diff --git a/monailabel/monaivista/lib/model/vista_point_2pt5/inferer.py b/monailabel/monaivista/lib/model/vista_point_2pt5/inferer.py
index 77e52f7..64b2213 100644
--- a/monailabel/monaivista/lib/model/vista_point_2pt5/inferer.py
+++ b/monailabel/monaivista/lib/model/vista_point_2pt5/inferer.py
@@ -238,14 +238,14 @@ def update_slice(
             continue
 
         inputs = inputs_l[..., start_idx - (n_z_slices // 2) : start_idx + (n_z_slices // 2) + 1].permute(2, 0, 1)
-        if device and (device == "cuda" or isinstance(device, torch.device) and device.type == "cuda"):
+        if device and ((isinstance(device, str) and device.startswith('cuda')) or isinstance(device, torch.device) and device.type == "cuda"):
             inputs = inputs.cuda()
         data, unique_labels = prepare_sam_val_input(
             inputs, class_prompts, point_prompts, start_idx, original_affine, device=device
         )
 
         predictor.eval()
-        if device == "cuda" or (isinstance(device, torch.device) and device.type == "cuda"):
+        if (isinstance(device, str) and device.startswith('cuda')) or (isinstance(device, torch.device) and device.type == "cuda"):
             with torch.cuda.amp.autocast():
                 outputs = predictor(data)
                 logit = outputs[0]["high_res_logits"]
@@ -297,14 +297,14 @@ def iterate_all(
     )
     for start_idx in start_range:
         inputs = inputs_l[..., start_idx - n_z_slices // 2 : start_idx + n_z_slices // 2 + 1].permute(2, 0, 1)
-        if device == "cuda" or (isinstance(device, torch.device) and device.type == "cuda"):
+        if (isinstance(device, str) and device.startswith('cuda')) or (isinstance(device, torch.device) and device.type == "cuda"):
             inputs = inputs.cuda()
         data, unique_labels = prepare_sam_val_input(inputs, class_prompts, point_prompts, start_idx, device=device)
         predictor = predictor.eval()
         with autocast():
             if cachedEmbedding:
                 curr_embedding = cachedEmbedding[start_idx]
-                if device == "cuda" or (isinstance(device, torch.device) and device.type == "cuda"):
+                if (isinstance(device, str) and device.startswith('cuda')) or (isinstance(device, torch.device) and device.type == "cuda"):
                     curr_embedding = curr_embedding.cuda()
                 outputs = predictor.get_mask_prediction(data, curr_embedding)
             else:
diff --git a/monailabel/monaivista/lib/model/vista_point_2pt5/utils/utils.py b/monailabel/monaivista/lib/model/vista_point_2pt5/utils/utils.py
index 695aeee..b2344ca 100644
--- a/monailabel/monaivista/lib/model/vista_point_2pt5/utils/utils.py
+++ b/monailabel/monaivista/lib/model/vista_point_2pt5/utils/utils.py
@@ -88,7 +88,7 @@ def prepare_sam_val_input(inputs, class_prompts, point_prompts, start_idx, origi
 
     class_list = [[i + 1] for i in class_prompts]
     unique_labels = torch.tensor(class_list).long()
-    if device == "cuda" or (isinstance(device, torch.device) and device.type == "cuda"):
+    if (isinstance(device, str) and device.startswith('cuda')) or (isinstance(device, torch.device) and device.type == "cuda"):
         unique_labels = unique_labels.cuda()
 
     volume_point_coords = [cp for cp in foreground_all]
@@ -133,7 +133,7 @@ def prepare_sam_val_input(inputs, class_prompts, point_prompts, start_idx, origi
     if point_coords:
         point_coords = torch.tensor(point_coords).long()
         point_labels = torch.tensor(point_labels).long()
-        if device == "cuda" or (isinstance(device, torch.device) and device.type == "cuda"):
+        if (isinstance(device, str) and device.startswith('cuda')) or (isinstance(device, torch.device) and device.type == "cuda"):
             point_coords = point_coords.cuda()
             point_labels = point_labels.cuda()