№ 01entry — browser AI lab

AI that never leaves your tab.

Local inference, client-side RAG, and voice agents — running on your GPU, on this page, right now. No cloud, no API keys.

$ webml check-runtime

  • webgpu
  • threads
  • memory·
  • model cache
  • servers0 — it all runs in this tab

What this is

WebML is a personal lab for browser-based AI. Embeddings, inference, RAG — running locally, without servers. Driven by curiosity, shipped in public.

  • Local-first

    AI that runs on your device. Models loaded once, executed entirely in the browser tab.

  • Privacy-native

    No data leaves the browser. No telemetry. No API keys. Your input stays yours.

  • Open lab

    Experiments built in public. Source available, ideas welcome, nothing gated.

Live on this page

Talk to this site.

The floating mic in the corner is a full voice agent: speech recognition, an 8B-parameter planner, and text-to-speech — three models in three Web Workers, all in this tab. Say “open the playground” and watch it navigate.

Nothing downloads until you tap the mic and confirm. Roughly 1.6 GB of weights, cached after the first run. Desktop Chrome or Edge with WebGPU.

Read how it's built

FAQ

Common questions

The short version of what this lab is about.

What is WebML?

WebML (webml.ai) is a browser AI lab that runs machine learning models entirely in the browser using WebGPU, ONNX Runtime Web, and Transformers.js — with no server, no API key, and no cloud required. It includes live experiments, articles, and an interactive playground.

What is browser-native AI?

Browser-native AI runs inference directly inside a web browser using WebGPU compute shaders and WebAssembly. Models execute on the user's device GPU or CPU, with no data leaving the browser — enabling privacy-first, offline-capable AI applications.

What technologies does WebML use?

WebML experiments use Transformers.js (Hugging Face), WebLLM (MLC-AI), ONNX Runtime Web, Chrome's built-in Prompt API (Gemini Nano), Web Workers for threading, AudioWorklet for audio processing, and WebGPU for GPU-accelerated inference.

Does WebML work offline?

Yes. Once model weights are downloaded and cached via the Cache API or Origin Private File System (OPFS), all inference runs locally with no network connection needed.

Omri Beladev

The person behind this

Omri Beladev

Engineer, CTF player, and browser AI experimenter. I build WebML to explore what's possible when AI runs locally — no cloud, no dependencies, just the browser and what it can do.

Tap the mic to load the voice agent