skills/model-optimization/sglang/sglang-hunyuan3-preview-optimization/SKILL.md
PR-backed and current-main optimization manual for Tencent Hunyuan 3 Preview in SGLang. Use when an engineer needs to audit or extend Hunyuan3 Preview cookbook recipes, BF16 MoE hardware sizing, H200/B200/B300/GB300 command generation, MTP/EAGLE flags, `hunyuan` reasoning/tool parsers, Blackwell attention backend selection, or trust-remote-code launch guidance.
npx skillsauth add BBuf/AI-Infra-Auto-Driven-SKILLS sglang-hunyuan3-preview-optimizationInstall this skill globally with one command. Works with Claude Code, Cursor, and Windsurf.
3 of 9 scanners reported clean
Some scanners were skipped, did not run, or reported a non-clean status. Review each row below.
Hunyuan 3 Preview currently enters SGLang through docs/cookbook support with a copyable command generator. The PR is docs-only, but the generator records critical serving assumptions: BF16 weights, TP sizing by GPU memory, parser flags, MTP/EAGLE toggles, Blackwell trtllm_mha, and --trust-remote-code.
Current evidence snapshot:
origin/main: bca3dd958 on 2026-04-24docs_new/cookbook/autoregressive/Tencent/Hunyuan3-Preview.mdxdocs_new/src/snippets/autoregressive/hunyuan3-preview-deployment.jsxUse skills/model-optimization/model-pr-diff-dossier/SKILL.md as the production bar.
Every PR cited for this family must be based on diff reading, not only PR titles.
Capture:
SGLANG_ENABLE_SPEC_V2=1--reasoning-parser hunyuan, --tool-call-parser hunyuan--attention-backend trtllm_mha--trust-remote-code is presentTreat the command generator as deployment data.
--attention-backend trtllm_mha.Before adding Hunyuan3 Preview evidence, open the PR diff/source and update references/pr-history.md with motivation, implementation, code/config excerpts, reviewed files, and validation implications.
trtllm_mha.SGLANG_ENABLE_SPEC_V2=1 and EAGLE flags.--trust-remote-code always present.references/pr-history.md: diff-reviewed Hunyuan3 Preview PR cards.development
Perform SGLang code review in the style of human maintainers by consulting the full non-agent PR review episode corpus from project start through the latest refresh (June 2026), including inline review threads, top-level PR comments, review submissions, original multilingual text, and multi-round discussions. Use when reviewing SGLang PRs, diffs, patches, or local changes for correctness, tests, performance, GPU/runtime risks, API compatibility, and maintainability.
documentation
Use when an SGLang, vLLM, or TensorRT-LLM serving/model optimization task needs prior model-family PR evidence. Query and read the PR-driven history docs under model-pr-optimization-history before choosing source paths, fast paths, kernel/fusion ideas, regression risks, or validation lanes.
development
Run an autonomous Humanize-governed vLLM SOTA performance loop for one LLM model: first perform the fixed fair vLLM/SGLang/TensorRT-LLM deployment search and benchmark, then start one RLCR loop that repeatedly decides the gap, profiles the current bottleneck, runs layer/kernel pipeline analysis, patches vLLM code, optionally uses ncu-report-skill for kernel evidence, and revalidates until vLLM matches or beats the best observed framework under the same workload and SLA.
devops
Inspect LLM torch profiler traces at forward-pass, layer, and kernel level. Use when you need layer timings, anchor-kernel boundaries, representative kernel flows, or Perfetto time ranges.