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This book is a complete guide to understanding and building large language model inference engines in Rust. It takes you from the mathematical foundations of the transformer architecture through tokenization, attention mechanisms, KV caching, quantization, batching strategies, GPU and CPU optimization, distributed serving, and production deployment. Along the way, you will see idiomatic Rust code examples, performance benchmarks, comparisons with leading frameworks like vLLM, TGI, llama.cpp, Candle, Burn, and mistral.rs, and practical insights for shipping inference systems that rival the best open-source and commercial offerings. Whether you are a systems programmer interested in AI infrastructure or an ML engineer curious about the Rust ecosystem, this book gives you the depth to build, optimize, and understand.

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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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