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feat: add Qwen3.5 FP8 GB200 Dynamo-SGLang MTP recipes / 新增 Qwen3.5 FP8 GB200 Dynamo-SGLang MTP 配方#2324

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feat: add Qwen3.5 FP8 GB200 Dynamo-SGLang MTP recipes / 新增 Qwen3.5 FP8 GB200 Dynamo-SGLang MTP 配方#2324
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qwen3.5-fp8-gb200-dynamo-sglang-mtp

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Summary

  • add a Qwen3.5-397B-A17B-FP8 GB200 disaggregated Dynamo-SGLang MTP configuration for 8k/1k
  • add seven SGLang recipes for TP4, TEP8, and DEP4/DEP16 prefill/decode topologies with EAGLE speculative decoding and Mooncake KV transfer
  • enable chat-formatted MTP inputs and validate digest-pinned Enroot imports before publishing shared squash files

中文说明

  • 新增面向 8k/1k 的 Qwen3.5-397B-A17B-FP8 GB200 分离式 Dynamo-SGLang MTP 配置
  • 添加七个 SGLang 配方,覆盖 TP4、TEP8 和 DEP4/DEP16 预填充/解码拓扑,并使用 EAGLE 投机解码与 Mooncake KV 传输
  • 为 MTP 输入启用聊天格式,并在发布共享 Squash 文件前校验摘要固定的 Enroot 镜像导入

Add the GB200 disaggregated configuration, seven SGLang recipes, chat-formatted MTP inputs, and digest-aware Enroot import validation.

中文:新增 Qwen3.5 FP8 GB200 Dynamo-SGLang MTP 配置

添加 GB200 分离式配置、七个 SGLang 配方、MTP 聊天格式输入,以及支持摘要固定镜像的 Enroot 导入校验。
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Thanks for the contribution! Please reach out to respective companies' CODEOWNER to fill in the latest PR_REVIEW_CHECKLIST.md before pinging core maintainer on Slack for review. In order for the signoff PR check bot to trigger, you must follow the PR_REVIEW_CHECKLIST.md template correctly, including the phrase As a PR reviewer and CODEOWNER, I have reviewed this and have.

For PR verification, add the full-sweep-fail-fast label (strongly recommended) to this PR — the benchmark sweep only runs on labeled PRs. Use full-sweep-enabled only if you need matrix jobs to keep running past a failure.

PR authors are responsible for ensuring that after merging, all GitHub Action jobs fully pass. A lot of the time, failures are just flakes and simply re-running the failed jobs will fix it. See GitHub's docs on re-running failed jobs


感谢你的贡献!请联系相应公司的 CODEOWNER 填写最新的 PR_REVIEW_CHECKLIST.md,然后再在 Slack 上联系核心维护者进行审阅。为了触发 signoff PR 检查机器人,你必须正确遵循 PR_REVIEW_CHECKLIST.md 模板,包括保留英文语句 As a PR reviewer and CODEOWNER, I have reviewed this and have

如需进行 PR 验证,请为此 PR 添加 full-sweep-fail-fast 标签(强烈推荐)— 基准测试 sweep 仅在带有标签的 PR 上运行。仅当需要矩阵任务在失败后继续运行时才使用 full-sweep-enabled

PR 作者有责任确保合并后所有 GitHub Action 任务完全通过。 很多时候失败只是偶发抖动(flake),重新运行失败的任务即可解决。参见 GitHub 关于重新运行失败任务的文档

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Thanks for the contribution! Please reach out to respective companies' CODEOWNER to fill in the latest PR_REVIEW_CHECKLIST.md before pinging core maintainer on Slack for review. In order for the signoff PR check bot to trigger, you must follow the PR_REVIEW_CHECKLIST.md template correctly, including the phrase As a PR reviewer and CODEOWNER, I have reviewed this and have.

For PR verification, add the full-sweep-fail-fast label (strongly recommended) to this PR — the benchmark sweep only runs on labeled PRs. Use full-sweep-enabled only if you need matrix jobs to keep running past a failure.

