Story · vLLM Blog
vLLM x AgentX: Optimizing for Real-World Agentic Serving (vLLM Blog)
vLLM walks through KV cache management, parallelism, scheduling and prefill/decode disaggregation for agent traffic, and reports up to 130K tokens per GPU-second on SemiAnalysis AgentX plus a 14.6x to 106x serving-cost advantage over Opus 5. Those are the project's own numbers.
In plain words
- A software team explained how it runs artificial intelligence systems that carry out tasks while keeping computing costs down.
- The software reuses saved information from earlier processing.
- It separates the work of reading requests from the work of producing answers.
- The team reports lower computing costs than Opus 5 for companies running these tasks, based on its own tests.
Appeared in
- Per-phase model routing cuts agent cost, RASER on Slurm, Amp steers mid-run
Sep 09, 2026 · in the sections
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