AutoLogi
AutoLogi is an automated method for synthesizing open-ended logic puzzles to evaluate reasoning abilities of Large Language Models. The benchmark addresses limitations of existing multiple-choice reasoning evaluations by featuring program-based verification and controllable difficulty levels. It includes 1,575 English and 883 Chinese puzzles, enabling more reliable evaluation that better distinguishes models' reasoning capabilities across languages.
Kimi K2 Instruct from Moonshot AI currently leads the AutoLogi leaderboard with a score of 0.895 across 2 evaluated AI models.
Kimi K2 Instruct leads with 89.5%, followed by Kimi K2-Instruct-0905 at 89.5%.
Progress Over Time
Interactive timeline showing model performance evolution on AutoLogi
AutoLogi Leaderboard
| Context | Cost | License | ||||
|---|---|---|---|---|---|---|
| 1 | Moonshot AI | 1.0T | — | — | ||
| 1 | Moonshot AI | 1.0T | — | — |
FAQ
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