diff --git a/src/transformers/quantizers/quantizer_gptq.py b/src/transformers/quantizers/quantizer_gptq.py
index 0fc35bea163..0aacfd55f36 100644
--- a/src/transformers/quantizers/quantizer_gptq.py
+++ b/src/transformers/quantizers/quantizer_gptq.py
@@ -22,7 +22,14 @@ from .base import HfQuantizer
 if TYPE_CHECKING:
     from ..modeling_utils import PreTrainedModel
 
-from ..utils import is_auto_gptq_available, is_gptqmodel_available, is_optimum_available, is_torch_available, logging
+from ..utils import (
+    is_auto_gptq_available,
+    is_gptqmodel_available,
+    is_optimum_available,
+    is_torch_available,
+    is_torch_xpu_available,
+    logging,
+)
 from ..utils.quantization_config import GPTQConfig, QuantizationConfigMixin
 
 
@@ -89,7 +96,12 @@ class GptqHfQuantizer(HfQuantizer):
 
     def update_device_map(self, device_map):
         if device_map is None:
-            device_map = {"": torch.device("cpu")}
+            if torch.cuda.is_available():
+                device_map = {"": torch.cuda.current_device()}
+            elif is_torch_xpu_available():
+                device_map = {"": torch.xpu.current_device()}
+            else:
+                device_map = {"": "cpu"}
         # Only with auto-gptq do not support CPU, we should move the model to cuda if available.
         if not is_gptqmodel_available() and device_map in ("cpu", {"": torch.device("cpu")}):
             device_map == {"": 0}