NVIDIA's AgentBaton: Well-Timed Strong-to-Weak Model Handoffs Slash Agent Costs
nvidia · hf · 2026-11-09
A NVIDIA-led paper, AgentBaton, studies how capable and efficient models can collaborate within a single long-horizon agentic task.
- Key finding: efficient-to-capable handoffs generally underperform capable-only execution with little cost reduction, while capable-to-efficient handoffs at suitable task stages preserve or even improve accuracy while substantially cutting cost.
- A lightweight detector decides handoff timing, achieving large API cost savings and extending the accuracy-cost Pareto frontier.
- The paper systematically examines handoff direction and context transfer design choices.
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