NVIDIA's AVO Hits 100 on ARC-AGI-3, Uses 12% Fewer Actions

NVIDIA says its new coding agent cleared every level of the ARC-AGI-3 public set.

In a blog post dated August 21, NVIDIA reports that the system, called Agentic Variation Operators (AVO), scored 100.00 RHAE across all 183 levels in the benchmark's 25 environments. On the same task, running the same Claude Opus 5 backbone, VISTA used 7,542 environment actions to AVO's 6,624, a roughly 12% reduction. Claude Opus 5 by itself reportedly reaches 30% at high reasoning effort.

"A frontier language model is only one component of an AI agent," the authors write. "The surrounding agent system… determines how the model receives context, uses tools, maintains state, responds to feedback, recovers from failure, and sustains progress over long-running tasks."

The harness, as the post describes it, has three pieces: a persistent memory that carries implementations and reasoning between attempts, a supervision loop that flags stagnation, and an agent loop that inspects, plans, implements, and evaluates. Similar scaffolding claims have run through our agents coverage all summer.

The team also applied AVO to GPU-kernel optimization, reporting 40 committed kernel versions from more than 500 explored directions over seven days, with the best beating FlashAttention-4 by up to 10.5% on DGX B200 systems. The post is credited to NVIDIA principal engineer Terry Chen along with Jean-Francois Puget and Humphrey Shi, the company's VP of High-Performance AI, among the co-authors.

The framing is blunt. "The model matters, but the model is not the entire agent."