diff --git a/vllm/model_executor/layers/sparse_attn_indexer.py b/vllm/model_executor/layers/sparse_attn_indexer.py
index 7dde4db00f..ae45b77dce 100644
--- a/vllm/model_executor/layers/sparse_attn_indexer.py
+++ b/vllm/model_executor/layers/sparse_attn_indexer.py
@@ -642,6 +642,19 @@ def sparse_attn_indexer(
         assert decode_metadata is not None
         kv_cache = kv_cache_as_quant_view(kv_cache, head_dim, use_fp4_cache)
         decode_lens = decode_metadata.decode_lens
+        # requires_padding can be computed False for ragged warmup/mixed
+        # batches (seen on SM120 TP=2: 8 tokens over 6 seqs -> uniform
+        # reshape below would crash). The token-count/batch-size divisibility
+        # check is a necessary-but-not-sufficient proxy for "uniform batch"
+        # (e.g. decode_lens=[1, 2, 3] divides evenly by 3 but isn't uniform);
+        # it catches the specific case seen in practice without requiring a
+        # device sync to inspect decode_lens directly, which would break
+        # CUDA-graph-capture safety on this path. Shared by both the pack
+        # branch below and the matching unpack branch further down — they
+        # must agree on which path was taken.
+        needs_padded_path = decode_metadata.requires_padding or (
+            num_decode_tokens % decode_lens.shape[0] != 0
+        )
         if num_decode_tokens == 0:
             padded_q_quant_decode_tokens = q_quant[:1].reshape(1, 1, *q_quant.shape[1:])
             padded_q_scale = (
@@ -649,7 +662,7 @@ def sparse_attn_indexer(
                 if q_scale is not None
                 else None
             )
-        elif decode_metadata.requires_padding:
+        elif needs_padded_path:
             # pad in edge case where we have short chunked prefill length <
             # decode_threshold since we unstrictly split
             # prefill and decode by decode_threshold
@@ -773,7 +786,7 @@ def sparse_attn_indexer(
                 cp_kv_cache_interleave_size,
             )
 
-        if decode_metadata.requires_padding:
+        if needs_padded_path:
             # if padded, we need to unpack
             # the topk indices removing padded tokens
             topk_indices = unpack_seq_triton(