Agent traffic is a strange inference workload: long prefix caching beats raw tokens per second
rohanpaul_ai · x · 2026-10-14
At DigitalOcean's Open Intelligence Summit, Yifan Qiao of Inferact presented on running vLLM for agentic production workloads.
Key point: agent traffic is an unusual workload for inference servers — every turn resends a long, nearly identical prefix (system prompt, tool schemas, conversation history) and gets back only a short tool call.
This shape makes prefix caching and KV-cache reuse matter more for agents than raw tokens per second. A cache miss on a long prefix means paying for the full prefill again on every turn of a long task.
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