Run Laya in the browser
Laya is small enough to run in a browser tab with no server and no API key. The input never leaves the page. The trade-off is a download of several hundred megabytes on the first visit and much slower inference than a native runtime.
171 projects
laya-bot-det
koteitan
Classifies Nostr authors as bots with Laya running in the browser
laya-mlx-wzq
smile-magic
A browser-based Gomoku game runs Laya-MLX locally to choose moves on Apple Silicon
laya-dev
AVMG20
A local HTTP server exposes Laya through a Jev-compatible API and includes a browser playground
laya-local
vit-cerny
Runs a browser agent using local Laya decisions or TypeSafe's hosted Jev backend
laya-email
sreekar2403
Tags Gmail messages locally with five Laya-powered classifications in one pass
lunar-laya
mraad
Runs Laya typed decisions on Apple MLX to guide a lunar-landing simulation
laya-curso
inematds
Teaches structured decisions with Laya and Jev through lessons, exercises, and practical projects
laya-flappy
cohenom
Uses the Laya model to vote on live game states in a flappy-bird-style physics game
laya-test
petrixh
Runs Laya as the decision-making pilot in a browser game with reproducible evaluations
laya-int8
koteitan
Provides an int8-quantized Laya Multilingual ONNX model split into downloadable parts
docker-laya-api
TheNerdMan
Packages the Laya decision model as a containerized HTTP API with an optional browser demo
lunar-mpc-laya
mraad
Pairs Laya with adaptive model-predictive control in a lunar lander decision game
laya-demo-web
sriramkasyap
Provides a browser playground for sending decision requests to a self-hosted Laya API
laya-snake-arena
sathwikkuncham
Compares local Laya and Jev decision engines in a configurable Snake arena
jev-laya-chess-bench
abe17124
Compares TypeSafe Jev and Laya in head-to-head chess games using legal moves
jev-laya-japanese-business-benchmark
snsk
Compares Jev and Laya on a Japanese business decision benchmark
ai-decision-lab
uibuckets
Provides a local playground and benchmark harness for Laya, with optional Jev comparisons
slop-finder
Code-Wizard-Wilson
Detects AI-like writing styles in social feeds using a local Laya-MLX helper
jev-zen
loongWoong
Reconstructs and validates Laya inference locally using NumPy and a browser-based interface
before-you-send
roisol144
Checks message tone, formality and fight risk while users type, using Laya decisions
mailaya
htpu
Uses a local Laya model to triage email, flag phishing, and check drafts in a browser extension
laya
iaeluk
Runs a local Laya-powered Snake game with a CUDA server and browser version
laya
Yahia-Raouf
Provides a self-hosted Laya inference API, key management, and an administration portal
laya-t-rex-runner
10086ggqq
A browser-based T-Rex runner uses typed-decision models and distilled agents to choose actions
Libraries
kevala is a zero-dependency Rust engine compiled to WebAssembly, with WebGPU kernels. It works from any page:
<script type="module">
import { Kevala } from "https://cdn.jsdelivr.net/npm/kevala@latest/js/src/index.js";
const kevala = await Kevala.load({ model: "laya", onProgress: console.log });
</script>
or pnpm add kevala. According to its README, the Laya int8 pack is 479 MB and is kept in browser storage after the first visit.
@r4ai/laya-web runs ONNX Runtime Web with WebGPU and a WebAssembly SIMD fallback, and is designed to run in a Web Worker:
npm install @r4ai/laya-web onnxruntime-web
Demos you can open
- layaForWeb: the English checkpoint as quantized ONNX (default build about 440 MB), with a live demo.
- open-jev-laya: multilingual Laya on Transformers.js (fp16 ONNX about 647 MB) with Gomoku, Big Two and a 3D maze.
- layaAsRagJudge: checks RAG claims against retrieved evidence entirely in the tab.
Speed and support
The layaForWeb README reports that a three-question call on the default WASM backend took about 2 to 5 seconds on a 2-core machine. In that project, WebGPU works only with the int4 build, because ONNX Runtime's WebGPU MatMulNBits kernel supports 2- and 4-bit weights. open-jev-laya tries WebGPU and falls back to WebAssembly.
Caveats
Quantized browser builds do not match PyTorch exactly. layaForWeb reports 97.9% top-answer agreement for all three of its quantized builds, with the largest probability gaps in int4. For a real-time loop, laya-pong keeps the model native. Its README gives the reason: the checkpoint wants about 2.4 GB resident in f32, and wasm32 has a 4 GB address space and no Metal.
More ways to use Laya