# OpenCodeGoEvals

Benchmarks and plain-language notes for every model in the **OpenCode Go** catalog:
a task-by-task performance matrix, cost/value analysis, and a description of what each
model is actually targeted for (agentic work, coding, data analysis, image understanding,
deep research, high-volume chores).

Static site, no build step — it is plain HTML/CSS/ES modules, deployed to **Cloudflare Pages**.

## What's here

| Path | What it is |
|---|---|
| `site/index.html` | The site: performance matrix, price/value charts, model guide |
| `site/assets/data.js` | Model catalogue — pricing, context, modality, target descriptions, caveats |
| `site/assets/evals.js` | Benchmark scores (0–100) per model per task family |
| `site/assets/app.js` | Rendering logic for the matrix, charts and guide |
| `site/assets/style.css` | Styling |
| `MODELS.md` | The same model descriptions in Markdown |
| `wrangler.toml` | Cloudflare Pages project configuration |
| `.gitea/workflows/pages.yml` | CI: builds and deploys to Cloudflare Pages on every push to `main` |

## Data sources

- [OpenCode Go docs](https://opencode.ai/docs/go) — pricing, monthly allowances, privacy/retention, client support
- [OpenCode Data](https://opencode.ai/data) — catalog metadata, context windows, usage and retention stats
- [Artificial Analysis](https://artificialanalysis.ai) — benchmark scores and the Intelligence Index
- Vendor announcements — Google (Gemini 4 Argon), Reflection AI (Beam), Meituan (LongCat),
  MiniMax (M3.1 Flash), xAI (Grok 4.7), StepFun (Step 5), Qwen, Zhipu, Moonshot, DeepSeek, Xiaomi, Tencent

Data snapshot date: **2026-10-21**. Re-run the collection script to refresh.

## Publishing to Cloudflare Pages

### 1. Create the Pages project

```bash
npm install
npx wrangler login                       # or export CLOUDFLARE_API_TOKEN
npx wrangler pages project create opencodogoevals
```

### 2. Give CI the credentials

Add these as repository secrets (Gitea: *Settings → Actions → Secrets*):

| Secret | Value |
|---|---|
| `CLOUDFLARE_API_TOKEN` | Cloudflare API token with **Cloudflare Pages: Edit** (and Account Settings: Read) |
| `CLOUDFLARE_ACCOUNT_ID` | The Cloudflare account that owns the Pages project |

The workflow in `.gitea/workflows/pages.yml` then deploys `site/` on every push to `main`.

### 3. Deploy manually (optional)

```bash
npm run deploy        # wrangler pages deploy site --project-name opencodogoevals
npm run dev           # local preview on http://localhost:8788
```

### Custom domain

Set it in Cloudflare Pages → *Custom domains*, then add a CNAME record pointing at
`<project>.pages.dev`.

## Local development

The site is static — open `site/index.html` directly, or use `npm run dev` for a
Cloudflare-compatible local server.

## Updating the data

1. Benchmark scores come from each model's Artificial Analysis page
   (`https://artificialanalysis.ai/models/<slug>`) — the embedded JSON payload in the page
   contains the full evaluation set per model.
2. Catalog facts (pricing, context window, modalities, release date) come from
   `https://opencode.ai/data/<lab>/<model>.json` and the Go docs.
3. Edit `site/assets/evals.js` and `site/assets/data.js`, then regenerate `MODELS.md`
   from `data.js` and re-commit.

## Caveats

- Task-matrix cells use the best published evaluation per task family; when a model has
  not been run on a benchmark the column falls back to another one, so the underlying
  benchmark can differ between rows in a column. Hover a cell to see which one it is.
- Free-tier models (MiniMax M3.1 Flash Free, Beam Free, LongCat 2.5 Preview Free) are
  limited-time offers.
- Contributor-tier models (Gemini 4 Argon, Muse Spark 1.3) may use your prompts and
  completions for training — check the Go docs' privacy table.
- No Go model generates images; they are all text-output.

## License

MIT — see [LICENSE](LICENSE).