AI agents solve 49 of 50 unpublished physics problems in DeepMind-backed study

An AI model just worked through a stack of 50 unpublished, research-level theoretical physics problems. It solved 49 of them. That result comes from a new preprint called TheoPhysEval, and the model in question is GPT-6-Astra. With web search turned on, it scored 98%, which is the kind of grade that usually gets a graduate student a handshake and a heavier workload. What the benchmark actually tested The paper is titled “TheoPhysEval: Assessing AI agents at autonomous theoretical physics problem solving.” It landed on arXiv on October 9, 2026. The benchmark contains 50 theoretical physics problems that had never been published. They span 11 subfields, including fluid dynamics and quantum field theory. The goal was to see what AI agents can do with no human help at all. Nobody nudged the models along or fixed their mistakes midstream. Physicists from institutions such as ICTS and Google DeepMind led the work. The author list runs to 35 people from a range of research institutions. The researchers tested off-the-shelf models, not custom-built research systems. They designed the criteria to approximate the skills an expert theoretical physicist would need. The scoreboard The study spl...