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This book teaches you how to make modern language models run on extremely constrained devices: microcontrollers with kilobytes of RAM, single-board computers with gigabytes, and mobile chips with NPUs. It is a practical engineering handbook for systems programmers who want to deploy LLM inference entirely offline on real hardware. You will learn the physics of why LLM inference is hard on small devices, the mathematics of transformer computation, the techniques for shrinking and accelerating models, the architecture of inference runtimes, and the skills needed to benchmark, debug, and deploy working systems. Every chapter builds on the previous one, culminating in complete case studies that show you how to design and implement an on-device LLM system from scratch.

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Kick off your book project, get started with GhostAI, get better at marketing, or spend the day doing all three! Free live workshops on Zoom. Saturday, June 27, 2026.

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