AI · 1h ago
KV-Cache: The Optimization That Makes LLM Chat Feasible
The KV-cache stores key-value pairs from previous tokens, reducing LLM generation from quadratic to linear time. Without it, each new token would recompute all prior tokens' representations. This optimization splits inference into a compute-heavy prefill phase and a cheap decode phase, enabling real-time chat.
Meridian48 take
The article correctly identifies KV-cache as critical, but understates the memory bottleneck it creates for long-context models—a tradeoff that limits deployment scale.
llm-inferencekv-cache