[DOC] Add fuse_minimax_qk_norm (#39782)

Signed-off-by: Jee Jee Li <pandaleefree@gmail.com>

docs/design/fusions.md

@@ -21,6 +21,7 @@ or just on the low or high end.
 | Fusion                                                                         | `PassConfig` flag            | Fused operations                               | Default at                     | E2E Speedup        | Fullgraph | `num_tokens` |
 | ------------------------------------------------------------------------------ | ---------------------------- | ---------------------------------------------- | ------------------------------ | ------------------ | --------- | ------------ |
 | [AllReduce + RMSNorm](#allreduce--rmsnorm-fuse_allreduce_rms)                  | `fuse_allreduce_rms`         | All-reduce → RMSNorm (+residual_add) (→ quant) | O2 (Hopper/Blackwell + TP > 1) | 5-20%              | No        | Low          |
+| [MiniMax QK Norm](#minimax-qk-norm-fuse_minimax_qk_norm)                       | `fuse_minimax_qk_norm`       | Q/K variance all-reduce → Q/K RMSNorm          | Off by default                 | 2-3%               | No        | Low          |
 | [Attention + Quant](#attention--quantization-fuse_attn_quant)                  | `fuse_attn_quant`            | Attention output → FP8/NVFP4 quant             | Off by default                 | 3-7%               | Yes       | Always       |
 | [MLA Attention + Quant](#attention--quantization-fuse_attn_quant)              | `fuse_attn_quant`            | MLA Attention output → FP8/NVFP4 quant         | Off by default                 | TBD                | Yes       | Always       |
 | [RoPE + KV-Cache Update](#rope--kv-cache-update-fuse_rope_kvcache)             | `fuse_rope_kvcache`          | Rotary embedding → KV cache write              | O2 (ROCm/AITER only)           | 2-4%               | No        | Low          |
@@ -40,6 +41,7 @@ The table below lists the quantization schemes supported by each fusion on each
 | Fusion                       | SM100 (Blackwell)                        | SM90 (Hopper)                            | SM89 (Ada)                               | SM80 (Ampere) | ROCm                                     |
 | ---------------------------- | ---------------------------------------- | ---------------------------------------- | ---------------------------------------- | ------------- | ---------------------------------------- |
 | `fuse_allreduce_rms`         | FP16/BF16, FP8 static, NVFP4             | FP16/BF16, FP8 static                    | —                                        | —             | —                                        |
+| `fuse_minimax_qk_norm`\*     | FP16/BF16                                | FP16/BF16                                | FP16/BF16                                | FP16/BF16     | —                                        |
 | `fuse_attn_quant`\*          | FP8 static\*, NVFP4\*                    | FP8 static\*                             | FP8 static\*                             | —             | FP8 static\*                             |
 | `fuse_attn_quant` (MLA)\*    | FP8 static\*, NVFP4\*                    | FP8 static\*                             | FP8 static\*                             | —             | FP8 static(untested)\*                   |
 | `fuse_rope_kvcache`          | —                                        | —                                        | —                                        | —             | FP16/BF16                                |
@@ -54,6 +56,9 @@ The table below lists the quantization schemes supported by each fusion on each
 fused quantization output. See the [`fuse_attn_quant` section](#attention--quantization-fuse_attn_quant)
 for per-backend details.
 
+\* `fuse_minimax_qk_norm` is a model-specific pass for `MiniMaxM2ForCausalLM`. It also requires
+tensor parallelism (`tp_size > 1`) and the CUDA custom op `minimax_allreduce_rms_qk`.
+
 † `enable_sp` and `fuse_gemm_comms` are only autoconfigured for SM90 today;
 other architectures support requires setting `PassConfig.sp_min_token_num` explicitly.
 SM100 support also requires setting `VLLM_DISABLED_KERNELS=FlashInferFP8ScaledMMLinearKernel`.
@@ -184,6 +189,35 @@ If these conditions are set, the fusion is enabled automatically for optimizatio
 
 - Pass: [`vllm/compilation/passes/fusion/rope_kvcache_fusion.py`](https://github.com/vllm-project/vllm/blob/main/vllm/compilation/passes/fusion/rope_kvcache_fusion.py)
 
+### MiniMax QK Norm (`fuse_minimax_qk_norm`)
+
+!!! info
+    This is a MiniMax-specific compile pass. It is currently only enabled when all of the following hold:
+    the model architecture is `MiniMaxM2ForCausalLM`, tensor parallelism is enabled (`tp_size > 1`),
+    and the CUDA custom op `minimax_allreduce_rms_qk` is available. It is not enabled by default at any
+    optimization level.
+
+**What it fuses.** Fuses the MiniMax M2 Q/K normalization path that performs an all-reduce over the
+per-token Q/K variances before applying RMS normalization to Q and K.
+
+This pass is distinct from [`enable_qk_norm_rope_fusion`](#qk-norm--rope-enable_qk_norm_rope_fusion):
+`fuse_minimax_qk_norm` targets MiniMax M2's tensor-parallel all-reduce + RMSNorm sequence, while
+`enable_qk_norm_rope_fusion` targets the later Q/K RMSNorm + RoPE sequence used by several other models.
+
+Example:
+
+```bash
+vllm serve MiniMaxAI/MiniMax-M2.5 \
+  --tensor-parallel-size 4 \
+  --compilation-config '{"mode": 3, "pass_config": {"fuse_minimax_qk_norm": true}}'
+```
+
+**Code locations.**
+
+- Pass: [`vllm/compilation/passes/fusion/minimax_qk_norm_fusion.py`](https://github.com/vllm-project/vllm/blob/main/vllm/compilation/passes/fusion/minimax_qk_norm_fusion.py)
+- CUDA op: [`csrc/minimax_reduce_rms_kernel.cu`](https://github.com/vllm-project/vllm/blob/main/csrc/minimax_reduce_rms_kernel.cu) (`minimax_allreduce_rms_qk`)
+- Workspace helper: [`vllm/model_executor/layers/mamba/lamport_workspace.py`](https://github.com/vllm-project/vllm/blob/main/vllm/model_executor/layers/mamba/lamport_workspace.py)
+
 ### Sequence Parallelism (`enable_sp`)
 
 **What it fuses.** Replaces all-reduce collectives with reduce-scatter + local RMSNorm + all-gather,