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Author SHA1 Message Date
noonghunna
3fa33332ce Initial commit — club-3090: model-agnostic LLM serving recipes for RTX 3090
Consolidates and supersedes:
  - noonghunna/qwen36-27b-single-3090
  - noonghunna/qwen36-dual-3090

The two predecessor repos partitioned by card count (1× vs 2×). This
repo partitions by engine instead, which matches how users actually
decide ("vLLM or llama.cpp?" before "1 card or 2"). Card count becomes
a config variant within each engine.

Structure (model-agnostic from day 1):

  docs/                       cross-model engine + hardware docs
    engines/                    vLLM / llama.cpp / SGLang comparison + per-engine deep dives
    HARDWARE.md                 Ampere SM 8.6+, NVLink, power, VRAM ceilings
    GLOSSARY.md                 plain-language definitions
    img/                        illustrations (vram-budget.svg)
    ARCHITECTURE.md             how this stack thinks about LLM serving on 24 GB

  models/<model-name>/        everything specific to a model
    qwen3.6-27b/                today's only model
      README.md / INTERNALS.md / USE_CASES.md / CHANGELOG.md
      vllm/                     vLLM-specific configs for this model
        compose/                  docker-compose files (single + dual variants)
        patches/                  tolist_cudagraph + Marlin pad notes
      llama-cpp/                llama.cpp recipes for this model
        recipes/                  shell scripts (single-card default + 262K max-ctx)
      sglang/                   SGLang status (currently blocked)

  scripts/                    shared, model-aware
    setup.sh                    bash setup.sh <model> → downloads + verifies
    verify.sh / verify-full.sh  smoke + functional tests
    bench.sh                    canonical TPS bench

vLLM compose variants (all under models/qwen3.6-27b/vllm/compose/):

  Single-card:
    docker-compose.yml              DEFAULT — TQ3 + Genesis P65, 48K, 51/68 TPS
    docker-compose.fast-chat.yml   fp8 + 20K, 55/70 TPS — fastest at small ctx
    docker-compose.tools-text.yml  fp8 + 75K, 53/70 TPS — best for long single prompts
    docker-compose.no-genesis-mtp.yml control variant
    docker-compose.minimal.yml     no spec-decode

  Dual-card:
    docker-compose.dual.yml              fp8 + 262K + MTP + vision, 71/89 TPS
    docker-compose.dual-turbo.yml       TQ3 + Genesis v7.14 — 4-stream concurrency
    docker-compose.dual-dflash.yml      DFlash N=5 + 185K + vision — 78/128 TPS
    docker-compose.dual-dflash-noviz.yml DFlash + 200K text-only

llama.cpp recipes (under models/qwen3.6-27b/llama-cpp/recipes/):

  single-card-default.sh    Q4_K_M + 65K
  single-card-max-ctx.sh    Q4_K_M + q4_0 KV at full 262K — the standout recipe

Old repos remain readable for issue history + external links (Medium,
Reddit, Twitter, Sandermage's PR threads). New issues should be filed
here.

Credits in README. Apache 2.0.
2026-04-28 10:24:14 +00:00