Why Anthropic’s Claude still hasn’t beaten Pokémon

Where previous models wandered aimlessly or got stuck in loops, Claude 3.7 Sonnet plans ahead, remembers its objectives, and adapts when initial strategies fail.

Critical skills for battling pixelated gym leaders. And, we posit, in solving real-world problems too. pic.twitter.com/scvISp14XG

— Anthropic (@AnthropicAI) February 25, 2025

One of the biggest things preventing the current version of Claude from getting better, Hershey said, is that “when it derives that good strategy, I don’t think it necessarily has the self-awareness to know that one strategy [it] came up with is better than another.” And that’s not a trivial problem to solve.

Still, Hershey said he sees “low-hanging fruit” for improving Claude’s Pokémon play by improving the model’s understanding of Game Boy screenshots. “I think there’s a chance it could beat the game if it had a perfect sense of what’s on the screen,” Hershey said, saying that such a model would probably perform “a little bit short of human.”

Expanding the context window for future Claude models will also probably allow those models to “reason over longer time frames and handle things more coherently over a long period of time,” Hershey said. Future models will improve by getting “a little bit better at remembering, keeping track of a coherent set of what it needs to try to make progress,” he added.

Twitch chat responds with a flood of bouncing emojis as Claude concludes an epic 78+ hour escape from Pokémon’s Mt. Moon.

Whatever you think about impending improvements in AI models, though, Claude’s current performance at Pokémon doesn’t make it seem like it’s poised to usher in an explosion of human-level, completely generalizable artificial intelligence. And Hershey allows that watching Claude 3.7 Sonnet get stuck on Mt. Moon for 80 hours or so can make it “seem like a model that doesn’t know what it’s doing.”

But Hershey is still impressed at the way that Claude’s new reasoning model will occasionally show some glimmer of awareness and “kind of tell that it doesn’t know what it’s doing and know that it needs to be doing something different. And the difference between ‘can’t do it at all’ and ‘can kind of do it’ is a pretty big one for these AI things for me,” he continued. “You know, when something can kind of do something it typically means we’re pretty close to getting it to be able to do something really, really well.”