Quantization hurts knowledge nonlinearly
SMRTR summary
Quantizing AI models saves storage space, but a new analysis of 55 quantizations of Qwen3.6 27B reveals that factual knowledge degrades nonlinearly. Models compressed to 5-bit or higher retain full quality, but 3-bit and 2-bit versions lose obscure knowledge rapidly, while general reasoning abilities remain mostly intact.
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