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WebLLM

High-performance in-browser LLM inference engine that leverages WebGPU for hardware-accelerated, privacy-preserving inference in the browser.

Overview

WebLLM is a high-performance in-browser language model inference engine that uses WebGPU to run LLM inference directly in web browsers without server-side processing, enabling privacy-preserving deployments and low-latency experiences.

Key Features

  • In-browser inference with WebGPU acceleration.
  • OpenAI API compatibility with streaming, JSON-mode, and experimental function calling support.
  • Support for multiple prebuilt models and easy custom model integration.

Use Cases

  • Privacy-focused chat assistants and browser-based AI tools.
  • Reducing backend costs and latency by moving inference to the client.
  • Education, demos, and rapid prototyping using CDN or npm integration.

Technical Highlights

  • WebAssembly + WebGPU for efficient inference and streaming generation.
  • WebWorker/ServiceWorker support for offloading computation and keeping UI responsive.
  • Modular NPM/ CDN usage with extensive examples for quick integration.

Comments

WebLLM
Resource Info
🧬 LLM 🚀 Deployment 🌱 Open Source