[Feature][MiniMax-H3] Support diffusion continuous batching (#5810)

Signed-off-by: princepride <wangzhipeng628@gmail.com>
Signed-off-by: lishunyang12 <lishunyang12@163.com>
Co-authored-by: Claude Opus 5 <noreply@anthropic.com>
Co-authored-by: lishunyang12 <lishunyang12@163.com>
Co-authored-by: Cursor <cursoragent@cursor.com>

docs/user_guide/diffusion/execution_modes.md

@@ -101,8 +101,16 @@ set `DIFFUSION_ATTENTION_BACKEND=TORCH_SDPA` or configure
 `--max-num-seqs >1`. See the
 [HunyuanImage-3.0 recipe](https://github.com/vllm-project/vllm-omni/blob/main/recipes/Tencent/HunyuanImage-3.0-Instruct.md)
 for its validated configuration. Helios supports single-request step execution only: use
-`--step-execution --max-num-seqs 1` for Helios. Consult the selected pipeline's
-documentation and source for the latest support status.
+`--step-execution --max-num-seqs 1` for Helios. MiniMax H3 supports step-wise
+continuous batching by packing co-batched requests into one sequence that keeps
+a separate attention document per request; that layout needs a backend which
+honors the packed `cu_seqlens` metadata, so run it with
+`--diffusion-attention-backend FLASH_ATTN` (other backends stay correct but
+fall back to one transformer forward per request). Batching H3 does not improve
+its throughput — see the measured numbers in the
+[MiniMax-H3 recipe](https://github.com/vllm-project/vllm-omni/blob/main/recipes/MiniMaxAI/MiniMax-H3.md)
+— so keep `--max-num-seqs 1` unless you need step-level scheduling. Consult the
+selected pipeline's documentation and source for the latest support status.
 
 ## Streaming Output