PR authors are responsible for ensuring that after merging, all GitHub Action jobs fully pass. A lot of the time, failures are just flakes and simply re-running the failed jobs will fix it. See GitHub's docs on re-running failed jobs


感谢你的贡献!请联系相应公司的 CODEOWNER 填写最新的 PR_REVIEW_CHECKLIST.md,然后再在 Slack 上联系核心维护者进行审阅。为了触发 signoff PR 检查机器人,你必须正确遵循 PR_REVIEW_CHECKLIST.md 模板,包括保留英文语句 As a PR reviewer and CODEOWNER, I have reviewed this and have

如需进行 PR 验证,请为此 PR 添加 full-sweep-fail-fast 标签(强烈推荐)— 基准测试 sweep 仅在带有标签的 PR 上运行。仅当需要矩阵任务在失败后继续运行时才使用 full-sweep-enabled

PR 作者有责任确保合并后所有 GitHub Action 任务完全通过。 很多时候失败只是偶发抖动(flake),重新运行失败的任务即可解决。参见 GitHub 关于重新运行失败任务的文档

Record the PR link for the Qwen3.5 GB200 MTP configuration.

中文:更新 #2324 的 perf-changelog 链接

记录 Qwen3.5 GB200 MTP 配置对应的 PR 链接。

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Deferring to human review — no bugs found, but this PR's launcher-script change is broader than a config addition and is worth a maintainer's eyes.

Extended reasoning...

Overview

This PR adds seven new Qwen3.5-FP8 GB200 disaggregated Dynamo-SGLang MTP benchmark recipes (config-only YAML), a corresponding nvidia-master.yaml scenario block, a perf-changelog.yaml entry, and — the part that raises the scope beyond a typical recipe PR — a rewrite of the enroot image-import logic in runners/launch_gb200-nv.sh: a new enroot_uri_for_image() helper that builds enroot URIs for digest-pinned vs. tag-only images across registries, plus a validation/atomic-replace pass (unsquashfs -l check before mv -f) in import_squash().

Security risks

No injection, auth, or data-exposure concerns — the script only builds enroot import URIs from config-controlled image strings and moves local files under a lock. No user-supplied/external input reaches this logic.

Level of scrutiny

The bug hunting system reviewed the new enroot_uri_for_image digest-splitting logic twice (double-colon-after-#, wrong split point) and found no real bug. However, import_squash is called unconditionally on every GB200 launch (import_squash "$SQUASH_FILE" "$IMAGE" / import_squash "$NGINX_SQUASH_FILE" "$NGINX_IMAGE"), so this change affects every existing GB200 recipe (dsr1, dsv4, glm5.x, kimik2.5, minimax, etc.) — not just the new Qwen3.5 recipes. A logic change to a shared, unconditionally-executed launcher path is the kind of critical-path change that benefits from a maintainer's sign-off even when no bug was found, since a subtle regression here would silently affect unrelated model sweeps.

Other factors

The seven new recipe YAMLs and master-config/changelog additions are mechanical and low-risk (new, additive, model-scoped). It's specifically the shared shell-script rewrite that pushes this past the bar for a shadow-approval.

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@Ankur-singh

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/reuse-sweep-run 30055331227

@Ankur-singh

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As a PR reviewer and CODEOWNER, I have reviewed this and have:

