Top 10 KV Cache Compression Techniques for LLM Inference: Reducing Memory Overhead Across Eviction, Quantization, and Low-Rank Methods

A review of ten recent methods maps out KV cache compression for LLM inference, from eviction and streaming to prefill, layer-wise, quantization, and low-rank approaches.

The article explains how these techniques are used in production pipelines and where each one fits best.

By shrinking KV cache growth, the methods can ease GPU memory pressure, support larger batches, and speed up inference for long-context models without retraining.