vLLM's agentic serving deep-dive: DeepSeek V4 Pro hits 83K tok/GPU-s at 106x lower cost than Opus 5

vllm_project · x · 2026-09-09

vLLM published a full-stack optimization deep-dive for agentic inference workloads, measured on SemiAnalysis's public AgentX benchmark.

What agent traffic looks like (from real coding-agent traces): median 43 turns per session; 142K-token median input vs. 444-token median output; 96%+ prefix-cache hit rate; 44% of sessions fork subagents — long prefixes, tiny outputs, constant reuse.

Key optimizations:

The economics: DeepSeek V4 Pro sustains 83K tokens per GPU-second under a strict p90 SLO of 50+ tok/s per user (130K at the frontier), while serving the same workload on Opus 5 at the same cache-hit rate costs 106x more — a measure of how much headroom open-weight models have when the stack is tuned for them.

Related event: vLLM Unveils AgentX Benchmark: Up to 106x Cost Advantage for Real-World Agentic Serving(5 posts)→

Original post →

More from coding & agent

coding & agent channel →