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Quantization from the ground up

L4 · DeveloperTutorials & GuidesSimon Willison's Blog· 3/26/2026

Developers optimizing model inference costs and edge deployment need to understand quantization trade-offs; this distills complex concepts with interactive visualization and real benchmark data.

AI Summary

Simon Willison curates an in-depth interactive essay by Sam Rose explaining of Large Language Models from first principles, covering floating-point representation, outlier preservation, and empirical accuracy impacts (8-bit ~no penalty, 4-bit ~90% quality). Includes visual explanations and benchmarks using Qwen 3.5 9B.

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