diff --git a/comfy/model_management.py b/comfy/model_management.py
index b01c4d7fa..83cb5d277 100644
--- a/comfy/model_management.py
+++ b/comfy/model_management.py
@@ -190,6 +190,14 @@ def is_wsl():
         return True
     return False
 
+_WSL_SOFT_EMPTY_CACHE_SKIP_LOGGED = False
+
+def wsl_skip_nonforced_soft_empty_cache():
+    return is_wsl() and os.getenv("COMFYUI_WSL_SOFT_EMPTY_CACHE", "0") != "1"
+
+def wsl_skip_model_load_synchronize():
+    return is_wsl() and os.getenv("COMFYUI_WSL_MODEL_LOAD_SYNCHRONIZE", "0") != "1"
+
 def get_torch_device():
     global directml_enabled
     global cpu_state
@@ -917,7 +925,14 @@ def load_models_gpu(models, memory_required=0, force_patch_weights=False, minimu
         if vram_set_state == VRAMState.NO_VRAM:
             lowvram_model_memory = 0.1
 
+        model_name = model.model.__class__.__name__ if hasattr(model, "model") else model.__class__.__name__
+        logging.info(
+            f"Loading model {model_name} start: device={torch_dev} "
+            f"vram_state={vram_set_state.name} lowvram_model_memory={lowvram_model_memory} "
+            f"force_full_load={force_full_load} force_patch_weights={force_patch_weights}"
+        )
         loaded_model.model_load(lowvram_model_memory, force_patch_weights=force_patch_weights)
+        logging.info(f"Loading model {model_name} complete")
         current_loaded_models.insert(0, loaded_model)
     return
 
@@ -1955,6 +1970,12 @@ def soft_empty_cache(force=False):
     elif is_mlu():
         torch.mlu.empty_cache()
     elif torch.cuda.is_available():
+        if wsl_skip_nonforced_soft_empty_cache() and not force:
+            global _WSL_SOFT_EMPTY_CACHE_SKIP_LOGGED
+            if not _WSL_SOFT_EMPTY_CACHE_SKIP_LOGGED:
+                logging.info("Skipping non-forced CUDA soft_empty_cache on WSL; set COMFYUI_WSL_SOFT_EMPTY_CACHE=1 to re-enable.")
+                _WSL_SOFT_EMPTY_CACHE_SKIP_LOGGED = True
+            return
         torch.cuda.synchronize()
         torch.cuda.empty_cache()
         torch.cuda.ipc_collect()
diff --git a/comfy/model_patcher.py b/comfy/model_patcher.py
index 00a15fa63..d7a2fb704 100644
--- a/comfy/model_patcher.py
+++ b/comfy/model_patcher.py
@@ -42,6 +42,8 @@ from comfy.patcher_extension import CallbacksMP, PatcherInjection, WrappersMP
 
 import comfy_aimdo.model_vbar
 
+_WSL_MODEL_LOAD_SYNC_SKIP_LOGGED = False
+
 def set_model_options_patch_replace(model_options, patch, name, block_name, number, transformer_index=None):
     to = model_options["transformer_options"].copy()
 
@@ -1005,6 +1007,11 @@ class ModelPatcher:
                 mem_counter += move_weight_functions(m, device_to)
 
             load_completely.sort(reverse=True)
+            skip_wsl_load_sync = comfy.model_management.is_device_cuda(device_to) and comfy.model_management.wsl_skip_model_load_synchronize()
+            global _WSL_MODEL_LOAD_SYNC_SKIP_LOGGED
+            if skip_wsl_load_sync and len(load_completely) > 0 and not _WSL_MODEL_LOAD_SYNC_SKIP_LOGGED:
+                logging.info("Skipping per-module CUDA synchronize during model load on WSL; set COMFYUI_WSL_MODEL_LOAD_SYNCHRONIZE=1 to re-enable.")
+                _WSL_MODEL_LOAD_SYNC_SKIP_LOGGED = True
             for x in load_completely:
                 n = x[1]
                 m = x[2]
@@ -1019,7 +1026,7 @@ class ModelPatcher:
                     key = key_param_name_to_key(n, param)
                     self.unpin_weight(key)
                     self.patch_weight_to_device(key, device_to=device_to)
-                if comfy.model_management.is_device_cuda(device_to):
+                if comfy.model_management.is_device_cuda(device_to) and not skip_wsl_load_sync:
                     torch.cuda.synchronize()
 
                 logging.debug("lowvram: loaded module regularly {} {}".format(n, m))