You can transfer pre-computed context between different-sized models in the same family, cutting context processing time by 6-21x—useful when deploying multiple model sizes and reusing the same input across them.
ACCT enables reusing computed context (KV cache) across different LLM sizes within the same family, avoiding redundant computation when switching models. It transforms a source model's KV cache into sparse, compressed states that a smaller target model can directly use, achieving 6.5-21x speedup on context processing while maintaining performance.