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Model x harness x effort registry; bigger top-bar controls

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Each entry is now explicitly a model x harness x effort combination:
models/*.json gains harness and effort fields, GPT-5.5 xhigh is
relabeled GPT-5.5 Codex (the harness distinguishes it from GPT-5.5
Pro), and the scrolling marquee is replaced by a readable registry
table (model / vendor / harness / effort / runs, pending rows dimmed)
with an explainer on the model-vs-harness relationship.

Top bar controls enlarged: segmented zh/EN switch and bordered 36px
icon buttons. README rewritten Chinese-first with a hand-maintained
registry snapshot table; README.en.md mirrors it.

Co-Authored-By: Claude Fable 5 <noreply@anthropic.com>
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Jesse ZhangandClaude Fable 5 committed 2026-06-10 12:09:09 +01:00
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README.en.md
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# NAGI BENCH
[中文](./README.md) | English
One-shot LLM eval cases by NAGI STUDIO: same prompt, different model x harness x effort combinations, one attempt and no retries — a side-by-side record of the runnable artifacts they ship.
**Live site:** https://bench.nagi.fun/
## Models vs harnesses
- **Model**: the weights and inference engine itself — GPT-5.5, Gemini 3.1 Pro, Claude Fable 5.
- **Harness**: the product/scaffolding wrapping the model — Codex CLI, Cursor, AntiGravity, the Claude web app. It controls tool calls, system prompts, context management and continuation strategy, and often shapes the outcome as much as the model does.
- The unit of evaluation here is therefore the **combination**: the same model under a different harness or effort level is a separate entry (GPT-5.5 Pro and GPT-5.5 Codex are two records of the same model family). Effort defaults to max; new effort variants of an existing combination can be added later.
## Registry
| Model | Vendor | Harness | Effort | Runs |
|---|---|---|---|---|
| Claude Fable 5 | Anthropic | Claude Web App | Max | 02 |
| GPT-5.5 Pro | OpenAI | ChatGPT Web | Extended Pro | 01 |
| GPT-5.5 Codex | OpenAI | Codex CLI (no skills) | xhigh | 02 |
| Gemini 3.1 Pro | Google | AntiGravity | High | 03 |
| Gemini 3.5 Flash | Google | AntiGravity | High | 03 |
| Grok Build | xAI | Grok Build TUI (local) | Max | 01 |
| Composer 2.5 | Cursor | Cursor | Max | 01 |
| DeepSeek-V4-Pro | DeepSeek | Claude Code | Max | 02 |
| Doubao Seed 2.0 Pro | ByteDance | Doubao Web | Pro Mode | 01 |
| Doubao Seed 2.0 Mini | ByteDance | Doubao Web | Fast Mode | 01 |
Pending: Mistral Medium 3.5 · Kimi K2.6 · MiniMax M3 · GLM-5.1 · Qwen3.7-Max (PRs welcome)
> This table is a hand-maintained snapshot; the site's registry section is generated live from `models/*.json` and is authoritative.
## Structure
```
outputs/<model-id>/<case-id>.<ext> raw model artifacts (HTML / SVG), filename = case id
models/<model-id>.json combination registry: label / vendor / harness / effort / order / run notes
site/ showcase app (Vite + React + Tailwind v4 + GSAP, bun)
site/src/data/cases.json case definitions (bilingual prompts, maintainer-owned)
.github/workflows/ deploy.yml deploys; ci.yml validates data + builds on PRs
```
## Development
```bash
cd site
bun install
bun run dev # syncs outputs/ and serves http://localhost:5173/
bun run build # data validation + type-check + build (site/dist)
```
## Contributing a run
Contributions are data-only — no code changes needed:
1. Artifact: `outputs/<model-id>/<case-id>.<ext>` (e.g. `outputs/gpt-5-5-pro/pelican-cycling.svg`).
2. Registration: `models/<model-id>.json` (new file for a new combination; add to `runs` for an existing one) — see the schema example in the Chinese README.
CI-enforced rules: dash-only lowercase ids matching the `outputs/` folder name; a **required bilingual provenance `note`** per run (which harness, what effort, one-shot or fixed); every declared run must have its artifact; multiple versions of the same combination x case go in an array with distinct `file` names (e.g. `pelican-cycling-2.svg`).
PRs get data validation + a build from CI; merges to `main` deploy automatically.
README.md
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# NAGI BENCH
