An advanced version of Google DeepMind’s Gemini model has achieved gold-medal performance at the 2025 International Mathematical Olympiad (IMO), solving five of the six problems and scoring 35 out of a possible 42 points.
The full set of Gemini’s solutions is available online.
Google says that it is the first time an AI system has officially reached the gold-medal threshold in the IMO, the world’s leading mathematics competition for pre-university students. The result was confirmed by IMO coordinators, who graded the model’s work using the same standards applied to human participants.
However, OpenAI also recently announced achieving a similar feat. Announcing the result on X, OpenAI researcher Alexander Wei said, “Our latest experimental reasoning LLM has achieved a longstanding grand challenge in AI: gold medal-level performance on the world’s most prestigious math competition—the International Math Olympiad.”
Google DeepMind chief Demis Hassabis said in a post on X on this disparity. “We didn’t announce on Friday because we respected the IMO Board’s original request that all AI labs share their results only after the official results had been verified by independent experts & the students had rightly received the acclamation they deserved,” he said.
He added that they have now been authorised to share results and are pleased to have been part of the inaugural cohort to have our model results officially graded and certified by IMO coordinators and experts, receiving the first official gold-level performance grading for an AI system.
“We can confirm that Google DeepMind has reached the much-desired milestone, earning 35 out of a possible 42 points — a gold medal score,” said Prof Gregor Dolinar, president of the IMO. “Their solutions were astonishing in many respects. IMO graders found them to be clear, precise, and most of them easy to follow.”
Meanwhile, OpenAI’s model also successfully solved 5 out of 6 problems, earning 35 out of 42 possible points. Three former IMO medalists graded each solution independently, with final scores based on unanimous agreement.
Gemini operated entirely in natural language, generating rigorous proofs directly from the official problem statements within the IMO’s 4.5-hour time limit.
This represents a significant improvement over last year’s effort, when DeepMind’s AlphaGeometry and AlphaProof systems required translating problems into formal languages and involved multiple days of computation.
The latest result by Google was made possible by Gemini’s Deep Think mode, which uses research techniques including parallel thinking. This allows the model to consider and combine multiple solution paths simultaneously before arriving at a final answer.
DeepMind also applied reinforcement learning strategies to improve multi-step reasoning and trained Gemini using a curated dataset of mathematical solutions. General strategies for approaching IMO problems were also included in its instruction set.
A version of the Deep Think model will be released to a limited group of testers, including professional mathematicians, before a broader rollout to Google AI Ultra subscribers.
DeepMind noted that while this year’s performance used natural language exclusively, work continues on formal reasoning tools like AlphaGeometry and AlphaProof. The long-term goal is to develop AI systems that combine fluency in natural language with the reliability of formal mathematical verification.
“We are still only at the start of AI’s potential to contribute to mathematics,” the company said. “By teaching our systems to reason more flexibly and intuitively, we are getting closer to building AI that can solve more complex and advanced mathematics.”
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