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MLC | WebLLM: A High-Performance In-Browser LLM Inference Engine

blog.mlc.ai · 1,757 words · saved by 1 readers

We are in an exciting year of generative AI. Open large language models bring significant opportunities to offer customization and domain-specific deployments. While most LLMs run on servers/cloud, there are promising opportunities for running capable models locally. Web browsers form a universally accessible platform, allowing users to effortlessly engage with any web applications without installation processes. Wouldn’t it be amazing to bring open language models directly into browsers, enabling anyone to run LLMs locally just by opening a webpage? In this post, we introduce the WebLLM engine (WebLLM for short), a high-performance in-browser LLM inference engine. WebLLM engine is a new chapter of the MLC-LLM project, providing a specialized web backend of MLCEngine, and offering efficient LLM inference in the browser with local GPU acceleration. WebLLM is fast (native GPU acceleration), private (100% client-side computation), and convenient (zero environment setup). The figure below

MLC | WebLLM: A High-Performance In-Browser LLM Inference Engine --> Home WebLLM: A High-Performance In-Browser LLM Inference Engine Jun 13, 2024 • MLC Community Introduction We are in an exciting year of generative AI. Open large language models bring significant opportunities to offer customization and domain-specific deployments. While most LLMs run on servers/cloud, there are promising opportunities for running capable models locally. Web browsers form a universally accessible platform, allowing users to effortlessly engage with any web applications without installation processes. Wouldn’t

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