laya-mlx plays Snake at 60 decisions per second on an M3 Max
介绍比Jev快50倍,在你设备上跑的laya-mlx! 只在你的设备上占用最高1G内存 Laya是一个开源的类似于Jev的,基于文本输出概率的分类系统 我将其移植到MLX,并且做了一些性能优化! 视频中就是这个模型在我的本地M3Max上玩贪吃蛇 这个模型能够以每秒决策60次的速度玩贪吃蛇!
Project: laya-mlx→The Laya project directory
Laya turns any text into typed decisions in milliseconds, on your own machine. Here is what it does, and 1045 projects people built with it.
Input text
“Hi, we were billed twice for March. Please refund the duplicate today or we will cancel our plan.”
laya-mlx · 146 input tokens · 0 output tokens
Which team should handle this ticket?
choiceHow urgent is this?
scoreDoes the customer threaten to cancel or leave?
yes / noDecided in 30.7 ms · 3 typed answers · one forward pass
Real outputs from Laya, not a mock-up. Run it yourself →
Seen on X this month
All demos →介绍比Jev快50倍,在你设备上跑的laya-mlx! 只在你的设备上占用最高1G内存 Laya是一个开源的类似于Jev的,基于文本输出概率的分类系统 我将其移植到MLX,并且做了一些性能优化! 视频中就是这个模型在我的本地M3Max上玩贪吃蛇 这个模型能够以每秒决策60次的速度玩贪吃蛇!
Project: laya-mlx→Local Laya moggs Jev at @grok 4.7-built Tetris 🧩 An open-weights System One model called Laya, beat cloud-based Jev at playing Tetris by making decisions 11 times faster, running locally on a 16GB MacBook Air! Run AI models locally ->
jev + opus 5.5... i simply can't comprehend why everyone isn't building this yet. in my workflow, this cut costs and time by ~80%. i think it's one of the best ways to use it. → pick relevant project notes before loading the context → route suitable tasks to a faster worker → choose a recovery path when a tool fails → run focused checks before the full test suite opus handles the hard reasoning. jev picks from options the harness prepares and validates. i explain how to build the decision layer in the article below:
This is NOT Jev. Open source. Runs on your laptop. Decides in ~27 ms, about 200× faster than waiting on a hosted LLM. Here it is playing Tetris by itself 👇
Thanks for the model, we were able to port Laya to coreml with 99.5% of the ops on ANE + benchmarked too. it is now blazing fast with 3.7 ms per decision on an M5 Pro. Release: Models:
Project: FluidUse→
He comes from a small village in Kasaragod, Kerala. In 2016, he was selected for IISER Mohali but couldn't afford to make the move. He eventually studied engineering at Government College of Engineering, Kannur. Last week he released Laya, an open-source AI model that challenged TypeSafe’s Jev on speed and on published decision-making scores. This is the story of Nandakishor M and how he built Laya.
laya-server
falk-werner
Serves Laya predictions through a local web server with prepared-question support
product_search_bench
Wanke15
Compares BM25, Jev, Qwen, and Laya for product search and reranking
LayaBOT
tomikan1208-code
Uses Laya decisions to control a Minecraft combat bot through Mineflayer
LayaMCP
GeneGulanesJr
Exposes Laya decision tools to MCP clients through an HTTP server
LayaWatch
BLANCO-11
Runs Laya in-process and provides a self-hosted console for traces, metrics, access control, and model management
laya-example
mkassaf
Demonstrates how to run the Laya typed-decision model with a minimal example
laya-ANE
vipuldivyanshu92
Ports Laya inference to Core ML for Apple devices, with a SwiftUI iPhone demonstration app
laya-multilingual-mlx
janvavrina
Provides a multilingual Laya model in MLX format
laya-t-rex-runner
10086ggqq
A browser-based T-Rex runner uses typed-decision models and distilled agents to choose actions
laya-ROCm
don-milsey-miller
Provides an AMD ROCm runtime and benchmarks for running the Laya decision model
layaagent
rotsl
Routes tasks through Laya classification and deterministic mediation to local or API-based coding agents
layad
rcwsr
Keeps the Laya decision model resident and serves it over HTTP with MLX or PyTorch
laya-vk
sulistta
Ports the Laya decision runtime to a Vulkan/IREE encoder backend for AMD and Qualcomm GPUs
rest-laya
wdonega
Serves the Laya model over REST with optional Jev-compatible endpoints for non-Python clients
laya-laravel
maeandrew
Adds a Laravel AI classification provider that sends typed questions to a self-hosted Laya server
ondevice-system1
Ahtsham0715
Develops smaller on-device typed-decision models derived from Laya, with training code and evaluations
laya-tictactoe
Kasa-Harendra
A terminal Tic-Tac-Toe demo runs the Laya model locally through Core ML on Apple Silicon
laya-mcp
WayneCommand
Wraps the Laya decision model in an MCP server and REST API for agent integrations
laya-mcp
YerikZ
Exposes Laya decision presets as MCP tools for coding agents
laya-onnx
Geoking2104
Runs Laya decision models with ONNX Runtime and provides export, inference, and benchmark tools
laya-test
jafs
Provides a web playground for testing Laya typed decisions on text or JSON
pi-laya
K0stIa
Adds typed-decision tools and session controls to Pi using a Laya-compatible service
laya-agent
ahmadfreijeh
A support-action agent combines a Python Laya prediction service with a Node.js customer-facing server
werewolf-laya
CallSohail
Runs a Werewolf game in which bots use Laya to score suspicions, choose intentions, and vote