Under direction from expert mathematicians and scientists, Gemini Deep Think is solving professional research problems across mathematics, physics, and computer science
In the summer of 2025, an advanced version of Gemini Deep Think achieved Gold-medal standard at the International Mathematics Olympiad (IMO) and later, an updated version, obtained similar results at the International Collegiate Programming Contest. These results demonstrated the model could reason through some of the most challenging math and programming problems designed for students. Since then, Gemini Deep Think mode has moved into science, engineering and enterprise workflows to tackle more complex, open-ended challenges.
In the last week, our teams published two papers (1, 2) detailing a cross-disciplinary effort to solve professional research problems using Gemini Deep Think mode. These results stem from deep collaboration between mathematicians, physicists, and computer scientists.
The Frontier of Pure Mathematics
Unlike IMO problems, research-level mathematics requires advanced techniques from vast literature. While foundation models have large knowledge bases, data scarcity often leads to superficial understanding and hallucinations in advanced subjects.
To solve this, we built a math research agent (internally codenamed Aletheia), powered by Gemini Deep Think mode. It features a natural language verifier to identify flaws in candidate solutions and enable an iterative process of generating and revising solutions. Crucially, this agent can admit failure to solve a problem, a key feature that improved the efficiency for researchers.
Additionally, the research agent uses Google Search and web browsing to navigate complex research, preventing spurious citations and computational inaccuracies when synthesizing published literature.
— Source: DeepMind Blog (https://deepmind.google/blog/accelerating-mathematical-and-scientific-discovery-with-gemini-deep-think/)
