local-ai

Running language models on your own hardware instead of calling remote APIs, covering everything from browser-based inference with WebGPU and WebLLM to desktop and edge deployments. Content here digs into the practical tradeoffs: model size versus quality, hardware requirements, privacy gains when prompts never leave the device, and the cost math of local compute versus cloud tokens. Expect hands-on setups and honest looks at what actually runs well offline.

Before you go...

Get our best AI insights delivered straight to your inbox. No spam, we promise.