推論系統
Yutori Reveals Browser Agent Inference Architecture: 100K-Token Inputs, Short Tool Outputs, and Prefix Caching to Reduce Per-Step Costs
Yutori’s Navigator calls a vision-language model dozens of times during each browser task, with historical context growing to roughly 100K tokens. Together AI handles this workload using vLLM prefix caching and separate latency targets, although the claimed 2× speedup and 4–5× lower cost remain vendor-reported comparison results.