Technique

KV Cache Quantization

Quantising attention keys/values to INT8 or INT4 to shrink KV-cache memory.

Definition

Since the KV cache dominates LLM inference memory, quantising it to 8-bit or 4-bit per element lets servers fit much longer contexts or more concurrent users. Modern engines (vLLM, TRT-LLM) support FP8 and INT4 KV cache with negligible quality loss.

Common use cases

  • Long-context serving
  • Multi-tenant inference
  • Memory savings

Related terms

    KV Cache Quantization — AI Glossary | Railwail