Modular: The Five Eras of KVCache — KV cache evolution from contiguous tensors to distributed inference

AI Impact Summary

KVCache evolution has shifted from naive contiguous tensors to sophisticated techniques like PagedAttention and now heterogeneous caches tailored to multimodal models and hybrid architectures. This Era 0-3 progression reflects the increasing complexity of LLMs, with each iteration introducing new state management requirements and optimization challenges. The shift to distributed KV caches represents a necessary scaling solution for modern LLM serving, but introduces significant operational complexity around fragmentation, load balancing, and data transfer.