2026
NanoQuant: Efficient Sub-1-bit Quantization of Large Language Models
ICML 2026poster
Weight-only quantization has become a standard approach for efficiently serving large language models (LLMs). However, existing methods fail to efficiently compress models to binary (1-bit), as they either require large amounts of data and compute or incur additional storage. In this work, we propos…