ArtifactArena: Evaluating Models by What They Build in the Physical World

Abstract:To evaluate the frontier, we must measure models not by what they say, but by what they can engineer and build in grounded physical environments. We introduce \textsc{ArtifactArena}, an open-ended platform where models face a physically grounded hardware-software co-design challenge: engineering fully functional robots to compete in a simulated arena. We evaluate a frontier model's zero-shot, verifier guided refinement, and open-ended physical design capabilities through three harnesses that refine their bot artifacts based on text descriptions, physics simulator feedback, and gameplay data. We benchmark these capabilities with an Elo ranking of frontier models derived from head-to-head tournaments between their artifacts. By releasing this framework and tournament infrastructure for ongoing community submissions, we establish a living, non-saturating testbed to continuously measure the expanding limits of open-ended intelligence in the physical world. Please visit \href{this https URL}{this https URL} for more information.

Robotics (cs.RO); Artificial Intelligence (cs.AI)

arXiv:2610.06511 [cs.RO]

(or arXiv:2610.06511v1 [cs.RO] for this version)

https://doi.org/10.48550/arXiv.2610.06511 Focus to learn more arXiv-issued DOI via DataCite (pending registration)

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