- Task matrix (12 task families x 23 Go models) from Artificial Analysis evals - Price/value scatter and value ranking - Model guide: what each model is targeted for (agentic, coding, data analysis, image understanding, research, free tier) with pricing and caveats - MODELS.md markdown version, README, MIT license - wrangler.toml + Gitea Actions workflow deploying site/ to Cloudflare Pages
3.8 KiB
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 — pricing, monthly allowances, privacy/retention, client support
- OpenCode Data — catalog metadata, context windows, usage and retention stats
- Artificial Analysis — 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
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)
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
- 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. - Catalog facts (pricing, context window, modalities, release date) come from
https://opencode.ai/data/<lab>/<model>.jsonand the Go docs. - Edit
site/assets/evals.jsandsite/assets/data.js, then regenerateMODELS.mdfromdata.jsand 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.