OpenAI has introduced FrontierScience, a new benchmark designed to measure high-level scientific reasoning in AI models across physics, chemistry, and biology. The system features two distinct tracks: the Olympiad set, which uses complex short-answer problems created by international medalists, and the Research set, which consists of PhD-level sub-tasks. To evaluate these open-ended research problems, the authors implemented a granular rubric-based architecture that assesses intermediate reasoning steps rather than just final answers. Initial testing shows that while top models like GPT-5.2 perform well on structured problems, they still struggle with the more complex, original research tasks. This benchmark aims to provide an unsaturated evaluation tool as AI capabilities begin to outpace existing scientific tests. By utilizing experts to craft novel, "Google-proof" questions, the framework ensures a rigorous standard of originality and difficulty.

References:

• Wang M, Lin R, Hu K, et al. FrontierScience: Evaluating AI's Ability to Perform Expert-Level Scientific Tasks[J]. arXiv preprint arXiv:2601.21165, 2026.