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
Everything the world is building on Laya.
Laya turns any text into typed decisions in milliseconds, on your own machine. Here is what it does, and 952 projects people built with it.
real run · laya-mlx
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?
choice✓ billing98%
technical1%
sales1%
How urgent is this?
scorenot urgent4%
soon15%
✓ blocking81%
Does the customer threaten to cancel or leave?
yes / no✓ yes84%
no16%
Decided in 30.7 ms · 3 typed answers · one forward pass
Real outputs from Laya, not a mock-up. Run it yourself →
- Projects
- 952
- New this week
- 952
- Platforms
- 18
Seen on X this month
All demos →
Local Laya beats Jev at Tetris on a MacBook Air
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 decision layer routes tasks and recovers from tool failures
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:
Laya plays Tetris locally with decisions in about 27 milliseconds
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 👇
laya-coreml runs 99.5% of operations on ANE at 3.7 ms per decision
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→A step-by-step Jev build guide with code and architecture
everything you need to start building with jev, in one article. code, architecture, diagrams... everything you need to follow the build and make it your own.
Directory
+ Submit yours
pi-laya-router
AdelysAlberto
Routes Pi coding-agent prompts using local Laya classification on Apple Silicon
2·GitHub repo
laya-router-skill
wangmiaozero
Adds local Laya decision routing to coding agents through skills and MCP
2·GitHub repo
laya-snake-k3
JiongLab
Runs an offline Laya-powered Snake game on SpaceMIT K3 using ONNX and AI Core
2·GitHub repo
JevCoreML
GodModeAI2025
Provides Core ML decision models, a Swift package, an HTTP server, and a demo app
2·GitHub repo
auto-mode-for-paseo
obetomuniz
Routes Paseo messages to personas using TypeSafe Jev or a local Laya model
2·GitHub repo
laya-jev-api
smallnest
Serves local Laya Core ML inference through a Jev-compatible HTTP API
2·GitHub repo
laya.axera
AXERA-TECH
Exports and calibrates Laya models for AXERA NPU deployment
2·GitHub repo
laya-serve
stiermid
Serves local Laya decision models through a Jev-compatible HTTP API
2·GitHub repo
openzl-laya
madeye
Adds optional on-device Laya routing to OpenZL compression on Linux and macOS
2·GitHub repo
laya-windows
Zuhair-01
Ports Laya typed-decision inference to Windows using ONNX Runtime and DirectML
2·GitHub repo
laya-cli
MIt9
A CLI runs Laya typed decisions with batch, routing, and resident-daemon modes
2·GitHub repo
laya-search
giaphutran12
Searches YC companies using local Laya inference or the TypeSafe Jev API
2·GitHub repo
laya-as-judge
rbrus
Uses Laya-MLX to evaluate models and agents with typed-decision judgments
2·GitHub repo
laya-vs-jev
zaferayan
Benchmarks multilingual Laya against hosted Jev across 900 cases, three tasks, and six languages
2·GitHub repo
Decis
chaitin
Serves open decision models through a self-hosted TypeSafe System One API
2·GitHub repo
stuntdouble
ReallyArtificial
Proxies Jev requests to local decision models and compares their answers on recorded traffic
2·GitHub repo
mac-attack
dockndevai
A macOS app uses Laya decisions to direct harmless effects in a camera-based screensaver game
2·GitHub repo
laya-cuda
Alexw1111
Provides a lightweight CUDA inference library for Laya
2·GitHub repo
laya-rs
Fanaperana
Reimplements Laya in Rust for zero-shot text classification with verified numerical parity
2·GitHub repo
laya-demo
almodover
A local web app analyzes text and ebooks across 82 dimensions using Laya
2·GitHub repo
SnakeGame_Laya
Okbatti
Uses a fine-tuned Laya model to choose moves in a Snake game
2·GitHub repo
oh-my-laya
leo1394
Installs local Laya tools for classification, scoring, and routing in coding agents
2·GitHub repo
laya-cpu-benchmark
taiheqi718-art
Measures steady-state CPU latency for the multilingual Laya model
2·GitHub repo
laya-ternary-lite
xixi3548942758-design
Quantizes Laya to ternary weights for smaller, lower-memory inference
2·GitHub repo