Jakub Pachocki 团队的推理模型在 2025 ICPC 世界总决赛解出全部 12 道题
Last week, our reasoning models took part in the 2025 International Collegiate Programming Contest (ICPC), the world’s premier university-level programming comp
Jakub Pachocki 团队的推理模型在约 5 小时内解出 2025 ICPC 世界总决赛全部 12 道题，而最佳人类队伍解出 11 道。该模型族此前还在 AtCoder Heuristics World Finals 获得第二名，并在国际数学奥林匹克和国际信息学奥林匹克中获得金牌；团队下一步将研究更开放、时间跨度更长的问题及长期运行模型的安全与对齐。
查看原帖1/n I’m really excited to share that our @OpenAI reasoning system got a perfect score of 12/12 during the 2025 ICPC World Finals, the premier collegiate programming competition where top university teams from around the world solve complex algorithmic problems. This would have placed it first among all human participants. 🥇🥇
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Last week, our reasoning models took part in the 2025 International Collegiate Programming Contest (ICPC), the world’s premier university-level programming competition. Our system solved all 12 out of 12 problems, a performance that would have placed first in the world (the best human team solved 11 problems).
This milestone rounds off an intense 2 months of competition performances by our models: - A second place finish in AtCoder Heuristics World Finals - Gold medal at the International Mathematical Olympiad - Gold medal at the International Olympiad in Informatics - And now, a gold medal, first place finish at the ICPC World Finals.
I believe these results, coming from a family of general reasoning models rooted in our main research program, are perhaps the clearest benchmark of progress this year. These competitions are great self-contained, time-boxed tests for the ability to discover new ideas. Even before our models were proficient at simple arithmetic, we looked towards these contests as milestones of progress towards transformative artificial intelligence.
Our models now rank among the top humans in these domains, when posed with well-specified questions and restricted to ~5 hours. The challenge now is moving to more open-ended problems, and much longer time horizons. This level of reasoning ability, applied over months and years to problems that really matter, is what we’re after - automating scientific discovery.
This rapid progress also underscores the importance of safety & alignment research. We still need more understanding of the alignment properties of long-running reasoning models; in particular, I recommend reviewing the fascinating findings from the study of scheming in reasoning models that we released today (https://t.co/Jzlv8NUxQP)!
Congratulations to my teammates that poured their hearts into getting these competition results, and to everyone contributing to the underlying fundamental research that enables them!