diff --git a/vllm/model_executor/models/deepseek_v2.py b/vllm/model_executor/models/deepseek_v2.py
index db0ccd695..13bb3cbd0 100644
--- a/vllm/model_executor/models/deepseek_v2.py
+++ b/vllm/model_executor/models/deepseek_v2.py
@@ -717,13 +717,20 @@ def sparse_attn_indexer(
             # decode_threshold since we unstrictly split
             # prefill and decode by decode_threshold
             # (currently set to 1 + speculative tokens)
+
+            # [num_decode_tokens, n_head, head_dim] -> [bs, 1+next_n, n_head, head_dim]
             padded_q_fp8_decode_tokens = pack_seq_triton(
                 q_fp8[:num_decode_tokens], decode_lens
             )
+            # [num_decode_tokens, n_head] -> [bs, 1+next_n, n_head]
+            padded_weights = pack_seq_triton(weights[:num_decode_tokens], decode_lens)
+            # [bs, 1+next_n, n_head] -> [bs * next_n, n_head]
+            padded_weights = padded_weights.flatten(0, 1)
         else:
             padded_q_fp8_decode_tokens = q_fp8[:num_decode_tokens].reshape(
                 decode_lens.shape[0], -1, *q_fp8.shape[1:]
             )
+            padded_weights = weights
         # TODO: move and optimize below logic with triton kernels
         batch_size = padded_q_fp8_decode_tokens.shape[0]
         next_n = padded_q_fp8_decode_tokens.shape[1]
@@ -739,14 +746,14 @@ def sparse_attn_indexer(
         logits = fp8_paged_mqa_logits_func(
             padded_q_fp8_decode_tokens,
             kv_cache,
-            weights[:num_padded_tokens],
+            padded_weights[:num_padded_tokens],
             decode_metadata.seq_lens,
             decode_metadata.block_table,
             decode_metadata.schedule_metadata,
             max_model_len=max_model_len,
         )
         num_rows = logits.shape[0]
-        topk_indices = topk_indices_buffer[:num_decode_tokens, :topk_tokens]
+        topk_indices = topk_indices_buffer[:num_padded_tokens, :topk_tokens]
 
         torch.ops._C.top_k_per_row_decode(
             logits,