analiza aiqbench

Nvidia's research demonstrates that for long-horizon agentic tasks, the architectural framework—specifically memory management and supervisor components—is more critical than the underlying model's raw capability. This finding shifts focus from chasing larger parameters to optimizing the scaffolding, tools, and runtime environments that enable reliable multi-step reasoning. Consequently, developers should prioritize refining their harness designs over selecting marginally better base models to achieve high performance in complex workflows.