Does Quantization Speed Up Inference? A Practical Guide

What this post added

This post introduces and explains model quantization as a technique to speed up AI inference. It details the process of reducing numerical precision of model weights (e.g., from FP32 to FP16, INT8, or INT4) and explains the mechanisms by which this leads to faster math, less memory movement, and smaller model footprints. The post also discusses the trade-offs in terms of accuracy loss for different quantization levels and hardware support, and positions quantization as one of several inference optimization strategies.