[MoE] Add VLLM_FP8_MOE_BACKEND to override FP8-expert routing indepently of --moe-backend

[ECMGit]

Purpose

--moe-backend is consumed by both the NVFP4 dispatcher (oracle/nvfp4.py:map_nvfp4_backend) and the FP8 dispatcher (oracle/fp8.py:map_fp8_backend). For FP4-only kernels — e.g. flashinfer_b12x, registered in the NVFP4 oracle by PR #40082 — the FP8 dispatcher has no corresponding backend, so on any mixed-precision checkpoint (NVFP4 experts + FP8 experts in the same model) map_fp8_backend raises at engine init:

ValueError: moe_backend='flashinfer_b12x' is not supported for FP8 MoE.
  Expected one of ['triton', 'deep_gemm', 'cutlass', 'flashinfer_trtllm',
                   'flashinfer_cutlass', 'marlin', 'aiter'].

This blocks every mixed-precision checkpoint that pairs NVFP4 expert layers with FP8 ones — e.g. nvidia/Qwen3.6-35B-A3B-2.06GB-per-token on DGX Spark (GB10 / sm_121a). Such checkpoints are the norm for the 2.06GB-per-token family.

Change:

Introduce VLLM_FP8_MOE_BACKEND so callers can route FP8 experts to a different backend while keeping --moe-backend=flashinfer_b12x for the NVFP4 majority.

• vllm/envs.py: declare VLLM_FP8_MOE_BACKEND (literal of valid FP8 backend strings, default None).
• vllm/model_executor/layers/fused_moe/oracle/fp8.py: map_fp8_backend reads envs.VLLM_FP8_MOE_BACKEND as an override before consulting runner_backend; error message identifies the source.

Unset behavior is unchanged — only callers that explicitly set the env var see the new dispatch.

Alternatives considered:

1. Extend b12x to handle FP8 experts — not feasible; b12x is FP4-only by construction (class docstring: "Only NVFP4 (kNvfp4Static/kNvfp4Dynamic) quantization is supported").
2. Auto-fall-back inside map_fp8_backend — opaque to callers and surprising; an explicit env-var opt-in is safer until the FP4/FP8 split is formalized in --moe-backend.
3. Per-layer-class backend selection in the model card — larger refactor; this env var is the minimal unblocker.

Risk: Low. Adds one env var (default unset → unchanged behavior). map_fp8_backend only branches when the env var is set; the existing error path is preserved for misconfigured values.

Test Plan

Hardware: DGX Spark (GB10, sm_121a)
Container: vllm/vllm-openai:nightly-aarch64 + this PR + the b12x-W4A16-supports companion PR
Model: nvidia/Qwen3.6-35B-A3B-2.06GB-per-token (modelopt-native, mixed NVFP4 + FP8 experts)
Tooling: FlashInfer 0.6.11.post3, cutlass-dsl trio 4.5.1

Recipe:

export VLLM_NVFP4_GEMM_BACKEND=flashinfer-b12x
export VLLM_USE_FLASHINFER_MOE_FP4=1
export VLLM_FP8_MOE_BACKEND=flashinfer_cutlass    # THIS PR — routes FP8 experts via FI-cutlass
export FLASHINFER_DISABLE_VERSION_CHECK=1
export CUTE_DSL_ARCH=sm_121a

vllm serve nvidia/Qwen3.6-35B-A3B-2.06GB-per-token \
    --tensor-parallel-size 1 --trust-remote-code --dtype auto \
    --kv-cache-dtype fp8 --attention-backend FLASHINFER \
    --gpu-memory-utilization 0.85 --max-model-len 40960 \
    --max-num-seqs 4 --max-num-batched-tokens 8192 \
    --enable-chunked-prefill --async-scheduling --enable-prefix-caching \
    --moe-backend=flashinfer_b12x --quantization=modelopt \
    --compilation-config '{"pass_config":{"fuse_norm_quant":true,"fuse_act_quant":true,"fuse_attn_quant":false}}' \
    --speculative-config '{"method":"mtp","num_speculative_tokens":3,"rejection_sample_method":"synthetic","synthetic_acceptance_length":3.12,"moe_backend":"triton"}'

Benchmark (aiperf): K=3 AL=3.12, BS=1 / concurrency=1, ISL=2048 + 32K user-context (total ISL=34,831), OSL=1024, 10 warmup + 60 measured requests, --use-server-token-count --streaming.

