WebLLM WebLLM
WebLLM is a high-performance in-browser inference engine that enables large language models to run directly in web browsers without server-side processing. It leverages WebGPU for hardware acceleration, allowing applications to remain functional offline while ensuring user data privacy.
The project continues to maintain active development with version 0.2.84, featuring expanded model support for newer releases like Llama 3 and Phi 3.5, along with improved cache backend policies.
As of
- Hardware-accelerated in-browser inference using WebGPU
- Full compatibility with the OpenAI chat completion API
- Support for streaming, JSON-mode, and function-calling (WIP)
- Modular architecture with support for Web Workers and Service Workers
- Custom model support via MLC format
Privacy-first applications, offline-capable web tools, Chrome extensions, and interactive prototypes that require zero server infrastructure.
Applications requiring models larger than ~8B parameters due to browser memory limits, or projects targeting environments without robust WebGPU support.
WebLLM is an open-source library released under the Apache 2.0 license, meaning it is free to use with no per-token API costs.
WebLLM is a powerful, production-ready solution for developers looking to move AI inference to the client side, offering impressive performance that reaches approximately 80% of native speeds.
Is WebLLM free?
Yes - WebLLM is Open Source. WebLLM is an open-source library released under the Apache 2.0 license, meaning it is free to use with no per-token API costs.
What is WebLLM best for?
Privacy-first applications, offline-capable web tools, Chrome extensions, and interactive prototypes that require zero server infrastructure.
Who makes WebLLM?
WebLLM is developed by MLC AI. It is listed in the Hardware & Edge AI category on ai.dosa.dev.
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