Understanding KV Cache: The Hidden Memory Cost of Serving LLMs (opens in new tab)

A deep dive into KV cache — the hidden memory bottleneck of LLM inference. Learn how KV cache grows with context length and concurrency, why it matters for self-hosted models, and how attention innovations like GQA, MQA, MLA, sliding-window attention, hybrid architectures, quantization, PagedAttention, and prefix caching reduce memory pressure.