Chapter 16
16Quantization
16.1Bits, ranges, and where the memory goes
Planned: Why weights dominate memory; the appeal of fewer bits per weight.
16.2Post-training quantization
Planned: GPTQ, AWQ, and the outlier-feature problem; calibration data.
16.3Formats you'll meet: GGUF, bitsandbytes, MLX
Planned: What each is for; K-quants and mixed-precision schemes.
16.4Quantization-aware training and the frontier
Planned: QAT, 4-bit and below, and the accuracy cliff.