Native MLX runtime for Laya typed decision models — 7–14 ms short decisions on M3 Max. No text generation, PyTorch, or cloud API.
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Updated
Sep 22, 2026 - Python
Native MLX runtime for Laya typed decision models — 7–14 ms short decisions on M3 Max. No text generation, PyTorch, or cloud API.
Local Laya typed decisions on Apple Core ML and Neural Engine. Validated ports, ~5 ms short decisions on M3 Max, reproducible speed and energy benchmarks.
An open-source toolbox that takes a game all the way "from idea → built → live" — Unity/Godot/Cocos/Laya clients + one .NET server. | 开源游戏全流程工具箱:Unity/Godot/Cocos/Laya 客户端 + .NET 服务器,从想法到上线一站搞定。
laya3.x引擎 + nodejs 开发的网络麻将,省去了大量复杂配置,极其适合上手
基于Typescript的渐进式通用游戏前端开发框架
A website, two games, a benchmark and an agent skill for Laya, the open-source decision model. Runs on your machine.
System 1 decision models (Jev, Laya, Cua-S1) as brain for agents: Browser use, computer use, games and robotics
Generate replayable Excel test cases from live browser pages, or run existing Excel cases, using Playwright and local Laya or a compatible decision API.
System One compatible API for open decision models, written in Rust.
Dohnuts builds small multimodal models for direct decisions. -> System One model
Local proxy that learns your app's typed LLM decisions and answers them with a Laya head. Jev and OpenAI compatible.
Agentic GraphRAG engine using swappable System One decision models (local Laya / cloud Jev). Features a complete 4-phase pipeline (Ingestion, Pre-Retrieval, Traversal, Post-Retrieval) and evaluation across Neo4j, Memgraph, Apache AGE, and Kùzu driven by a custom A* traversal algorithm.
Run Jev-style typed decisions locally on your Mac with low RAM usage and fast responses
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