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Enable Rust frontend (VLLM_USE_RUST_FRONTEND=1) #1634

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Merged
functionstackx merged 4 commits into from
Jun 8, 2026
+9 −0
Merged

Enable Rust frontend (VLLM_USE_RUST_FRONTEND=1) #1634

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a79476d
Enable Rust frontend (VLLM_USE_RUST_FRONTEND=1)
chunfangamd Jun 1, 2026
7d601a0
Update per-changelog
chunfangamd Jun 1, 2026
aa63214
Merge branch 'main' into chun/minimax-rust-frontend
chunfangamd Jun 2, 2026
72d58da
Merge branch 'main' into chun/minimax-rust-frontend
functionstackx Jun 8, 2026
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1 change: 1 addition & 0 deletions benchmarks/single_node/fixed_seq_len/minimaxm2.5_fp4_mi355x.sh
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Original file line number Diff line number Diff line change
Expand Up @@ -25,6 +25,7 @@ if [ -n "$ROCR_VISIBLE_DEVICES" ]; then
fi

export VLLM_ROCM_USE_AITER=1
export VLLM_USE_RUST_FRONTEND=1
EXTRA_VLLM_ARGS=""
# if [ "$TP" -ge 4 ]; then
# # AITER CK fused MoE kernels lack compiled tiles for N=intermediate_size/TP
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8 changes: 8 additions & 0 deletions perf-changelog.yaml
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Expand Up @@ -3523,3 +3523,11 @@
- "Aligned decode params with Weiliang config: swa-full-tokens-ratio=0.20, max-running-requests=18432, moe-dense-tp-size=1; added prefill enable-dp-lm-head and cuda-graph-max-bs=512"
- "Remove 4 dominated old configs (4p-dep16-8n, 8p-dep16-12n, 10p-dep16-14n, 12p-dep12-15n) superseded by wide-EP frontier"
pr-link: https://github.com/SemiAnalysisAI/InferenceX/pull/1586

- config-keys:
- minimaxm2.5-fp4-mi355x-vllm
description:
- "Enable vLLM Rust request frontend by exporting VLLM_USE_RUST_FRONTEND=1 in benchmarks/single_node/minimaxm2.5_fp4_mi355x.sh (v0.22.0 ROCm image ships the vllm-rs binary, so the flag engages it). Environment-only change; serve flags, TP/EP, attention/kernel settings unchanged"
- "The Rust frontend replaces only the Python serving/API layer (HTTP, tokenization, scheduling glue, detokenization) and spawns the same Python EngineCore, so GPU kernels/attention/MoE GEMM/KV cache are untouched"
- "A/B sweep (28 single-node points, 1k1k + 8k1k, TP 1/2/4) vs the Python-frontend baseline (run 26696260751): throughput Pareto-neutral (peak tok/s/GPU within <1.5%, frontiers coincident) and TPOT flat (+-0.5%); TTFT improves ~8% at 1k1k and ~22% at 8k1k (every point), the expected signature of lower frontend CPU latency before first token, scaling with input length"
pr-link: https://github.com/SemiAnalysisAI/InferenceX/pull/1634
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