diff --git a/atom/model_ops/attention_mla.py b/atom/model_ops/attention_mla.py
index ee98185f4..f320fad1a 100644
--- a/atom/model_ops/attention_mla.py
+++ b/atom/model_ops/attention_mla.py
@@ -1288,7 +1288,6 @@ def forward(
 
 @triton.jit
 def _convert_req_index_to_global_index_kernel(
-    qo_indptr,  # int32 [num_requests]
     kv_indptr,  # int32 [num_requests+1]
     page_kv_indptr,  # int32 [num_requests+1]
     kv_indices,  # int32 [num_requests * max_num_blocks_per_req]
@@ -1315,33 +1314,33 @@ def _convert_req_index_to_global_index_kernel(
     kv_end = tl.load(kv_indptr + batch_id + 1)
     out_kv_start = tl.load(page_kv_indptr + batch_id)
     kv_len = kv_end - kv_start
-    qo_start = tl.load(qo_indptr + batch_id)
-    qo_end = tl.load(qo_indptr + batch_id + 1)
-
-    for token_id in range(qo_start, qo_end):
-        # Load token indices for this tile
-        ti_ptr = token_indices_ptr + token_id * ti_stride0 + indice_id * ti_stride1
-        tok = tl.load(ti_ptr)  # int32
-
-        # Guard block_table access
-        valid_mask = (indice_id < kv_len) & (indice_id < NUM_TOPK_TOKENS)
-        out_val = tl.load(
-            kv_indices + kv_start + tok,
-            mask=valid_mask,
-            other=0,
-        )
 
-        # Store results
-        out_ptr_ij = out_kv_indices + out_kv_start + indice_id
-        tl.store(
-            out_ptr_ij,
-            out_val,
-            mask=valid_mask,
-        )
+    # Decode-only: token_id == batch_id. Don't read qo_indptr (cu_seqlens_q),
+    # which can be stale/cumulative under CUDA-graph replay.
+    token_id = batch_id
+
+    # Load token indices for this tile
+    ti_ptr = token_indices_ptr + token_id * ti_stride0 + indice_id * ti_stride1
+    tok = tl.load(ti_ptr)  # int32
+
+    # Guard block_table access
+    valid_mask = (indice_id < kv_len) & (indice_id < NUM_TOPK_TOKENS)
+    out_val = tl.load(
+        kv_indices + kv_start + tok,
+        mask=valid_mask,
+        other=0,
+    )
+
+    # Store results
+    out_ptr_ij = out_kv_indices + out_kv_start + indice_id
+    tl.store(
+        out_ptr_ij,
+        out_val,
+        mask=valid_mask,
+    )
 
 
 def triton_convert_req_index_to_global_index(
-    qo_indptr: torch.Tensor,  # int32 [num_tokens + 1]
     kv_indptr: torch.Tensor,  # int32 [num_tokens + 1]
     page_kv_indptr: torch.Tensor,  # int32 [num_tokens + 1]
     kv_indices: torch.Tensor,  # int32 [total_kv_seqlen]
@@ -1373,7 +1372,6 @@ def triton_convert_req_index_to_global_index(
     tiles_per_row = NUM_TOPK_TOKENS // BLOCK_N
 
     # Ensure contiguous tensors on the same device
-    qo_indptr_c = qo_indptr.contiguous()
     kv_indptr_c = kv_indptr.contiguous()
     kv_indices_c = kv_indices.contiguous()
     token_indices_c = token_indices.contiguous()
@@ -1391,7 +1389,6 @@ def triton_convert_req_index_to_global_index(
     grid = (num_batch, tiles_per_row)
 
     _convert_req_index_to_global_index_kernel[grid](
-        qo_indptr_c,
         kv_indptr_c,
         page_kv_indptr_c,
         kv_indices_c,
diff --git a/atom/models/deepseek_v2.py b/atom/models/deepseek_v2.py
index ff47a5fcc..ef5fef1c6 100644
--- a/atom/models/deepseek_v2.py
+++ b/atom/models/deepseek_v2.py
@@ -1301,7 +1301,6 @@ def sparse_attn_indexer(
             )
         else:
             triton_convert_req_index_to_global_index(
-                attn_metadata.cu_seqlens_q,
                 attn_metadata.kv_indptr,
                 attn_metadata.sparse_kv_indptr,
                 attn_metadata.kv_indices,