docs(cookbook): total (input+output) throughput per GPU + percentile latency labels (#30214)

Co-authored-by: Claude Opus 4.8 <noreply@anthropic.com>

.claude/skills/cookbook-add-model/references/authoring-reference.md

@@ -49,6 +49,7 @@ the full contract):
 | `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. |
 | `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. |
 | `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. |
 
 ## 2.2 Author the 5-dim matrix (`cells[]`)

.claude/skills/cookbook-add-model/templates/benchmarks.jsx.tmpl

@@ -6,7 +6,10 @@
 // One entry per cell `match` tuple (same 5 keys as config cells). The card stays
 // "pending" until an entry has a non-null speed metric or accuracy. Speed shape:
 //   speed: [{ workload: {dataset, isl, osl, max_concurrency}, ttft_ms, tpot_ms,
-//             tokens_per_sec_per_gpu }, ...]   // interactivity is derived (1000/TPOT)
+//             tokens_per_sec_per_gpu }, ...]
+//   - ttft_ms/tpot_ms are P50 (median); set config.latencyPercentile ("P50" default, or "Mean").
+//   - tokens_per_sec_per_gpu = total (in+out) tok/s/GPU
+//     (= output tok/s ÷ GPUs × (isl+osl)/osl). interactivity is derived = 1000/TPOT (tokens/s/user).
 // Per-cell `accuracy: { <key>: <pct> }` overrides the config's defaultAccuracy.
 
 export const benchmarks = [