Google DeepMind introduced Monday that a complicated model of its Gemini synthetic intelligence mannequin has formally achieved gold medal-level efficiency on the Worldwide Mathematical Olympiad, fixing 5 of six exceptionally tough issues and incomes recognition as the primary AI system to obtain official gold-level grading from competitors organizers.
The victory advances the sphere of AI reasoning and places Google forward within the intensifying battle between tech giants constructing next-generation synthetic intelligence. Extra importantly, it demonstrates that AI can now deal with advanced mathematical issues utilizing pure language understanding moderately than requiring specialised programming languages.
“Official results are in — Gemini achieved gold-medal level in the International Mathematical Olympiad!” Demis Hassabis, CEO of Google DeepMind, wrote on social media platform X Monday morning. “An advanced version was able to solve 5 out of 6 problems. Incredible progress.”
— Demis Hassabis (@demishassabis) July 21, 2025
The Worldwide Mathematical Olympiad, held yearly since 1959, is broadly thought of the world’s most prestigious arithmetic competitors for pre-university college students. Every collaborating nation sends six elite younger mathematicians to compete in fixing six exceptionally difficult issues spanning algebra, combinatorics, geometry, and quantity principle. Solely about 8% of human contributors sometimes earn gold medals.
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How Google DeepMind’s Gemini Deep Assume cracked math’s hardest issues
Google’s newest success far exceeds its 2024 efficiency, when the corporate’s mixed AlphaProof and AlphaGeometry programs earned silver medal standing by fixing 4 of six issues. That earlier system required human consultants to first translate pure language issues into domain-specific programming languages after which interpret the AI’s mathematical output.
This 12 months’s breakthrough got here via Gemini Deep Assume, an enhanced reasoning system that employs what researchers name “parallel thinking.” In contrast to conventional AI fashions that observe a single chain of reasoning, Deep Assume concurrently explores a number of attainable options earlier than arriving at a closing reply.
“Our model operated end-to-end in natural language, producing rigorous mathematical proofs directly from the official problem descriptions,” Hassabis defined in a follow-up publish on the social media web site X, emphasizing that the system accomplished its work inside the competitors’s commonplace 4.5-hour time restrict.
We achieved this 12 months’s spectacular consequence utilizing a complicated model of Gemini Deep Assume (an enhanced reasoning mode for advanced issues). Our mannequin operated end-to-end in pure language, producing rigorous mathematical proofs immediately from the official downside descriptions –…
— Demis Hassabis (@demishassabis) July 21, 2025
The mannequin achieved 35 out of a attainable 42 factors, comfortably exceeding the gold medal threshold. In response to IMO President Prof. Dr. Gregor Dolinar, the options have been “astonishing in many respects” and located to be “clear, precise and most of them easy to follow” by competitors graders.
OpenAI faces backlash for bypassing official competitors guidelines
The announcement comes amid rising pressure within the AI trade over aggressive practices and transparency. Google DeepMind’s measured strategy to releasing its outcomes has drawn reward from the AI neighborhood, notably in distinction to rival OpenAI’s dealing with of comparable achievements.
“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,” Hassabis wrote, showing to reference OpenAI’s earlier announcement of its personal olympiad efficiency.
Btw as an apart, we didn’t announce on Friday as a result of we revered the IMO Board’s authentic request that every one AI labs share their outcomes solely after the official outcomes had been verified by impartial consultants & the scholars had rightly acquired the acclamation they deserved
— Demis Hassabis (@demishassabis) July 21, 2025
Social media customers have been fast to notice the excellence. “You see? OpenAI ignored the IMO request. Shame. No class. Straight up disrespect,” wrote one person. “Google DeepMind acted with integrity, aligned with humanity.”
The criticism stems from OpenAI’s determination to announce its personal mathematical olympiad outcomes with out collaborating within the official IMO analysis course of. As a substitute, OpenAI had a panel of former IMO contributors grade its AI’s efficiency, a strategy that some locally view as missing credibility.
“OpenAI is quite possibly the worst company on the planet right now,” wrote one critic, whereas others instructed the corporate must “take things seriously” and “be more credible.”
You see?
OpenAI ignored the IMO request. Disgrace. No class. Straight up disrespect.
Google DeepMind acted with integrity, aligned with humanity.