Negative test (without VLLM_FP8_MOE_BACKEND set): verify the error path still triggers and the message correctly identifies the source.

Test Result

Without this PR (current behavior on mixed-precision checkpoint):

ValueError: moe_backend='flashinfer_b12x' is not supported for FP8 MoE.
  Expected one of ['triton', 'deep_gemm', 'cutlass', 'flashinfer_trtllm',
                   'flashinfer_cutlass', 'marlin', 'aiter'].

Serve dies at engine init; no throughput measurement possible.

With this PR + VLLM_FP8_MOE_BACKEND=flashinfer_cutlass:

Metric	Value
Output Token Throughput	91.00 tok/s
Output Token Throughput / user	97.42 tok/s/user
TTFT	746.81 ms
ITL	10.27 ms
Request Latency	11,249.37 ms
MTP acceptance length	3.15 (target 3.12) ✓
Requests / errors	60 / 0

With this PR + env var unset (regression sanity): same error as "Without this PR" above is raised, now annotated with (from --moe-backend) to disambiguate the source.

---

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[gemini-code-assist]

Code Review

This pull request introduces the VLLM_FP8_MOE_BACKEND environment variable, allowing users to override the FP8 MoE backend independently of the primary --moe-backend flag. This change addresses scenarios where a specific backend (like flashinfer_b12x for NVFP4) lacks an FP8 equivalent, preventing potential runtime errors in mixed-precision configurations. The map_fp8_backend function has been updated to prioritize this new environment variable and includes improved error reporting to clarify the source of the backend configuration. I have no feedback to provide as there were no review comments to evaluate.

[ECMGit]

add @meena-at-work as reviewer

[xinli-sw]

does #43148 solve your issue?

[xinli-sw]

if not can you rebase the fix onto that approach?

[ECMGit]

if not can you rebase the fix onto that approach?

I've done the rebase, please check it out.

[mgoin]

@ECMGit @xinli-sw could we solve this by introducing granularity to --moe-backend instead of adding new environment variables? For instance --fp8-moe-backend would be fine with me. Or expanding --moe-backend into a config so you could do --moe-backend.fp8

I'm curious why you need to specify --moe-backend in this case at all though, since I assume the b12x backend will be chosen by default as the most performance one on spark. If not, we should fix the heuristics rather than rely on user's to specify the right (increasingly complex) args

[ECMGit]

@ECMGit @xinli-sw could we solve this by introducing granularity to --moe-backend instead of adding new environment variables? For instance --fp8-moe-backend would be fine with me. Or expanding --moe-backend into a config so you could do --moe-backend.fp8

I'm curious why you need to specify --moe-backend in this case at all though, since I assume the b12x backend will be chosen by default as the most performance one on spark. If not, we should fix the heuristics rather than rely on user's to specify the right (increasingly complex) args

Hi @mgoin thanks for reviewing it.

let me explain the intention for this fix: this is for mixed-precision checkpoints like interleave NVFP4 and FP8 experts in the same model. if b12x as default --moe-backend is consumed by both the NVFP4 and FP8 dispatchers, so picking flashinfer_b12x for the FP4 majority crashes map_fp8_backend and b12x is FP4-only by construction. A per-dtype override could be the minimal fix.

I can switch to --fp8-moe-backend as a optional arg if that is more surgical.

[mgoin]

@ECMGit I think you missed my second point - why do you need to set --moe-backend at all? If you don't explicitly set that argument, vLLM can already select different backends through the default dispatch within each oracle. The best case we aim for is to select the best kernel by default, so I think you should make it so b12x is selected by default on your system for your case if it is the best

[ECMGit]

Hi @mgoin , I think you are right. I've ran and re-test it on my end:
aiperf headline on nightly + only PR #43332 applied (no VLLM_FP8_MOE_BACKEND, no --moe-backend):
verified:

• FP4 oracle auto-picks FLASHINFER_B12X; FP8 Linear auto-binds FlashInferFP8ScaledMMLinearKernel.
• 60/60 requests, OTT 93.99 tok/s (within 3% of the 2026-05-21 baseline of 91.00), TTFT 767ms, MTP acceptance length 3.10–3.13.

PR #43334 is not needed for the Qwen3.6-35B mixed-precision checkpoint.
however PR #43332 is needed for running this checkpoint
I am Happy to close #43334 or rescope to just port to use auto dispatch even when moe_backend is explictly assigned