Jevman – AI decision models play Pac-Man
Six AI decision models played Pac-Man in real time against the classic arcade ghosts. See the leaderboard, watch their games, or play against them.
Jevman – AI decision models play Pac-Man launched on October 8, 2026 with 81 votes, #225 of 3,080 launches that month and more than 95% of that year's launches.
In plain words
Jevman is an open-source platform that tests AI decision models by having them play Pac-Man against classic arcade ghosts. Six pre-trained models competed in 100 games each, with results displayed on a leaderboard alongside recorded gameplay. Users can watch the games, play against the models themselves, or integrate their own models via HTTP endpoint. The game sends maze data as JSON and allows two seconds per move decision.
written from the facts on this page · October 2026
From the sources
Six of them played 100 games each against the arcade ghosts. See how they rank, watch their games or play against them. =1 means tied: those scores are within each other's margin of error. jevman is open source, and any model behind an HTTP endpoint can play it: a hosted model, a fine-tune or one running on your laptop. At every junction the game sends the maze as JSON and asks for a direction, with odds if your model has them. The repo has a 34-line example endpoint to start from. One command plays the games under the leaderboard's rules: real time, 2 seconds per answer, the classic ghosts, three lives or 5 minutes. CI replays every game you submit and checks its score. Your model then…from opper.ai
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