkpoint_info.sha256
-
-        print(f"Using already loaded model {already_loaded.sd_checkpoint_info.title}: done in {timer.summary()}")
-        sd_vae.reload_vae_weights(already_loaded)
-        return model_data.sd_model
-    elif shared.opts.sd_checkpoints_limit > 1 and len(model_data.loaded_sd_models) < shared.opts.sd_checkpoints_limit:
-        print(f"Loading model {checkpoint_info.title} ({len(model_data.loaded_sd_models) + 1} out of {shared.opts.sd_checkpoints_limit})")
-
-        model_data.sd_model = None
-        load_model(checkpoint_info)
-        return model_data.sd_model
-    elif len(model_data.loaded_sd_models) > 0:
-        sd_model = model_data.loaded_sd_models.pop()
-        model_data.sd_model = sd_model
-
-        sd_vae.base_vae = getattr(sd_model, "base_vae", None)
-        sd_vae.loaded_vae_file = getattr(sd_model, "loaded_vae_file", None)
-        sd_vae.checkpoint_info = sd_model.sd_checkpoint_info
-
-        print(f"Reusing loaded model {sd_model.sd_checkpoint_info.title} to load {checkpoint_info.title}")
-        return sd_model
-    else:
-        return None
+    pass
 
 
 def reload_model_weights(sd_model=None, info=None, forced_reload=False):