Built with Evals and benchmarks
laya-vs-jev
Laya vs Jev: local MLX and hosted AI decisions playing T-Rex side by side, with live metrics and replay recording
115 ★ on GitHub
What it is
Two AI decision models play Chrome's T-Rex game side by side: Laya runs locally on Apple Silicon through MLX, while Jev uses TypeSafe's hosted API. Watch their choices, response times, survival streaks, and crash replays on a shared obstacle course.
What the README says it does
- choice: probabilities over named options.
- score: probabilities over ordered rubric levels and their expected score.
- noul: P(true) for a proposition.
From the project’s README.
Getting started
From the README:
pip install laya-mlxWhere the decision sits
laya-vs-jev calls the hosted decision API rather than running its own weights. That keeps the project small and means its behaviour moves whenever the vendor ships a new model version. It also means an API key and a network round trip sit in the path of every decision.
Models it references: Jev, laya-typed-decisions, laya-mlx, laya-multilingual-mlx, laya-multilingual, laya-typed-decisions-mlx, laya-typed-decisions, laya.
How active it is
Created 2026-09-21, last pushed 2026-09-21, 115 stars and 12 forks when we read it on 2026-11-02. Everything in this category is weeks old at most, so a stale push date means something different here than it would on a mature project. Check the repository before you depend on it.
Find out what your data actually supports
We turn your historical decisions into a frozen test set, then tell you which model, which threshold, and how much of it you can safely automate.