webllm

Running language models directly in the browser, no server round trips, using WebGPU for hardware acceleration and in-browser inference engines. Content here covers loading quantized models client-side, managing memory and download budgets, and building private applications where prompts stay on the user's device. Expect practical notes on performance tradeoffs, model selection for browser constraints, and shipping zero-cost inference to end users.