About

dig.bench is a benchmark of scientific discovery.

Each of its 70 games measures whether an agent can experiment to discover that game's own unknown rules. Every game is text-based, which puts it in the natural domain of language models: no visual confounds stand between a model and the discovery, so what dig.bench tests is discovery alone. Humans and frontier models play the same games with access to the same information, and progress is scored by whether the game can be beaten within a limited number of steps.

The games come in 7 tiers, depending on their difficulty. No game is easy and they all require effortful play, but humans can make the discoveries necessary to solve even our hardest games, while the best models struggle to beat games in the top tier.

Scale

70 new interactive games (21 publicly released).

What qualities of models do we test

To beat each game an agent must discover the unknown rules and apply them to solve challenges.

Evaluation

Humans and frontier models play through the same interface: identical game states, identical action sets, identical step budgets.

Play

21 of the 70 games are public. Tiers get increasingly harder for models (1 = easiest, 7 = hardest).

Reproduce it

Run any model against the games through the SDK or API.

Join us

Join our community DisCo, where you can track your progress on these puzzles and hang out with like-minded folk.

Citation

DiG-bench: Discovery in Games

Ruairidh M. Battleday, Kai Sandbrink, Jimi Cullen-Drohan, Zihan Yan, Timothy Muller, Clare Maguire, Ales Kubicek, Fraser Greenlee-Scott, Sukrit Sumant, Tri Dao, Jürgen Schmidhuber, Michal Valko, Joshua Tenenbaum, Thomas L. Griffiths, Zeb Kurth-Nelson, James C.R. Whittington

@misc{battleday2026dig,
  title={DiG-bench: Discovery in Games},
  author={Ruairidh M. Battleday and Kai Sandbrink and Jimi Cullen-Drohan and Zihan Yan and Timothy Muller and Clare Maguire and Ales Kubicek and Fraser Greenlee-Scott and Sukrit Sumant and Tri Dao and Jürgen Schmidhuber and Michal Valko and Joshua Tenenbaum and Thomas L. Griffiths and Zeb Kurth-Nelson and James C.R. Whittington},
  year={2026},
  eprint={2608.12593},
  archivePrefix={arXiv},
  primaryClass={cs.AI},
  url={https://arxiv.org/abs/2608.12593},
}