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Add Kimi K2.6 NVFP4 B200 Dynamo vLLM configuration / 新增 Kimi K2.6 NVFP4 B200 Dynamo vLLM 配置 - #2360

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Add Kimi K2.6 NVFP4 B200 Dynamo vLLM configuration / 新增 Kimi K2.6 NVFP4 B200 Dynamo vLLM 配置#2360
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@RohitNagraj

@RohitNagraj RohitNagraj commented Jul 27, 2026

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Summary

  • Add the Kimi K2.6 NVFP4 B200 Dynamo vLLM disaggregated configuration.
  • Register seven checked-in 8K/1K prefill/decode topology and concurrency recipes.
  • Pin the current NVIDIA/srt-slurm main commit for runtime, then overlay the checked-in recipes and run the vLLM v0.25.1 image without setup hooks or runtime engine patches.

Recipe definitions: NVIDIA/srt-slurm#282

Recipe reference: Kimi-K2.6 vLLM recipe

中文说明

  • 新增 Kimi K2.6 NVFP4 B200 Dynamo vLLM 分离式推理配置。
  • 注册七个随代码提交的 8K/1K 预填充/解码拓扑与并发配方。
  • 固定当前 NVIDIA/srt-slurm main 提交作为运行时基础,随后覆盖加入随代码提交的配方,并直接运行 vLLM v0.25.1 镜像,不使用额外的 setup hook 或运行时引擎补丁。

配方定义:NVIDIA/srt-slurm#282

配方参考:Kimi-K2.6 vLLM 配方

Add seven 8K/1K disaggregated configuration points and load their recipes from NVIDIA/srt-slurm.

中文:新增 Kimi K2.6 B200 Dynamo vLLM 配置,注册七个 8K/1K 分离式推理配置项,并从 NVIDIA/srt-slurm 加载相应配方。
中文:在性能变更日志中补充 #2360 的 PR 链接。
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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

Fetch the public recipe PR ref and check out its immutable commit before launching the configuration.

中文:获取公开配方 PR 引用,并在启动配置前检出其不可变提交。
Bring the configuration branch up to date with the latest public repository changes.

中文:将配置分支同步到公开仓库的最新 main。
Point the B200 launch script at the Kimi K2.6 NVFP4 checkpoint staged on cluster storage.

中文:将 B200 启动脚本指向集群存储中已准备好的 Kimi K2.6 NVFP4 模型路径。
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RohitNagraj marked this pull request as ready for review July 27, 2026 23:00
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RohitNagraj requested a review from a team July 27, 2026 23:00
@claude

claude Bot commented Jul 27, 2026

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Claude finished @RohitNagraj's task in 5m 16s —— View job


PR Review

  • Read PR diff (configs/nvidia-master.yaml, perf-changelog.yaml, runners/launch_b200-dgxc.sh)
  • Validate config structure against utils/matrix_logic/validation.py and the existing kimik2.5-fp4-gb200-dynamo-vllm entry
  • Check master-config/perf-changelog pairing and entry position
  • Check image accessibility and enroot import path
  • Review launcher changes (model resolution, srt-slurm pinning)

Summary

No blocking issues found. One 🟡 warning posted inline: the srt-slurm pin in runners/launch_b200-dgxc.sh:120-121 checks out a SHA that is only reachable via refs/pull/282/head of an open upstream PR, and a failed checkout isn't caught — if that PR is force-pushed, the run would silently continue on main without the Kimi K2.6 recipes and fail confusingly at srtctl apply. Adding || exit 1 (and repointing to a main-reachable SHA once srt-slurm#282 merges) addresses it.

Everything else checks out:

  • perf-changelog.yaml entry is present and correctly appended at the end of the file.
  • vllm/vllm-openai:v0.25.1 is a public Docker Hub image, and the launcher's existing import_squash enroot flow covers it.
  • All seven search-space entries are internally consistent — the prefill/decode num-worker/tp/ep metadata matches the topology encoded in each CONFIG_FILE name (1p1d-dep8-tp8-c1, 1p8d-dep4-tp4-c32/128, 1p4d-dep4-tp4-c512, 1p1d-dep4-dep8-c1024, 1p1d-dep8-dep8-c2048, 2p1d-dep8-dep8-c8192), and the entry structure mirrors the merged kimik2.5-fp4-gb200-dynamo-vllm config.
  • Missing kimik2.6 keys in utils/evals/thresholds.yaml and configs/ci-priority.yaml degrade gracefully (default thresholds / no priority adjustment), so they're non-blocking.

Two things I could not verify from this environment (network-restricted) and which the sweep run will confirm:

  1. That the seven recipe files under recipes/vllm/kimi-k2.6/b200-fp4/8k1k/ actually exist at the pinned srt-slurm commit d94c8505.
  2. That the recipes reference the model alias kimi-k2.6-nvfp4 — that string must match the model: field in the srt-slurm recipe YAMLs, since it's what the launcher maps to /scratch/models/Kimi-K2.6-NVFP4 in srtslurm.yaml.

