Toolorchestra Achieves 35.1% Higher Accuracy And 2.5x Efficiency Via Efficient Model And Tool Orchestration

NVIDIA AI Releases Orchestrator-8B: A Reinforcement Learning Trained Controller for Efficient Tool and Model Selection

How can an AI system learn to pick the right model or tool for each step of a task instead of always relying on one large model for everything? NVIDIA researchers release ToolOrchestra, a novel method for training a small language model to act as the orchestrator- the ‘brain’ of a heterogeneous tool-use agent https://arxiv.org/pdf/2511.21689 From Single Model Agents to an Orchestration Policy Most current agents follow a simple pattern. A singl…

Toolorchestra Achieves 35.1% Higher Accuracy And 2.5x Efficiency Via Efficient Model And Tool Orchestration

Researchers have developed a new artificial intelligence system, ToolOrchestra, that outperforms larger models like GPT-5 on complex reasoning tasks while significantly reducing computational costs by strategically coordinating a diverse set of specialized tools.