NVIDIA 的 Vera Rubin NVL72 在 AI 智能体应用中实现了高达 30 倍的单位功率工作量提升。该系统应对了智能体工作负载消耗令牌量是简单聊天请求 15 倍的挑战，这是由于数据库查询和子智能体调用等活动所导致的。

According to OpenRouter data, agentic AI workloads consume 15x more tokens than a simple chat request. Why? Consider what happens when an AI agent researches a company for an investment decision. The agent queries financial databases, searches news and filings, invokes a sub-agent to run peer comparisons and model valuations, then synthesizes everything into a […]