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• The paper introduces the first unified mathematical model that captures the core trade-offs between KV cache eviction and query routing.method 95%
• The default Least Recently Used (LRU) eviction algorithm struggles with dynamic online query arrivals in multi-LLM serving scenarios.limitation 90%
• The proposed approach achieves up to a 6.92× improvement in cache hit rate over state-of-the-art methods.result 95%
• The proposed approach achieves up to a 77.4% increase in throughput over state-of-the-art methods.result 95%
• The algorithm combines provably competitive randomized KV cache eviction with learning-based methods to adaptively route queries.method 90%
• Performance improvements were validated across 4 benchmarks and 3 prefix-sharing settings.result 95%
• The algorithm's performance largely depends on specific workload characteristics, and edge cases may exist where traditional methods perform better.limitation 85%
• Balancing query load across workers and maximizing cache hit rate of each worker are inherently conflicting objectives in multi-LLM serving scenarios.technical 85%

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