What Is the KV Cache? A Complete Guide to How LLM Inference Reuses Key-Value Tensors, Its Quadratic-to-Linear Speedup, and How It Differs from Prompt Caching
The KV Cache is the optimization that turns Transformer LLM inference from quadratic to linear by reusing computed Key and Value tensors. Learn how it works, its memory cost, and how it relates to Prompt Caching, PagedAttention, and vLLM.


































