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.
361 projects
laya-ultrafast
ipenywis
Runs a browser automation agent using local Laya decisions through MLX
laya-playground
wdobry
A local website combines Laya model demos, games, a benchmark, and an agent skill
laya-pilot
anthonyli
Generates and replays Excel browser tests using Playwright and local Laya decisions
laya-browser
cklxx
Fine-tunes Laya as a browser-agent decision head for web navigation
laya-vs-jev-arena
PromptEngineer48
Pits locally run Laya against Jev in Snake and fighting games
layaForWeb
vishalmysore
Runs a quantized ONNX version of the Laya decision model entirely in the browser
open-jev-laya
killkli
Runs Laya multilingual ONNX inference in browser-based decision demos
laya-mind2web-browser-agent
ShaunSpark
Fine-tunes Laya on Mind2Web for browser automation decisions
zlaya
dip-proto
Runs Laya inference locally in Zig, including native and WebAssembly targets
kevala
bvolpato
A Rust WebAssembly engine runs Laya and other decision models locally in browsers
layaForWorkflows
vishalmysore
Runs browser-based Laya decisions to automate branching workflows
laya-multilingual-ONNX
onnx-community
Provides an ONNX conversion of Laya multilingual for use with Transformers.js
deqio
ILuce
Serves multiple typed-decision models, including Laya, through a local API and browser UI
laya-plays-google-snake
Makankn
Controls the real Google Snake game using Laya decisions and visual tracking
laya-multilingual-onnx
mizchi
Exports multilingual Laya to ONNX for native and browser WebGPU inference
laya-pong
aovestdipaperino
Demonstrates Laya-driven paddle decisions in a browser Pong game
laya-mlx-voice-browser
aryanbhujade
Uses a local Laya-MLX model to turn spoken commands into browser actions on Mac
Ollaya-Web-UI
samarkandiy
Provides a browser interface for deciding questions and managing models on an Ollaya server
traffic-solver-laya-
alipyth
Simulates city traffic controlled by Laya and includes a model playground and tutorial
vegaml
NandhaKishorM
Produces calibrated typed decisions from frozen language models with conformal sets and abstention
laya-onnx
gqgs
Exports the Laya model to quantized ONNX for browser inference
kevin
gauravsaini
Runs a browser automation agent that uses Laya-ONNX to rank candidate actions
laya-web
r4ai
Runs Laya typed-decision models in browsers and Node.js using ONNX Runtime Web
zero-shot-ie-bench
umstek
Compares Laya and other zero-shot systems across information-extraction and classification tasks
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