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TLAPS-Bench website

Static site for the TLAPS Proof Benchmark.

The published leaderboard is Proof Completion Core only: every model is graded on the same task list in results/core-manifest.json (currently 190 proof-completion tasks). Proof-from-scratch and Full-suite runs are not shown.

A bundle is published only when it covers that Core set exactly. Older Full-suite dumps that omit Apalache (ben-or83, tendermint) or other Core tasks cannot appear on the leaderboard, even if they were produced this week — their numbers would not be comparable.

Scoring

The leaderboard's primary score is the Spec-balanced pass rate: calculate the task pass rate within each Core specification, then average those rates so every specification has equal weight. The table also reports tasks passed and specifications completed as supporting counts.

Run locally

python3 -m http.server 8000

Then open http://localhost:8000

Edit

  • Model runs live in results/<backend-id>.json (must cover the Core task set exactly).
  • The Core task list lives in results/core-manifest.json.
  • Page copy lives in scripts/site-content.mjs.

Install the build dependencies once:

npm install

After changing results, content, or JSX, rebuild:

npm run build

Use node scripts/build-data.mjs --check to validate the generated data without rewriting data.js.

Updating the Core

When the Core task set changes:

  1. Drop a complete Core result bundle into results/.
  2. Regenerate the manifest:
node scripts/sync-core-manifest.mjs results/<that-bundle>.json
  1. Replace every published model run so each covers the new Core exactly (same benchmarks, theorems, and sources).
  2. Rebuild and bump the ?v= cache-buster on data.js in index.html.

Adding a model

  1. Drop the run into results/<backend-id>.json with meta.backend set to that id, meta.cohort of one-shot or agentic, current meta.scoring, complete usage and equivalent-price data, and results for every Core task.
  2. Add a BACKEND_INFO entry in scripts/build-data.mjs and list the id in PUBLISHED_BACKENDS.
  3. Add the model's public pricing source to PRICE_SOURCE_BY_MODEL.
  4. Rebuild, then bump the ?v= cache-buster on data.js in index.html.

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