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Advanced version of Gemini with Deep Think officially achieves gold-medal standard at the International Mathematical Olympiad

Google DeepMind · 2025

AI-verified citationSRC-DEEPMIND-IMO-2025
url
https://deepmind.google/blog/advanced-version-of-gemini-with-deep-think-officially-achieves-gold-medal-standard-at-the-international-mathematical-olympiad/
verification note
Announcement dated 21 July 2025; content read via search retrieval of the official DeepMind page (2026-08-22 run). Confirmed: five of six problems solved, 35 of 42 points, gold-medal standard, graded and certified by IMO coordinators using the same criteria and the 4.5-hour limit as student contestants, and operating end-to-end in natural language rather than through Lean formalization as in 2024. The confirming quotation is attributed on the page to IMO President Gregor Dolinar.
reliability notes
  • A corporate blog post, but the load-bearing fact — official IMO grading — is externally attested and was the point of the exercise.
  • Not peer-reviewed and no accompanying paper; the model is unreleased. Weaker as a citable source than the Nature AlphaProof paper, and used here only for the natural-language and officially-graded details the Nature paper predates.

Evidence drawn from this source

Supports· weakORCH-E024

Gemini Deep Think: officially graded IMO gold, in natural language

what the source states
DeepMind reports that an advanced version of Gemini with Deep Think solved five of six problems at the 2025 International Mathematical Olympiad for 35 of 42 points, achieving gold-medal standard. The announcement states the solutions were graded and certified by IMO coordinators using the same criteria applied to student contestants, and that the system worked end-to-end in natural language within the 4.5-hour competition limit — without the Lean formalization used in 2024. The page attributes a confirming statement to IMO President Gregor Dolinar.
what we infer
Included for two specific facts the Nature paper predates: official IMO grading under contest conditions, and natural-language rather than formalized operation. Graded weak as a source because it is a corporate blog post with no accompanying paper and an unreleased model, so it rests on DeepMind's account — though the load-bearing element, external grading by IMO coordinators, is the part least susceptible to self-report bias. Same scoping as the rest of this theme: motivation rung only.
limitations
  • Corporate announcement; no peer-reviewed paper and no released model.
  • Solutions in natural language were not machine-verified, unlike the 2024 Lean work.
  • Competition mathematics, not open research problems.
  • Bears on the motivation rung only.