Luce KVFlash is a memory-efficient optimization enabling 256K context windows using only 72 MiB of KV cache on the GPU. It reduces memory consumption for long-sequence inference by compressing key-value cache storage.
KV cache compression techniques, including Multi-Query Attention (MQA), Grouped-Query Attention (GQA), Multi-head Latent Attention (MLA), and linear-attention hybrids, have evolved to reduce memory overhead in large language models. These developments have quietly enabled the long context windows required for modern agentic LLM applications by making key-value caching more efficient.