diff --git a/tests/ut/attention/test_mla_v1.py b/tests/ut/attention/test_mla_v1.py
index c55234bc3d..ebfea50e85 100644
--- a/tests/ut/attention/test_mla_v1.py
+++ b/tests/ut/attention/test_mla_v1.py
@@ -82,7 +82,8 @@ def test_ascend_mla_prefill_metadata_with_chunked_context(self):
             seq_tot=seq_tot,
             max_seq_lens=max_seq_lens,
             workspace=workspace,
-            chunk_seq_lens=chunk_seq_lens)
+            chunk_seq_lens=chunk_seq_lens,
+            chunk_seq_lens_npu=chunk_seq_lens.npu())
 
         metadata = AscendMLAPrefillMetadata(
             attn_mask=torch.tensor([[1, 0], [1, 1]], dtype=torch.bool),
diff --git a/vllm_ascend/attention/mla_v1.py b/vllm_ascend/attention/mla_v1.py
index 86418720af..1f2a5c486a 100644
--- a/vllm_ascend/attention/mla_v1.py
+++ b/vllm_ascend/attention/mla_v1.py
@@ -79,6 +79,7 @@ class ChunkedContextMetadata:
         max_seq_lens: list[int]
         workspace: torch.Tensor
         chunk_seq_lens: torch.Tensor
+        chunk_seq_lens_npu: torch.Tensor
 
     attn_mask: torch.Tensor
     query_lens: torch.Tensor
@@ -370,6 +371,7 @@ def build(
                     seq_tot=chunk_seq_lens.sum(dim=1).tolist(),
                     max_seq_lens=chunk_seq_lens.max(dim=1).values.tolist(),
                     chunk_seq_lens=chunk_seq_lens,
+                    chunk_seq_lens_npu=chunk_seq_lens.to(device),
                     workspace=self.chunked_prefill_workspace,
                 )
             prefill_input_positions = input_positions[tokens_start:]
@@ -774,6 +776,8 @@ def _compute_prefill_context(
             toks = prefill_metadata.chunked_context.seq_tot[i]
 
             seq_len2 = prefill_metadata.chunked_context.chunk_seq_lens[i]
+            seq_len2_npu = prefill_metadata.chunked_context.chunk_seq_lens_npu[
+                i]
             seq_len = torch.stack([seq_len1, seq_len2])
             kv_c_normed = torch.empty(toks,
                                       num_heads,
@@ -790,7 +794,7 @@ def _compute_prefill_context(
                 cache_kv_c,
                 cache_k_pe,
                 prefill_metadata.block_table,
-                seq_len2.to(q_nope.device),
+                seq_len2_npu,
                 seq_starts=prefill_metadata.chunked_context.starts[i],
                 key=kv_c_normed,
                 value=k_pe,