diff --git a/comfy/model_management.py b/comfy/model_management.py
index 5c3033127..a4840f688 100644
--- a/comfy/model_management.py
+++ b/comfy/model_management.py
@@ -47,11 +47,10 @@ if args.deterministic:
     logging.info("Using deterministic algorithms for pytorch")
     torch.use_deterministic_algorithms(True, warn_only=True)
 
-directml_enabled = False
+directml_device = None
 if args.directml is not None:
     import torch_directml # pylint: disable=import-error
 
-    directml_enabled = True
     device_index = args.directml
     if device_index < 0:
         directml_device = torch_directml.device()
@@ -90,10 +89,9 @@ def is_intel_xpu():
 
 
 def get_torch_device():
-    global directml_enabled
+    global directml_device
     global cpu_state
-    if directml_enabled:
-        global directml_device
+    if directml_device:
         return directml_device
     if cpu_state == CPUState.MPS:
         return torch.device("mps")
@@ -111,7 +109,7 @@ def get_torch_device():
 
 
 def get_total_memory(dev=None, torch_total_too=False):
-    global directml_enabled
+    global directml_device
     if dev is None:
         dev = get_torch_device()
 
@@ -119,7 +117,7 @@ def get_total_memory(dev=None, torch_total_too=False):
         mem_total = psutil.virtual_memory().total
         mem_total_torch = mem_total
     else:
-        if directml_enabled:
+        if directml_device:
             mem_total = 1024 * 1024 * 1024  # TODO
             mem_total_torch = mem_total
         elif is_intel_xpu():
@@ -707,7 +705,7 @@ def supports_cast(device, dtype): #TODO
         return True
     if is_device_mps(device):
         return False
-    if directml_enabled: #TODO: test this
+    if directml_device: #TODO: test this
         return False
     if dtype == torch.bfloat16:
         return True
@@ -722,7 +720,7 @@ def device_supports_non_blocking(device):
         return False  # pytorch bug? mps doesn't support non blocking
     if args.deterministic: #TODO: figure out why deterministic breaks non blocking from gpu to cpu (previews)
         return False
-    if directml_enabled:
+    if directml_device:
         return False
     return True
 
@@ -759,13 +757,13 @@ def cast_to_device(tensor, device, dtype, copy=False):
 
 
 def xformers_enabled():
-    global directml_enabled
+    global directml_device
     global cpu_state
     if cpu_state != CPUState.GPU:
         return False
     if is_intel_xpu():
         return False
-    if directml_enabled:
+    if directml_device:
         return False
     return XFORMERS_IS_AVAILABLE
 
@@ -806,7 +804,7 @@ def force_upcast_attention_dtype():
         return None
 
 def get_free_memory(dev=None, torch_free_too=False):
-    global directml_enabled
+    global directml_device
     if dev is None:
         dev = get_torch_device()
 
@@ -814,7 +812,7 @@ def get_free_memory(dev=None, torch_free_too=False):
         mem_free_total = psutil.virtual_memory().available
         mem_free_torch = mem_free_total
     else:
-        if directml_enabled:
+        if directml_device:
             mem_free_total = 1024 * 1024 * 1024  # TODO
             mem_free_torch = mem_free_total
         elif is_intel_xpu():
@@ -864,7 +862,7 @@ def is_device_cuda(device):
 
 
 def should_use_fp16(device=None, model_params=0, prioritize_performance=True, manual_cast=False):
-    global directml_enabled
+    global directml_device
 
     if device is not None:
         if is_device_cpu(device):
@@ -880,7 +878,7 @@ def should_use_fp16(device=None, model_params=0, prioritize_performance=True, ma
     if FORCE_FP32:
         return False
 
-    if directml_enabled:
+    if directml_device:
         return False
 
     if mps_mode():
@@ -943,7 +941,7 @@ def should_use_bf16(device=None, model_params=0, prioritize_performance=True, ma
     if FORCE_FP32:
         return False
 
-    if directml_enabled:
+    if directml_device:
         return False
 
     if cpu_mode() or mps_mode():