You can now select the device index with: --directml id

Like this for example: --directml 1

comfy/cli_args.py

@@ -10,7 +10,7 @@ parser.add_argument("--output-directory", type=str, default=None, help="Set the
 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("--dont-upcast-attention", action="store_true", help="Disable upcasting of attention. Can boost speed but increase the chances of black images.")
 parser.add_argument("--force-fp32", action="store_true", help="Force fp32 (If this makes your GPU work better please report it).")
-parser.add_argument("--directml", action="store_true", help="Use torch-directml.")
+parser.add_argument("--directml", type=int, nargs="?", metavar="DIRECTML_DEVICE", const=-1, help="Use torch-directml.")
 
 attn_group = parser.add_mutually_exclusive_group()
 attn_group.add_argument("--use-split-cross-attention", action="store_true", help="Use the split cross attention optimization instead of the sub-quadratic one. Ignored when xformers is used.")

comfy/model_management.py

@@ -21,10 +21,15 @@ accelerate_enabled = False
 xpu_available = False
 
 directml_enabled = False
-if args.directml:
+if args.directml is not None:
     import torch_directml
-    print("Using directml")
     directml_enabled = True
+    device_index = args.directml
+    if device_index < 0:
+        directml_device = torch_directml.device()
+    else:
+        directml_device = torch_directml.device(device_index)
+    print("Using directml with device:", torch_directml.device_name(device_index))
     # torch_directml.disable_tiled_resources(True)
 
 try:
@@ -226,7 +231,8 @@ def get_torch_device():
     global xpu_available
     global directml_enabled
     if directml_enabled:
-        return torch_directml.device()
+        global directml_device
+        return directml_device
     if vram_state == VRAMState.MPS:
         return torch.device("mps")
     if vram_state == VRAMState.CPU: