CacheOPT is a novel system designed to optimize LLM inference by addressing KV-cache bottlenecks that cause slow response times and poor user experience.

• Mitigates competition for KV cache resources between requests
• Intelligently prioritizes requests to meet both Time-to-First-Token (TTFT) and Time-Between-Tokens (TBT) performance goals
• Provides significant improvements in tail latency for time-sensitive LLM applications
• Enhances overall system efficiency without requiring hardware upgrades

This research matters because it directly addresses performance challenges in production LLM systems, allowing developers to deliver more responsive AI applications with existing resources.

Mitigating KV Cache Competition to Enhance User Experience in LLM Inference