Minor non-blocking note: kimik2.6 isn't in the priority-classifier model enum in .github/workflows/run-sweep.yml (line 247) or the model-prefix weights in configs/ci-priority.yaml, so these jobs will just get default scheduling priority — fine to leave, or add alongside a future change.

Comment thread runners/launch_b200-dgxc.sh Outdated
Comment on lines +120 to +121
git fetch origin refs/pull/282/head
git checkout d94c8505136b1e021ade99f1e7cd3359fc491cb9

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🟡 WARNING: Pinned SHA d94c8505 is only reachable through refs/pull/282/head, and a failed checkout is not caught.

Why it matters: Unlike the sibling branches here (which pin a branch/tag or a SHA on main), this SHA lives only on an open PR's head ref. If NVIDIA/srt-slurm#282 is force-pushed or rebased before merge, git fetch origin refs/pull/282/head will no longer bring in d94c8505, the git checkout fails, and — since the script has no set -e — the run silently continues on main without recipes/vllm/kimi-k2.6/..., failing much later at the sed/srtctl apply step with a confusing error.

Fix: Fail fast on checkout so the root cause is obvious:

Suggested change
git fetch origin refs/pull/282/head
git checkout d94c8505136b1e021ade99f1e7cd3359fc491cb9
git fetch origin refs/pull/282/head
git checkout d94c8505136b1e021ade99f1e7cd3359fc491cb9 || exit 1

Longer-term, once srt-slurm#282 merges, repoint this at a main-reachable SHA (like the dsr1-fp4 case above) so the pin can't be orphaned.

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LGTM — straightforward, well-patterned model onboarding config for Kimi K2.6 on B200.

What was reviewed: the new kimik2.6-fp4-b200-dynamo-vllm master-config entry (structure matches existing Kimi K2.5/GLM-5/DSv4 disaggregated dynamo-vllm entries), the perf-changelog addition, and the new MODEL_PATH/SRT_SLURM_MODEL_PREFIX + srt-slurm checkout branch in launch_b200-dgxc.sh. The bug hunting system flagged the /scratch/models vs /scratch/fsw/models path convention as a candidate issue and ruled it out; I don't have cluster access to independently confirm the staging path, but the launcher fails loudly (missing MODEL_PATH check + full-sweep CI) if it's wrong, so it will surface quickly rather than silently corrupting results.

Extended reasoning...

Overview

This PR adds a new model recipe: Kimi K2.6 NVFP4 disaggregated prefill/decode config for B200 using Dynamo vLLM. It touches three files: configs/nvidia-master.yaml (new top-level config block with 7 concurrency scenarios pointing to srt-slurm recipe YAMLs), perf-changelog.yaml (changelog entry), and runners/launch_b200-dgxc.sh (new MODEL_PATH resolution branch and a new srt-slurm checkout branch pinned to a specific commit on NVIDIA/srt-slurm PR #282).

Security risks

None. This is a benchmark configuration and CI launcher change — no user input handling, auth, or crypto involved. The srt-slurm checkout is pinned to a specific commit hash (not a floating branch), which is the safer pattern already used elsewhere in this file (e.g. the dsr1 sglang branch has an explicit comment about not floating on main).

Level of scrutiny

This is a standard 'add a new model+hardware recipe' PR, which is a well-trodden, high-frequency pattern in this repo (dozens of near-identical entries already exist for other models/precisions). The new master-config block and launcher branch are structurally identical to existing Kimi K2.5 / GLM-5 / DSv4 entries, so the risk of a subtle logic bug is low, and the PR review checklist already gates this via CODEOWNER sign-off and the full-sweep CI (which actually runs the job on hardware and would fail loudly on a bad MODEL_PATH or CONFIG_FILE reference). The main manual-review-only risk is the exact MODEL_PATH staging convention, which the bug hunting system already flagged and investigated.

Other factors

No unresolved review comments in the timeline. This is the first substantive review pass on this PR (only the automated recipe-reminder bot and a placeholder "working" comment precede it).

Stop the B200 launcher immediately when the pinned srt-slurm recipe commit cannot be checked out.

中文:当固定的 srt-slurm 配方提交无法检出时,立即终止 B200 启动流程。
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Pass --no-preflight only for Kimi K2.6 FP4 Dynamo-vLLM so srtctl can submit recipes whose model path is available on Slurm compute nodes.

中文:仅为 Kimi K2.6 FP4 Dynamo-vLLM 传递 --no-preflight,使 srtctl 能够提交模型路径仅在 Slurm 计算节点可用的配方。
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Point Kimi K2.6 NVFP4 at the shared Lustre path exposed on B200 Slurm nodes.

中文:将 Kimi K2.6 NVFP4 指向 B200 Slurm 节点可访问的共享 Lustre 路径。
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sorry @RohitNagraj i am cancelling https://github.com/SemiAnalysisAI/InferenceX/actions/runs/30314875577 for the day 0 k3 rn

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Update the pinned srt-slurm recipe revision so multi-prefill workers rely on vLLM-generated engine IDs.

中文:更新固定的 srt-slurm 配方版本,使多预填充工作进程使用 vLLM 自动生成的 engine ID。
Preserve current main and re-append the Kimi K2.6 changelog entry at EOF.

