OpenAI has launched a new high-stakes exam for artificial intelligence. Announced on December 16, the “FrontierScience” benchmark is designed to rigorously test whether advanced AI models possess expert-level scientific reasoning in physics, chemistry, and biology. This move comes as companies like OpenAI report their models are increasingly being used to accelerate real scientific research.
Why a New Scientific Test Was Needed
AI models have recently achieved startling results, like solving International Math Olympiad problems at a gold-medal level. But OpenAI states that existing science benchmarks are no longer tough enough. Many rely on multiple-choice questions or have been effectively “solved” by the latest models. For instance, a once “Google-Proof” benchmark saw scores jump from 39% with GPT-4 to 92% with GPT-5.2 in just two years. FrontierScience was created to be a far more challenging measure of deep reasoning, not just factual recall.
What Does FrontierScience Actually Measure?
The benchmark comprises over 700 tough questions, split into two distinct tracks. The first is FrontierScience-Olympiad. It features 100 short-answer questions crafted by International Science Olympiad medalists. The problems require constrained, theoretical reasoning at least as difficult as those top-tier competitions.
The second track is FrontierScience-Research. This includes 60 original, multi-step research subtasks written by PhD-level scientists. These are designed to mirror real-world scientific challenges, like interpreting complex data or designing follow-up experiments. Answers here are graded on a detailed 10-point rubric.
How Do the Leading AI Models Perform?
The early results show strong performance but also clear limits. On the Olympiad track, OpenAI’s GPT-5.2 scored 77%, with Google’s Gemini 3 Pro close at 76%, showing major gains in expert-level reasoning. However, the Research track was much tougher. GPT-5.2 managed only 25%, indicating that open-ended, multi-step scientific reasoning is still challenging. Because grading such large-scale responses manually was impractical, all answers were evaluated using a strict, model-based scoring system.
What Are the Limitations of This Benchmark?
OpenAI is clear that FrontierScience has boundaries. It tests on constrained, expert-written problems but does not evaluate how AI might generate truly novel hypotheses or interact with real-world lab equipment and multimodal data like video. It is a benchmark of reasoning on paper, not a test of conducting hands-on science. The company views it as one crucial tool among many needed to gauge AI’s scientific potential.
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The Road Ahead for AI in Science
OpenAI says success is not about acing tests but about driving scientific breakthroughs. FrontierScience acts as an early signal of which AI models may assist researchers. Progress will come from improved reasoning systems and science-focused AI tools. OpenAI plans to broaden the benchmark to more domains and connect it with real-world evaluations.
FAQs
Q: What is FrontierScience?
A: It’s a new benchmark from OpenAI with over 700 expert-level questions in physics, chemistry, and biology, designed to test AI’s deep scientific reasoning, not just its knowledge.
Q: How did GPT-5.2 perform?
A: It demonstrated ability in limited reasoning but trouble with intricate, multi-step research tasks, scoring 77% on the theoretical Olympiad-style problems but just 25% on the open-ended Research track.
Q: Why is this benchmark important?
A: Greater use of AI in research makes it necessary to evaluate its deeper reasoning abilities, not just performance on older tests, raising the standard.
Q: Was the test graded by humans?
A: No. Due to the scale, a model-based grader (GPT-5) evaluated answers using a strict, point-based rubric designed for objective assessment.