diff --git a/comfy/multigpu.py b/comfy/multigpu.py
index 096270c12..eff7d0649 100644
--- a/comfy/multigpu.py
+++ b/comfy/multigpu.py
@@ -162,16 +162,16 @@ def create_multigpu_deepclones(model: ModelPatcher, max_gpus: int, gpu_options:
         gpu_options.register(model)
     else:
         logging.info("No extra torch devices need initialization, skipping initializing MultiGPU Work Units.")
-    # TODO: only keep model clones that don't go 'past' the intended max_gpu count
-    # multigpu_models = model.get_additional_models_with_key("multigpu")
-    # new_multigpu_models = []
-    # for m in multigpu_models:
-    #     if m.load_device in limit_extra_devices:
-    #         new_multigpu_models.append(m)
-    # model.set_additional_models("multigpu", new_multigpu_models)
-    # persist skip_devices for use in sampling code
-    # if len(skip_devices) > 0 or "multigpu_skip_devices" in model.model_options:
-    #     model.model_options["multigpu_skip_devices"] = skip_devices
+    # only keep model clones that don't go 'past' the intended max_gpu count;
+    # this prunes any inherited multigpu clones whose load_device is no longer allowed
+    # when max_gpus is lowered between runs.
+    allowed_devices = set(limit_extra_devices)
+    allowed_devices.add(model.load_device)
+    multigpu_models = model.get_additional_models_with_key("multigpu")
+    new_multigpu_models = [m for m in multigpu_models if m.load_device in allowed_devices]
+    if len(new_multigpu_models) != len(multigpu_models):
+        model.set_additional_models("multigpu", new_multigpu_models)
+        model.match_multigpu_clones()
     return model