NAGI STUDIO 的 LLM 测评案例集：同一段提示词，不同模型，一次生成、不许返工，并排对比它们交出的可运行作品。
中文 | [English](./README.en.md)
One-shot LLM eval cases by NAGI STUDIO: same prompt, different models, one attempt and no retries — a side-by-side record of the runnable artifacts they ship.
NAGI STUDIO 的 LLM 测评案例集：同一段提示词，不同「模型 × Harness × 思考配额」组合，一次生成、不许返工，并排对比它们交出的可运行作品。
**Live site:** https://bench.nagi.fun/
**线上站点：** https://bench.nagi.fun/
## 模型与 Harness 的关系
- **模型（Model）**：权重与推理引擎本身，如 GPT-5.5、Gemini 3.1 Pro、Claude Fable 5。
- **Harness（运行环境）**：包裹模型的产品/脚手架，如 Codex CLI、Cursor、AntiGravity、Claude 网页版——它决定工具调用、系统提示词、上下文管理与续写策略，对最终产出的影响往往不亚于模型本身。
- 因此本仓库的测评单位是**组合**：同一个模型在不同 Harness 或不同思考配额下，记为不同条目（例如 GPT-5.5 Pro 与 GPT-5.5 Codex 是同一模型家族的两条记录）。思考配额默认拉满（Max），未来同一组合可以追加新配额版本。
## 已测组合 / Registry
| 模型 | 厂商 | Harness 环境 | 思考配额 | 产出 |
|---|---|---|---|---|
| Claude Fable 5 | Anthropic | Claude 网页版 | Max | 02 |
| GPT-5.5 Pro | OpenAI | ChatGPT 网页版 | Extended Pro | 01 |
| GPT-5.5 Codex | OpenAI | Codex CLI（无 skill） | xhigh | 02 |
| Gemini 3.1 Pro | Google | AntiGravity | High | 03 |
| Gemini 3.5 Flash | Google | AntiGravity | High | 03 |
| Grok Build | xAI | Grok Build TUI（本地） | Max | 01 |
| Composer 2.5 | Cursor | Cursor | Max | 01 |
| DeepSeek-V4-Pro | DeepSeek | Claude Code | Max | 02 |
| Doubao Seed 2.0 Pro | ByteDance | 豆包网页版 | 超能模式 | 01 |
| Doubao Seed 2.0 Mini | ByteDance | 豆包网页版 | 快速模式 | 01 |
待测：Mistral Medium 3.5 · Kimi K2.6 · MiniMax M3 · GLM-5.1 · Qwen3.7-Max（欢迎 PR 补充）
> 此表为人工维护的快照；站点上的「模型阵容」表由 `models/*.json` 实时生成，以站点为准。
## 结构 / Structure
```
outputs/<model-id>/<case-id>.<ext> 模型产出原文件（HTML / SVG），文件名 = 案例 id
models/<model-id>.json 模型登记：label / vendor / order / 各案例运行备注
models/<model-id>.json 组合登记：label / vendor / harness / effort / order / 各案例运行备注
site/ 展示站点（Vite + React + Tailwind v4 + GSAP，bun 驱动）
site/src/data/cases.json 案例定义：双语标题与提示词（维护者维护）
.github/workflows/ deploy.yml 自动部署；ci.yml 对 PR 跑数据校验 + 构建
```
## URL 规则 / URL scheme
| URL | 含义 / Meaning |
| --- | --- |
| `https://bench.nagi.fun/` | 站点首页 / Home |
| `https://bench.nagi.fun/#<case-id>` | 定位到某个案例 / Anchor to a case (e.g. `#mythos-craft`) |
| `https://bench.nagi.fun/#<case-id>:<model-id>` | 定位案例并选中模型 / Case + preselected model tab |
| `https://bench.nagi.fun/outputs/<model-id>/<case-id>.<ext>` | 产物直链 / Raw artifact |
切换模型标签时地址栏自动更新（`replaceState`），当前视图随时可直接分享。旧域名链接（`https://nagi-studio.github.io/nagi-bench/*`）由 GitHub Pages 自动 301 重定向到 `https://bench.nagi.fun/*`，路径保留。
Switching a model tab updates the address bar in place, so the current view is always shareable. Legacy `nagi-studio.github.io/nagi-bench/*` links are 301-redirected by GitHub Pages to `bench.nagi.fun/*` with the path preserved.
## 本地开发 / Development
```bash
cd site
bun install
bun run dev # 同步 outputs/ 并启动 http://localhost:5173/
bun run build # 类型检查 + 产物构建（输出到 site/dist）
bun run build # 数据校验 + 类型检查 + 产物构建（输出到 site/dist）
```
## 贡献一个模型产出 / Contributing a run
@@ -43,18 +55,20 @@ bun run build # 类型检查 + 产物构建（输出到 site/dist）
贡献**不需要改任何代码**，只涉及两类文件：
1. 产出文件：`outputs/<model-id>/<case-id>.<ext>`（如 `outputs/gpt-5-5-pro/pelican-cycling.svg`）。
2. 模型登记：`models/<model-id>.json`（新模型新建文件；已有模型在 `runs` 里加一条）：
2. 组合登记：`models/<model-id>.json`（新组合新建文件；已有组合在 `runs` 里加一条）：
```json
{
"label": "GPT-5.5 Pro",
"vendor": "OpenAI",
"harness": "ChatGPT Web",
"effort": "Extended Pro",
"order": 20,
"runs": {
"pelican-cycling": {
"note": {
"zh": "在哪个工具/产品里、什么思考档位、是否一次生成、是否有修复",
"en": "Which tool, what effort level, one-shot or fixed"
"zh": "在哪个 Harness 里、什么思考档位、是否一次生成、是否有修复",
"en": "Which harness, what effort level, one-shot or fixed"
}
}
}
@@ -64,8 +78,7 @@ bun run build # 类型检查 + 产物构建（输出到 site/dist）
规则（CI 自动校验，不满足会挂）：
- `model-id` 只用小写字母/数字/连字符（如 `doubao-seed-2-0-pro`），文件名与 `outputs/` 目录名一致；
- 每条 run 的 `note` **双语必填**——这是本仓库的可信度来源，必须写明产出怎么来的；
- 声明的 run 必须有对应的产出文件。
- 声明的 run 必须有对应的产出文件；
- 同一组合对同一案例可提交多个版本：`runs.<case-id>` 写成数组，第二个版本起必须用 `file` 指定不同文件名（如 `pelican-cycling-2.svg`）。
提 PR 后 CI 会跑数据校验 + 构建；合入 `main` 自动部署。
Contributions are data-only — no code changes needed. Drop the artifact into `outputs/<model-id>/<case-id>.<ext>` and register it in `models/<model-id>.json` (schema above). CI enforces: dash-only ids matching the folder name, a required bilingual provenance `note` per run, and that every declared run has its artifact. Merges to `main` deploy automatically.