  • Verified that as of the moment of typing this, this is the latest version of PR_REVIEW_CHECKLIST.md
  • Verified that the general code quality meets the InferenceX standard and does not make the code quality any worse.
  • Verified that this PR has passed PR validation. Please link to GitHub Action workflow that shows this. — https://github.com/SemiAnalysisAI/InferenceX/actions/runs/30055331227
  • Verified that this PR passes evals. Please link to GitHub Action workflow that shows this. — https://github.com/SemiAnalysisAI/InferenceX/actions/runs/30055331227
  • Verified that speculative decoding PRs uses chat templates to align the AL distribution to real world
  • For agentic workloads: verified that speculative-decoding configs (EAGLE / MTP / draft models) run with simulated synthetic acceptance, with the acceptance-length value taken from the committed golden AL curve in golden_al_distribution/ for that model, thinking mode, and draft length. A submission may choose any supported draft length, but it may not substitute a different acceptance target.
  • Verified that the model architecture isn't changed with benchmark hacks like using --hf-overrides to skipping indexer for every x layers on models that don't natively support this. As a general rule, we won't accept optimizations that reduces the number of model architecture FLOPs. Anything that makes that same computation run faster is fair game; FLOPs at lower precisions is fine, given that the config passes private evals. As an general north star princple, we should only use optimizations which is used in production by customers that care about accuracy
  • If an company claims that they support vLLM/SGLang as first class LLM inference engines on their hardware, I have verified that the respective vLLM submission made using upstream https://hub.docker.com/u/vllm docker repo, upstream SGLang https://hub.docker.com/u/lmsysorg docker repo. The only exceptions are for new hardware, such as MI455X UALoE72, Vera Rubin NVL72, Rubin NVL8, etc., and for new model architectures where there is an actual reason why vLLM/SGLang does not fundamentally support them yet as supported by vLLM/SGLang community maintainers
  • If an company claims that they support vLLM/SGLang as first class upstream in-tree LLM inference engines on their hardware, I have have verified that the respective vLLM/SGLang submission has been made before additional frameworks (TRT-LLM, ATOM, etc.). The only exceptions are for new hardware, such as MI455X UALoE72, Vera Rubin NVL72, Rubin NVL8, etc., and for new model architectures where there is an actual reason why vLLM/SGLang does not fundamentally support them yet.
  • Verified that every single-node vLLM/SGLang recipe in this PR is documented in the official vLLM recipes and/or the SGLang cookbook:
    • I linked the corresponding upstream PR in the vLLM recipe repo or SGLang repo and verified that it is MERGED before this InferenceX PR merges. An opened, draft, or closed-without-merge upstream PR does not satisfy this requirement. If the matching recipe was already published, I linked the published recipe/cookbook page in the additional detail section below.
  • Verified that this PR does not patch the inference engine or serving stack — the pinned image must run as shipped. This covers .patch files / git apply / patch, inline patches embedded in benchmark scripts (e.g. a python3/sed heredoc that rewrites installed engine sources before serving), in-place edits of site-packages, monkey-patching, overwriting container files, and installing forked/rebuilt engine wheels on top of the pinned image. The only exception is a patch covered by a filled-out waiver at docs/waiver/<PR_NUMBER>.md — named after the PR that introduces the patch and filed in that same PR, stating what is patched, why the unmodified upstream image cannot run this benchmark, the upstream PR/issue link, and the removal plan — which I have linked below in the additional detail section.
  • If any of the above criteria cannot reasonably be satisfied, I have provided additional reasoning below.

Additional detail section:

