arXiv: cs.AI preprintsInternational11 November 2026
Bursts That Outlast Themselves: Persistent Degradation in Prefix-Cached Agent Serving
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arXiv:2611.13412v1 Announce Type: cross Abstract: LLM agents drive inference engines with closed-loop sessions whose context grows every turn, and serving them economically depends on prefix caching: a hit costs an incremental prefill of about a thousand tokens, a miss recomputes a 10--40K-token context. We show that this makes prefix-cached agent serving metastable. With an identical base workload, a few minutes of extra arrivals leaves a vLLM server in a degraded regime--a ~10% hit ratio, about half the throughput, and a backlog that grows for the remaining 70 minutes--while its no-burst twi
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