KV Cache Compression 900000x Beyond TurboQuant and Per-Vector Shannon Limit
Researchers have developed a KV cache compression method that achieves 900,000x compression beyond TurboQuant and approaches the per-vector Shannon limit. This breakthrough significantly reduces memory requirements for large language models while maintaining performance.