| `multiNodeHints` | `{[hwId]: string[]}` | Lines prepended as `# ...` comments to multi-node commands (env-var hints). Per-hw, and only for hw whose **cluster fabric needs manual NIC config** (e.g. `gb200` NVL72/MNNVL → NVSHMEM/Gloo hints). NOT every multi-N hw needs an entry — standard-IB DeepEP (h200) auto-detects the HCA, and Marlin multi-node (h100) uses no DeepEP/NVSHMEM at all. |
| `dockerImages` | `{[key]: string}` | Image for `docker run` framing, keyed by `hw\|quant` (most specific) then `hw`. Use a `hw\|quant` key only when one quant on a shared GPU needs a different image (e.g. an NVFP4 dev build on b300/gb300 while FP8/BF16 stay on the release image); otherwise key by plain `hw`. **Ask the user which sglang build the recipes ran on; don't guess a supporting release.** Falls back to `lmsysorg/sglang:dev` if missing — also the sensible default when unsure. |
| `playgroundFeatures` | `{[axisId]: {...}}` | Opts into the Playground widget. See §2.3. |
| `benchmarkCommands` | `{speed: string, accuracy: {[accKey]: string \| {[variant]: string}}, numPromptsByConc?: {[c]: number}}` | Powers the benchmark card's **"⚡ Reproduce"** modal. `speed` is ONE `bench_serving` template; the engine fills `{{DATASET}}`/`{{ISL}}`/`{{OSL}}` from each cell's `speed[].workload`, the chip-picked `{{MAX_CONCURRENCY}}`, and `{{NUM_PROMPTS}}` (resolved `workload.num_prompts ?? numPromptsByConc[c] ?? max(c*2, 200)`). `accuracy` maps an accuracy field (e.g. `gsm8k_pct`) to a per-eval template — a string, OR a `{flash, pro, …}` object keyed by variant when the command differs per variant (e.g. GPQA/AIME `--max-tokens`). The modal renders a chip per eval (one command area, like Speed). Both also use `{{MODEL_NAME}}` + `{{CURL_HOST}}`/`{{CURL_PORT}}` like `curl`. Optional; the button only appears when this AND `benchmarks` are present. |
| `benchmarkCommands` | `{speed: string, accuracy: {[accKey]: string \| {[variant]: string}}, numPromptsByConc?: {[c]: number}}` | Powers the benchmark card's **"⚡ Reproduce"** modal. `speed` is ONE `bench_serving` template; the engine fills `{{DATASET}}`/`{{ISL}}`/`{{OSL}}` from each cell's `speed[].workload`, the chip-picked `{{MAX_CONCURRENCY}}`, and `{{NUM_PROMPTS}}` (resolved `workload.num_prompts ?? numPromptsByConc[c] ?? max(c*2, 200)`). `accuracy` maps an accuracy field (e.g. `gsm8k_pct`) to a per-eval template — a string, OR a `{flash, pro, …}` object keyed by variant when the command differs per variant (e.g. GPQA/AIME `--max-tokens`). The modal renders a chip per eval (one command area, like Speed). Both also use `{{MODEL_NAME}}` + `{{CURL_HOST}}`/`{{CURL_PORT}}` like `curl`.`speed` should carry `--flush-cache` (bench_serving's `random` prompts are deterministic — warm reruns hit the radix cache and inflate throughput; measure cache-cold). Optional; the button only appears when this AND `benchmarks` are present. |
| `defaultAccuracy` | `{[variant]: {[accKey]: number}}` | Model-level accuracy applied to **every** cell of a variant (e.g. GPQA Diamond / AIME25 — hardware-independent). Merged UNDER each cell's measured `accuracy` (a per-cell value wins), so you set a variant's score once instead of copying it onto every benchmark entry. Keys must match `accuracyLabels` (below) + `benchmarkCommands.accuracy`. |
| `accuracyLabels` | `[key, label, unit][]` | The eval set rendered in the benchmark card and the "⚡ Reproduce" modal — **the engine ships no default**, every config declares its own (e.g. DSv4: GPQA/AIME25/GSM8K; Qwen3.5: GSM8K/MMMU). Required whenever the benchmarks carry accuracy data; without it the accuracy rows silently don't render. Every key used in `benchmarks[].accuracy`, `defaultAccuracy`, and `benchmarkCommands.accuracy` must appear here. |
| `latencyPercentile` | `"Mean" \| "P50"` | Optional, **temporary**; the percentile the benchmark TTFT/TPOT values are. **Default `"P50"`** — the card renders `TTFT (<pct>)` / `TPOT (<pct>)`. Set `"Mean"` only for legacy data recorded as Mean (being re-measured to P50). `tokens_per_sec_per_gpu` is stored as **total (in+out)/GPU** = `output tok/s/GPU × (isl+osl)/osl`, shown by the card as-is. |
| `latencyPercentile` | `"Mean" \| "P50"` | Optional, **temporary**; the percentile the benchmark TTFT/TPOT values are. **Default `"P50"`** — the card renders `TTFT (<pct>)` / `TPOT (<pct>)`. Set `"Mean"` only for legacy data recorded as Mean (being re-measured to P50). A benchmarks entry may carry its own `latencyPercentile` to override the page value per cell (entry → config → `"P50"`).`tokens_per_sec_per_gpu` is stored as **total (in+out)/GPU** = `output tok/s/GPU × (isl+osl)/osl`, shown by the card as-is. |
| `github` | `{owner?, repo?, issueTemplate?, cookbookModel?}` | Overrides for the "Submit verified cell" CTA in the playground. Defaults: `sgl-project/sglang` + `3-playground-verified-cell.yml` + `"deepseek-ai/deepseek-v4"`. Set `cookbookModel` to the model's HF id (`<hf-org>/<model-slug>`); it prefills the issue template's free-form `model` input when the issue opens. **Don't prune this block** — without it the engine falls back to `deepseek-ai/deepseek-v4` and submissions from your page get mislabeled. |
`# To install sgl-eval: pip install git+https://github.com/sgl-project/sgl-eval
@@ -1276,7 +1276,7 @@ sgl-eval run aime25 \\
"--speculative-num-steps 3",
"--speculative-eagle-topk 1",
"--speculative-num-draft-tokens 4",
"--mem-fraction-static 0.83",
"--mem-fraction-static 0.90",
"--host {{HOST_IP}}",
"--port {{PORT}}",
],
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Douglas Yang