diff --git a/vllm/v1/structured_output/utils.py b/vllm/v1/structured_output/utils.py
index 0d31363cb5b4..9fc1accb2e2c 100644
--- a/vllm/v1/structured_output/utils.py
+++ b/vllm/v1/structured_output/utils.py
@@ -17,6 +17,7 @@
 import vllm.envs as envs
 from vllm.logger import init_logger
 from vllm.utils.import_utils import LazyLoader
+from vllm.utils.platform_utils import is_pin_memory_available
 from vllm.v1.core.sched.output import GrammarOutput, SchedulerOutput
 
 if TYPE_CHECKING:
@@ -106,28 +107,33 @@ def apply_grammar_bitmask(
     # since the bitmask is already aligned with the logits.
     skip_out_indices = len(out_indices) == logits.shape[0]
 
-    index_tensor = None
-    if not skip_out_indices:
-        # xgrammar expects a python list of indices but it will actually work with
-        # a tensor. If we copy the tensor ourselves here we can do it in a non_blocking
-        # manner and there should be no cpu sync within xgrammar.
-        index_tensor = torch.tensor(
-            out_indices, dtype=torch.int32, device="cpu", pin_memory=True
-        )
-        index_tensor = index_tensor.to(logits.device, non_blocking=True)
+    if not logits.is_cpu:
+        index_tensor = None
+        if not skip_out_indices:
+            # xgrammar expects a python list of indices but it will actually work with
+            # a tensor. If we copy the tensor ourselves here we can do it in a
+            # non_blocking manner and there should be no cpu sync within xgrammar.
+            pin_memory = is_pin_memory_available()
+            index_tensor = torch.tensor(
+                out_indices, dtype=torch.int32, device="cpu", pin_memory=pin_memory
+            )
+            index_tensor = index_tensor.to(logits.device, non_blocking=True)
+
+        xgr.apply_token_bitmask_inplace(logits, grammar_bitmask, indices=index_tensor)
+        return
 
+    # CPU case, use list for indices.
+    indices = None if skip_out_indices else out_indices
     # Handle dtype conversion for CPU (older xgrammar CPU kernels require float32)
     # See: https://github.com/vllm-project/vllm/issues/31901
-    if logits.device.type == "cpu" and logits.dtype != torch.float32:
+    if logits.dtype != torch.float32:
         # Convert to float32, apply bitmask, then convert back
-        logits_float32 = logits.to(torch.float32)
-        xgr.apply_token_bitmask_inplace(
-            logits_float32, grammar_bitmask, indices=index_tensor
-        )
+        logits_fp32 = logits.to(torch.float32)
+        xgr.apply_token_bitmask_inplace(logits_fp32, grammar_bitmask, indices=indices)
         # Copy the modified values back to the original tensor
-        logits.copy_(logits_float32.to(logits.dtype))
+        logits.copy_(logits_fp32.to(logits.dtype))
     else:
-        xgr.apply_token_bitmask_inplace(logits, grammar_bitmask, indices=index_tensor)
+        xgr.apply_token_bitmask_inplace(logits, grammar_bitmask, indices=indices)
 
 
 class OutlinesVocabulary: