devadmin
46447d422b
Deploy to Cloudflare Pages / deploy (push) Failing after 25s
- scripts/deploy.sh: manual Cloudflare Pages deploy (same steps as CI) - scripts/refresh-evals.mjs: re-scrape Artificial Analysis + OpenCode Data into evals.js - evals.js now carries OpenCode Go list prices; Hy4 and LongCat 2.5 left empty rather than borrowing a neighbouring model's numbers - workflow creates the Pages project idempotently
103 lines
4.2 KiB
Markdown
103 lines
4.2 KiB
Markdown
# OpenCodeGoEvals
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Benchmarks and plain-language notes for every model in the **OpenCode Go** catalog:
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a task-by-task performance matrix, cost/value analysis, and a description of what each
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model is actually targeted for (agentic work, coding, data analysis, image understanding,
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deep research, high-volume chores).
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Static site, no build step — it is plain HTML/CSS/ES modules, deployed to **Cloudflare Pages**.
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## What's here
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| Path | What it is |
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| `site/index.html` | The site: performance matrix, price/value charts, model guide |
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| `site/assets/data.js` | Model catalogue — pricing, context, modality, target descriptions, caveats |
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| `site/assets/evals.js` | Benchmark scores (0–100) per model per task family |
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| `site/assets/app.js` | Rendering logic for the matrix, charts and guide |
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| `site/assets/style.css` | Styling |
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| `MODELS.md` | The same model descriptions in Markdown |
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| `wrangler.toml` | Cloudflare Pages project configuration |
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| `.gitea/workflows/pages.yml` | CI: builds and deploys to Cloudflare Pages on every push to `main` |
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## Data sources
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- [OpenCode Go docs](https://opencode.ai/docs/go) — pricing, monthly allowances, privacy/retention, client support
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- [OpenCode Data](https://opencode.ai/data) — catalog metadata, context windows, usage and retention stats
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- [Artificial Analysis](https://artificialanalysis.ai) — benchmark scores and the Intelligence Index
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- Vendor announcements — Google (Gemini 4 Argon), Reflection AI (Beam), Meituan (LongCat),
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MiniMax (M3.1 Flash), xAI (Grok 4.7), StepFun (Step 5), Qwen, Zhipu, Moonshot, DeepSeek, Xiaomi, Tencent
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Data snapshot date: **2026-10-21**. Re-run the collection script to refresh.
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## Publishing to Cloudflare Pages
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### 1. Create the Pages project
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```bash
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npm install
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npx wrangler login # or export CLOUDFLARE_API_TOKEN
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npx wrangler pages project create opencodogoevals
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```
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### 2. Give CI the credentials
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Add these as repository secrets (Gitea: *Settings → Actions → Secrets*):
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| Secret | Value |
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| `CLOUDFLARE_API_TOKEN` | Cloudflare API token with **Cloudflare Pages: Edit** (and Account Settings: Read) |
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| `CLOUDFLARE_ACCOUNT_ID` | The Cloudflare account that owns the Pages project |
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The workflow in `.gitea/workflows/pages.yml` then:
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1. checks out the repo and installs Wrangler,
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2. stages `MODELS.md` next to the site,
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3. creates the Pages project if it does not exist yet (idempotent),
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4. deploys `site/` on every push to `main`, on a manual *Run workflow*, and hourly.
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A runner must be registered on the Gitea instance for the workflow to execute.
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### 3. Deploy manually (optional)
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```bash
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./scripts/deploy.sh # uses env vars or your wrangler login session
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npm run deploy # same thing, wrangler only
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npm run dev # local preview on http://localhost:8788
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```
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### Custom domain
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Set it in Cloudflare Pages → *Custom domains*, then add a CNAME record pointing at
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`<project>.pages.dev`.
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## Local development
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The site is static — open `site/index.html` directly, or use `npm run dev` for a
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Cloudflare-compatible local server.
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## Updating the data
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1. `node scripts/refresh-evals.mjs` re-scrapes every model's benchmark scores from
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Artificial Analysis and rewrites `site/assets/evals.js`. Model names, OpenCode Go
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prices and free-tier flags come from `site/assets/data.js` (hand-maintained from the
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Go docs), so the chart always shows Go pricing.
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2. Descriptions, modalities, release dates and caveats live in `site/assets/data.js`;
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update them there and regenerate `MODELS.md`.
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3. Commit both files — CI publishes the site on push.
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## Caveats
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- Task-matrix cells use the best published evaluation per task family; when a model has
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not been run on a benchmark the column falls back to another one, so the underlying
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benchmark can differ between rows in a column. Hover a cell to see which one it is.
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- Free-tier models (MiniMax M3.1 Flash Free, Beam Free, LongCat 2.5 Preview Free) are
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limited-time offers.
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- Contributor-tier models (Gemini 4 Argon, Muse Spark 1.3) may use your prompts and
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completions for training — check the Go docs' privacy table.
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- No Go model generates images; they are all text-output.
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## License
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MIT — see [LICENSE](LICENSE).
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