# Google DeepMind Achieves Gold-Medal Performance on International Mathematical Olympiad Benchmark

> Google DeepMind says its Gemini Deep Think system reached gold-medal standard on a new benchmark built to test mathematical proof, scoring as high as 90 percent on the advanced tier of what its authors call IMO-ProofBench. The benchmark is modeled on the International Mathematical Olympiad and, importantly, was vetted by a panel of former olympiad medalists, ten of them gold and five silver, to judge whether the AI's written proofs actually hold up. That last detail is the interesting part. Multiple-choice math is easy to game, but generating a full proof that expert humans accept as correct is a much harder bar, and it targets the kind of step-by-step reasoning that has long tripped up language models. Scores climbed with more compute, suggesting the gains come partly from letting the model think longer. Benchmarks are not the same as genuine mathematical discovery, and olympiad problems have known answers a research frontier does not. Still, credible proof-writing at this level hints that AI is inching from pattern matching toward something closer to structured reasoning, which is where the real scientific payoff would eventually live.

_Section: [Daily AI Updates](https://www.wortins.com/daily-ai) · Source: Google DeepMind · Published Friday, August 14, 2026_

## Wortins' read

Google DeepMind says its Gemini Deep Think system reached gold-medal standard on a new benchmark built to test mathematical proof, scoring as high as 90 percent on the advanced tier of what its authors call IMO-ProofBench. The benchmark is modeled on the International Mathematical Olympiad and, importantly, was vetted by a panel of former olympiad medalists, ten of them gold and five silver, to judge whether the AI's written proofs actually hold up. That last detail is the interesting part. Multiple-choice math is easy to game, but generating a full proof that expert humans accept as correct is a much harder bar, and it targets the kind of step-by-step reasoning that has long tripped up language models. Scores climbed with more compute, suggesting the gains come partly from letting the model think longer. Benchmarks are not the same as genuine mathematical discovery, and olympiad problems have known answers a research frontier does not. Still, credible proof-writing at this level hints that AI is inching from pattern matching toward something closer to structured reasoning, which is where the real scientific payoff would eventually live.

## Source

[Read the full story at Google DeepMind](https://imobench.github.io/)

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