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
laya-decision-brain
kevinbadi
Provides a web lab for Laya decisions on survey data and a Snake game
4·GitHub repo
laya-mlx-voice-browser
aryanbhujade
Uses a local Laya-MLX model to turn spoken commands into browser actions on Mac
4·GitHub repo
jev-chat-windows-laya
ZJemYoung
Adds an optional local Laya backend to a Windows WeChat chat assistant
4·GitHub repo
mjbrain
jinlio
Fine-tunes Laya into a real-time recommendation system for Japanese riichi mahjong
4·GitHub repo
laya-codex
pilotspace
Ranks repository code for Claude Code using the Laya re-ranker, hooks, and an MCP server
4·GitHub repo
T
laya-vision-demo
thaitea
Demonstrates calibrated image-based yes/no, choice and rubric decisions with Laya Vision
4·HF Space
A
laya-multilingual-demo
abhishekbhakat
Demonstrates multilingual Laya typed decisions and probabilities through a Gradio interface
4·HF Space
A
Laya
AXERA-TECH
Packages Laya checkpoints for deployment on AXERA AX650 and AX8850 NPUs
110·HF model
L
laya-grounded
Luni
Fine-tunes Laya to improve grounding, contradiction handling, and calibration
3·HF model
A
laya-multilingual-typed-decisions
alfred361
Fine-tunes the Laya multilingual model on a typed-decisions dataset
3·HF model
T
laya-onnx
techtheist
Provides quantized ONNX exports of English and multilingual Laya checkpoints
3·HF model
chunklaya
myxamediyar
Chunks long documents and uses Laya for typed-decision lookup across inputs up to one million tokens
3·GitHub repo
laya-pong
aovestdipaperino
Demonstrates Laya-driven paddle decisions in a browser Pong game
3·GitHub repo
laya-web
r4ai
Runs Laya typed-decision models in browsers and Node.js using ONNX Runtime Web
3·GitHub repo
zero-shot-ie-bench
umstek
Compares Laya and other zero-shot systems across information-extraction and classification tasks
3·GitHub repo
structured-decision-bench
zhengbangbo
Benchmarks structured decisions from Qwen3, Jev, and Laya CoreML
3·GitHub repo
runtime-tutorials
Runtime-weekly
Provides runnable Python guides for Laya classification and a comparison of Laya with other systems
3·GitHub repo
doomLaya
azalio
Trains and compares Laya and Jev agents playing FreeDoom with reproducible results
3·GitHub repo
Laya-Showcase
zamax14
Demonstrates and benchmarks multilingual Laya alongside Jev and GPT models
3·GitHub repo
decision-systems-bakeoff
actuallyrizzn
Runs a reproducible benchmark comparing Flybrain, Jev, and Laya on four public tests
3·GitHub repo
jev-as-quant
jiayylu
Combines Laya and Jev with Claude in a quantitative research stack and evaluates trading experiments
3·GitHub repo
Laya
ljw98
Provides a local web console and HTTP API for running Laya typed-decision models
3·GitHub repo
chinese-laya
yanqiangmiffy
Fine-tunes Laya multilingual for Chinese typed decisions and evaluates the resulting checkpoints
3·GitHub repo
fast-laya-compaction
ShinyDataTech
Uses local Laya decisions to compact agent context and provides filters, caching, and an MCP server
3·GitHub repo