Intel drops AutoRound to make 2-bit quantization actually usable
Intel just detailed AutoRound, a post-training quantization tool designed for LLMs and vision-language models. By optimizing weight rounding and clipping ranges together, it boosts relative accuracy at INT2 by up to 2.1x over popular baselines. Quantizing a 72B model takes just 37 minutes, with direct exports to GPTQ, AWQ, and GGUF.