NVIDIA AVO Reaches 100% on ARC-AGI-3, Demonstrating a Frontier-Level General-Purpose Architecture for Long-Horizon Autonomous Agents | NVIDIA Technical Blog

This post introduces the NVIDIA Agentic Variation Operators (AVO) architecture, a general-purpose agent system designed for sustained autonomous operation across long horizons. It details AVO's application to GPU-kernel optimization, where it achieved significant performance gains over existing methods by autonomously exploring and refining kernels. The post then describes the adaptation of the same AVO architecture to the ARC-AGI-3 interactive reasoning benchmark, where it achieved a 100.00 RHAE score. Key contributions include demonstrating that long-horizon capability emerges from the full agent system (memory, tools, feedback, recovery) rather than solely from model capability, and highlighting the transferability of the core agent loop across different domains (software engineering and interactive reasoning). The post emphasizes the importance of persistent memory and supervision for maintaining progress and adapting strategies.