TRVTHNUKE pic.twitter.com/8LAOak6XUE
— NIK (@ns123abc) July 21, 2025
Contained in the coaching strategies that powered Gemini’s mathematical mastery
Google DeepMind’s success seems to stem from novel coaching strategies that transcend conventional approaches. The workforce used superior reinforcement studying strategies designed to leverage multi-step reasoning, problem-solving, and theorem-proving information. The mannequin was additionally offered entry to a curated assortment of high-quality mathematical options and acquired particular steering on approaching IMO-style issues.
The technical achievement impressed AI researchers who famous its broader implications. “Not just solving math… but understanding language-described problems and applying abstract logic to novel cases,” wrote AI observer Elyss Wren. “This isn’t rote memory — this is emergent cognition in motion.”
Ethan Mollick, a professor on the Wharton College who research AI, emphasised the importance of utilizing a general-purpose mannequin moderately than specialised instruments. “Increasing evidence of the ability of LLMs to generalize to novel problem solving,” he wrote, highlighting how this differs from earlier approaches that required specialised mathematical software program.
It wasn’t simply OpenAI.
Google additionally used a normal function mannequin to resolve the very laborious math issues of the Worldwide Math Olympiad in plain language. Final 12 months they used specialised instrument use
Growing proof of the flexibility of LLMs to generalize to novel downside fixing https://t.co/Ve72fFmx2b
— Ethan Mollick (@emollick) July 21, 2025
The mannequin demonstrated notably spectacular reasoning in a single downside the place many human opponents utilized graduate-level mathematical ideas. In response to DeepMind researcher Junehyuk Jung, Gemini “made a brilliant observation and used only elementary number theory to create a self-contained proof,” discovering a extra elegant resolution than many human contributors.
What Google DeepMind’s victory means for the $200 billion AI race
The breakthrough comes at a vital second within the AI trade, the place corporations are racing to reveal superior reasoning capabilities. The success has quick sensible implications: Google plans to make a model of this Deep Assume mannequin obtainable to mathematicians for testing earlier than rolling it out to Google AI Extremely subscribers, who pay $250 month-to-month for entry to the corporate’s most superior AI fashions.
The timing additionally highlights the intensifying competitors between main AI laboratories. Whereas Google celebrated its methodical, officially-verified strategy, the controversy surrounding OpenAI’s announcement displays broader tensions about transparency and credibility in AI growth.
This aggressive dynamic extends past simply mathematical reasoning. Latest weeks have seen varied AI corporations announce breakthrough capabilities, although not all have been acquired positively. Elon Musk’s xAI not too long ago launched Grok 4, which the corporate claimed was the “smartest AI in the world,” although leaderboard scores confirmed it trailing behind fashions from Google and OpenAI. Moreover, Grok has confronted criticism for controversial options together with sexualized AI companions and episodes of producing antisemitic content material.
The daybreak of AI that thinks like people—with real-world penalties
The mathematical olympiad victory goes past aggressive bragging rights. Gemini’s efficiency demonstrates that AI programs can now match human-level reasoning in advanced duties requiring creativity, summary considering, and the flexibility to synthesize insights throughout a number of domains.
“This is a significant advance over last year’s breakthrough result,” the DeepMind workforce famous of their technical announcement. The development from requiring specialised formal languages to working totally in pure language means that AI programs have gotten extra intuitive and accessible.
For companies, this growth indicators that AI might quickly deal with advanced analytical issues throughout varied industries with out requiring specialised programming or area experience. The flexibility to cause via intricate challenges utilizing on a regular basis language might democratize subtle analytical capabilities throughout organizations.
Nevertheless, questions persist about whether or not these reasoning capabilities will translate successfully to messier real-world challenges. The mathematical olympiad offers well-defined issues with clear success standards — a far cry from the ambiguous, multifaceted choices that outline most enterprise and scientific endeavors.
Google DeepMind plans to return to subsequent 12 months’s competitors “in search of a perfect score.” The corporate believes AI programs combining pure language fluency with rigorous reasoning “will become invaluable tools for mathematicians, scientists, engineers, and researchers, helping us advance human knowledge on the path to AGI.”
However maybe probably the most telling element emerged from the competitors itself: when confronted with the competition’s most tough downside, Gemini began from an incorrect speculation and by no means recovered. Solely 5 human college students solved that downside accurately. In the long run, it appears, even gold medal-winning AI nonetheless has one thing to study from teenage mathematicians.
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