diff --git a/comfy/cli_args.py b/comfy/cli_args.py
index e7ce256b..29e5fb15 100644
--- a/comfy/cli_args.py
+++ b/comfy/cli_args.py
@@ -40,7 +40,10 @@ parser.add_argument("--extra-model-paths-config", type=str, default=None, metava
 parser.add_argument("--output-directory", type=str, default=None, help="Set the ComfyUI output directory.")
 parser.add_argument("--auto-launch", action="store_true", help="Automatically launch ComfyUI in the default browser.")
 parser.add_argument("--cuda-device", type=int, default=None, metavar="DEVICE_ID", help="Set the id of the cuda device this instance will use.")
-parser.add_argument("--cuda-malloc", action="store_true", help="Enable cudaMallocAsync.")
+cm_group = parser.add_mutually_exclusive_group()
+cm_group.add_argument("--cuda-malloc", action="store_true", help="Enable cudaMallocAsync (enabled by default for torch 2.0 and up).")
+cm_group.add_argument("--disable-cuda-malloc", action="store_true", help="Enable cudaMallocAsync.")
+
 parser.add_argument("--dont-upcast-attention", action="store_true", help="Disable upcasting of attention. Can boost speed but increase the chances of black images.")
 
 fp_group = parser.add_mutually_exclusive_group()
@@ -85,4 +88,3 @@ args = parser.parse_args()
 
 if args.windows_standalone_build:
     args.auto_launch = True
-    args.cuda_malloc = True #work around memory issue in nvidia drivers > 531
diff --git a/main.py b/main.py
index a2254557..61ba9e8e 100644
--- a/main.py
+++ b/main.py
@@ -61,7 +61,23 @@ if __name__ == "__main__":
         os.environ['CUDA_VISIBLE_DEVICES'] = str(args.cuda_device)
         print("Set cuda device to:", args.cuda_device)
 
-    if args.cuda_malloc:
+    if not args.cuda_malloc:
+        try: #if there's a better way to check the torch version without importing it let me know
+            version = ""
+            torch_spec = importlib.util.find_spec("torch")
+            for folder in torch_spec.submodule_search_locations:
+                ver_file = os.path.join(folder, "version.py")
+                if os.path.isfile(ver_file):
+                    spec = importlib.util.spec_from_file_location("torch_version_import", ver_file)
+                    module = importlib.util.module_from_spec(spec)
+                    spec.loader.exec_module(module)
+                    version = module.__version__
+            if int(version[0]) >= 2: #enable by default for torch version 2.0 and up
+                args.cuda_malloc = True
+        except:
+            pass
+
+    if args.cuda_malloc and not args.disable_cuda_malloc:
         env_var = os.environ.get('PYTORCH_CUDA_ALLOC_CONF', None)
         if env_var is None:
             env_var = "backend:cudaMallocAsync"