Quantization formats

A format is an algorithm, not a bit count. It fixes how many weights share a scale, whether an offset is stored alongside it, and whether important weights are protected from rounding. Q8_0 is effectively lossless, is the llama.cpp default at roughly 0.8 percent perplexity cost, and AWQ and GPTQ target rather than local files. Formats below 3 bits only hold up on a large model or on weights trained at that precision from the start.

Formula

Worked example: Qwen3-32B in Q4_K_M

The bartowski Q4_K_M build measures 19,762,149,696 bytes and costs about 0.8 percent perplexity against full precision. Weigh that against Q3, where the loss stops being a rounding argument and starts being visible in the output.

Try Q4_K_M on a current 27B model