中文:合并当前 main,并在文件末尾重新追加 Kimi K2.6 变更日志条目。
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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. Run Sweep 30418587119
  • Verified that this PR passes evals. Please link to GitHub Action workflow that shows this. Run Sweep 30418587119
  • 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:

  • Exact-head evidence: Run Sweep 30418587119, attempt 2, passed all seven applicable multi-node 8k1k benchmark jobs and all six materialized non-skipped multi-node eval jobs on 97a9cf794dafc107a8f547a46b3674b748b84ff7.
  • Speculative-decoding and agentic acceptance criteria are not applicable: this PR introduces neither speculative decoding nor an agentic workload.
  • The model architecture is unchanged: the configuration contains no --hf-overrides or reduced-FLOP architecture hack.
  • Single-node recipe publication criteria are not applicable. This PR adds a multinode: true, disagg: true configuration only, and every referenced recipe is a multi-node disaggregated recipe supplied by pinned NVIDIA/srt-slurm PR #282 commit 003cc5d5f350fbe8838e950ad197736fb85a5559; no vLLM recipes-repository submission is required by the live checklist for this PR.
  • The submission uses the upstream vllm/vllm-openai:v0.25.1 image, and vLLM is the submitted inference engine; no additional-framework ordering exception is needed.
  • The diff contains no inference-engine or serving-stack patch. The runner fetches a pinned srt-slurm recipe commit, adjusts only srt-slurm job configuration, and disables login-node preflight for compute-node-staged weights; it does not rewrite vLLM sources, site-packages, or container files and does not install a forked/rebuilt engine wheel. No waiver is required.

Signed: Ankur-singh

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❌❌❌ REJECTED ❌❌❌

@Ankur-singh — blocking issue: this PR's pinned benchmark path patches the vLLM engine inside the pinned image at runtime, with no waiver at docs/waiver/2360.md and a sign-off that states no patching exists. See Check 9.

✅ Check 0 (CODEOWNER): PASS — Ankur-singh is a listed owner of configs/nvidia-master.yaml; the other changed paths carry only the catch-all default.
✅ Check 1 (green sweep on in-PR commit): PASS — run 30418587119 on head 97a9cf7: all 7 multi-node 8k1k / and all 6 materialized multi-node eval / jobs concluded success (executed, not skipped).
✅ Check 2 (evals pass): PASS — GSM8K em_strict 0.9689–0.9735 (n=1319) across the 6 eval lanes vs the 0.90 bar (utils/evals/thresholds.yaml default), run on the same vllm/vllm-openai:v0.25.1 image as this PR's config.
➖ Check 3 (recipe linked/merged): N/A — disaggregated/multi-node submission (multinode: true, disagg: true, dynamo-vllm); the recipe-link requirement applies to single-node recipes only.
✅ Check 4 (reuse command): PASS — /reuse-sweep-run 30418587119 posted by Ankur-singh (COLLABORATOR).
✅ Check 5 (latest checklist): PASS — every current-template item is present and checked.
✅ Check 6 (upstream image / engine-first): PASS — upstream vllm/vllm-openai:v0.25.1; vLLM is the serving engine under Dynamo orchestration, the sign-off documents this, and it matches merged precedent (kimik2.5-fp4-gb200-dynamo-vllm, kimik3-fp4-b200-dynamo-vllm-agentic).
✅ Check 7 (no architecture hacks): PASS — no --hf-overrides or FLOP-reducing knobs in the diff or the seven pinned recipe YAMLs; compilation/fusion flags only.
➖ Check 8 (spec-decode chat template): N/A — no speculative decoding in this PR.
❌ Check 9 (no engine patches): FAIL — the benchmark path rewrites installed vLLM engine sources before serving, and no waiver exists. All seven pinned recipe YAMLs set setup_script: vllm-container-deps.sh; srtctl runs it in every worker container preamble (src/srtctl/cli/mixins/worker_stage.py /configs/patches/ fallback), and at the pinned commit it executes vllm_numa_bind_hash_fix.py, which edits /usr/local/lib/python3.12/dist-packages/vllm/config/parallel.py (ParallelConfig.compute_hash ignored_factors) inside vllm/vllm-openai:v0.25.1. This PR adds no docs/waiver/2360.md, docs/waiver/ on the default branch is empty, and the sign-off's "no inference-engine or serving-stack patch … no waiver is required" is contradicted by the pinned recipe contents. Fix: file and link a waiver covering this patch, or repin to a recipe commit whose setup path does not modify engine sources, then re-sign.
➖ Check 10 (agentic golden AL): N/A — no agentic speculative-decoding changes.

Add seven checked-in srt-slurm recipes, pin the current srt-slurm main commit, and run the vLLM 0.25.1 image without setup hooks or runtime patches.

中文:将 Kimi K2.6 配置同步到当前 main,加入七个随代码提交的 srt-slurm 配方,固定当前 srt-slurm main 提交,并直接运行 vLLM 0.25.1 镜像,不使用额外的 setup hook 或运行时补丁。
@SemiAnalysisAI SemiAnalysisAI deleted a comment from Ankur-singh Jul 29, 2026
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