Qwen3next flashinfer allreduce auto enable

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Summary

Enable FlashInfer allreduce fusion by default for Qwen3NextForCausalLM on supported single-node SM90/SM100 TP runs.

Why

Qwen/Qwen3-Coder-Next was running with enable_flashinfer_allreduce_fusion=false on H100, and profiler traces showed prefill time dominated by unfused cross-device reduce kernels.

Change

• add Qwen3NextForCausalLM to the existing FlashInfer allreduce auto-enable whitelist

H100 Evidence

Model: Qwen/Qwen3-Coder-Next

Command:

python -m sglang.launch_server --model-path Qwen/Qwen3-Coder-Next --tp 4 --port 31080

Server args:

• baseline: enable_flashinfer_allreduce_fusion=false
• patch: enable_flashinfer_allreduce_fusion=true

Benchmark (sglang.bench_serving, random 2048/256, 128 prompts, max_concurrency=32):

Metric	Baseline	Patch	Delta
Request throughput (req/s)	5.49	9.41	+71.4%
Mean TTFT (ms)	456.24	167.54	-63.3%
Mean TPOT (ms)	50.41	25.49	-49.4%

Full accuracy:

Eval	Baseline	Patch	Delta
MMLU (14042)	0.8745905	0.8714571	-0.31 pp
GSM8K (1314)	0.9627093	0.9687976	+0.61 pp

Profiler (TP-0 EXTEND):

• baseline: cross_device_reduce_2stage 136.171 ms (21.89%)
• patch: allreduce_fusion_kernel_oneshot_lamport 57.661 ms (10.41%)

This change activates the fused allreduce path and removes the previous dominant unfused reduce hotspot.

Validation

• H100 before/after throughput benchmark
• H100 before/after sglang.profiler
• H100 before/after full MMLU and full GSM8K server eval

Modifications

Accuracy Tests

Speed Tests and Profiling

Checklist

• Format your code according to the Format code with pre-commit.
• Add unit tests according to the Run and add unit tests.
• Update documentation according to Write documentations.
• Provide accuracy and speed benchmark results according to Test the accuracy and Benchmark the speed.
• Follow the SGLang code style guidance.

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