  • Scope: new config qwen3.5-fp8-gb200-dynamo-sglang-mtp — Qwen3.5-397B-A17B-FP8, GB200, disaggregated Dynamo-SGLang with EAGLE MTP, 8k1k. Seven recipes covering 1P1D TP4/TP4, 1P1D TEP8/TEP8, and 3P/4P/6P/7P/8P DEP4/DEP16 topologies; Mooncake KV transfer; image lmsysorg/sglang:v0.5.14-cu130@sha256:5027e95… (upstream lmsysorg, digest-pinned).
  • Launcher change: runners/launch_gb200-nv.sh adds qwen3.5 to the staged-model allow-list and introduces enroot_uri_for_image() so Enroot 3.x can import the digest-pinned image (tag@digest isn't parseable by Enroot's default path), plus a post-import unsquashfs -l validation before publishing the shared squash file. This is import/orchestration plumbing — it does not modify the engine or serving stack; it is backward-compatible for non-digest images and was exercised by the green sweep.
  • Validation & evals: Run Sweep https://github.com/SemiAnalysisAI/InferenceX/actions/runs/30055331227 (head 4c714e2d) is green top-level with non-skipped multi-node 8k1k benchmark jobs (all 7 topologies) and multi-node eval jobs (6 topologies) passing; collect-evals/collect-results/compare-results all succeeded.
  • Chat template (spec decode): all seven MTP recipes set use_chat_template: true in the sa-bench benchmark block alongside speculative-algorithm: EAGLE, aligning the acceptance-length distribution to real-world chat usage.
  • Architecture / precision: EAGLE MTP speculative decoding with fp8 quantization / fp8 kv-cache — precision and native spec-decode, not a reduction of model-architecture FLOPs — and the configs pass evals.
  • No engine patching: the recipes are declarative Dynamo/srt-slurm YAML and the pinned image runs as shipped; no patch files, sed/heredoc rewrites, site-packages edits, or forked wheels.
  • Agentic item (unchecked): not applicable — fixed-seq-len (8k1k) multi-node throughput/latency configs, not agentic workloads; agentic jobs correctly skipped.
  • Single-node recipe item (unchecked): not applicable — this PR adds only multi-node DISAGG srt-slurm recipes; the single-node recipe-documentation requirement is out of scope for a disaggregated multi-node submission.

Signed: Ankur-singh

@Klaud-Cold

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✅✅✅ Verdict: PASS ✅✅✅

✅ Check 0 (CODEOWNER): PASS — Ankur-singh is a listed owner of configs/nvidia-master.yaml (the only specifically-owned changed path); all other paths fall under the catch-all.
✅ Check 1 (passing sweep on in-PR commit): PASS — head 4c714e2d carries run 30055331227 with all 7 multi-node 8k1k / and all 6 multi-node eval / jobs executed with conclusion success (single-node lanes correctly skipped for this multi-node-only PR).
✅ Check 2 (evals pass): PASS — aggregated results show 6/6 gsm8k evals at 0.9651–0.9704, all above the committed 0.94 bar for qwen3.5 (n_eff 1319), run on the same digest-pinned lmsysorg/sglang:v0.5.14-cu130@sha256:5027e95… image as this PR's config.
➖ Check 3 (recipe link): N/A — disaggregated/multi-node submission (benchmarks/multi_node/srt-slurm-recipes/**, master entry multinode: true + disagg: true); the recipe-link requirement applies to single-node recipes only.
✅ Check 4 (reuse command): PASS — /reuse-sweep-run 30055331227 posted by Ankur-singh (COLLABORATOR).
✅ Check 5 (latest checklist): PASS — sign-off matches the current template; the two unchecked items (agentic AL, single-node recipe) are explained as not applicable in the additional detail section, and that assessment is correct.
✅ Check 6 (upstream image / engine-first): PASS — image is upstream digest-pinned lmsysorg/sglang:v0.5.14-cu130@sha256:5027e95…; the SGLang-engine entry for this model+SKU (qwen3.5-fp8-gb200-dynamo-sglang) already exists on main, and no non-SGLang/vLLM framework precedes it on gb200 for qwen3.5.
✅ Check 7 (no architecture hacks): PASS — no --hf-overrides/model-config edits; fp8 quant + fp8 kv-cache with passing evals; mamba flags are scheduler/cache runtime knobs, not FLOPs reduction.
✅ Check 8 (spec-decode chat template): PASS — all 7 MTP recipes set use_chat_template: true in their sa-bench blocks.
✅ Check 9 (no engine patches): PASS — recipes are declarative YAML; the runners/launch_gb200-nv.sh change is Enroot import plumbing (digest-URI translation + unsquashfs -l validation) and the pinned Dynamo hash is the declared dynamo-router frontend, not a modification of the shipped engine image.
➖ Check 10 (agentic golden AL): N/A — no agentic spec-decode changes (fixed-seq-len 8k1k only; agentic lanes skipped), and no simulated-acceptance knobs appear on these non-agentic configs.

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