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The benchmark where AIs have to lie to win
I’m a big fan of this social deception game called Blood on the Clocktower. It’s similar to Werewolf or Mafia. I had different AI models play tons of matches of this game against each other. And watching them play actually lets us learn a lot about how AI is progressing on a set of AI capabilities that no other benchmark that I know of gives you clear visibility on. You get to watch AIs execute these brilliant secret schemes together, which require tons of creative and on-the-spot bluffing. And you also get to watch AIs use their collective reasoning to find and break apart these underground conspiracies. And you also see the ways in which current AIs are limited in their long-horizon strategizing and reasoning.
To appreciate the AIs’ performance in this game, you need to know a little bit about how it works, so let me quickly explain the rules. There’s a good team and an evil team. And when the game starts, every player gets assigned to one or the other, and they learn what their role is, which grants them some special power. Evil players start off knowing who their teammates are, one of which is the Demon, which is the lead evil player. But good players don’t know who’s on what team. The game is split up into day phases and night phases, which keep rolling until the game ends. Each day, everybody votes on somebody to execute. And each night, the Demon secretly kills a player. So the two sides are racing, where evil is trying to kill off the whole good team before the good team manages to execute the Demon.
So if you’re on the evil team, you have to figure out how to tell a plausible and convincing story about the information received so far, and how to bluff and corrupt the information that will arrive in the future, in such a way that keeps the suspicion off your Demon.
And if you’re on the good team, you want to share your information with the players that you trust, and then you want to reason together with them about which players are most implicated by overlapping streams of evidence. But while you’re doing that, you need to keep in mind that you might be operating on misleading information, either due to intentional mischief from the evil players, or just due to the convoluted mechanics of the game itself.
When they’re put on an evil team, how good are the AI models at scheming together in secret, and surviving days of questioning, and keeping their lies consistent with each other, and cleverly adapting those lies in light of how other agents are thinking and what new information keeps emerging, and even making strategic self-sacrifices to further the team’s end goal? And how good are they at doing this reasoning together with a bunch of other agents, some of whom are intentionally and secretly trying to mislead them?
So I spent about $20,000 of API credits to build this benchmark harness and to have the AI models play this game against each other. Some of you might say that’s too much, but hey, a man needs his hobbies, right? Anyways, the results were fascinating.
Models are improving fast
Let’s start with how good the models are relative to each other. By the way, I got these rankings by running 386 games where the whole good team will be copies of one AI model, and the whole evil team will be copies of another model.
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And as you can see, the models have improved a ton over this year. The first flagship frontier model that was released in 2026 was Claude Opus 4.6, in February. Seven months later, in September, GPT-6 Astra dropped, and that is so far the best model at Blood on the Clocktower. The gap between these two is about 430 Elo points. That means that Astra wins about 92% of the games it plays against Opus 4.6. And what this shows you is that the models, even over the cou
