TurboQuant: Revolutionizing LLM Efficiency with Near-Optimal Quantization

This exciting development introduces TurboQuant, a groundbreaking algorithm that significantly reduces the memory footprint of Large Language Models (LLMs) while maintaining impressive performance. By leveraging near-optimal 4-bit quantization with an 8-bit residual, this approach promises substantial memory savings and faster Inference. The benchmarks are looking very promising!