Quick Summary AI models like OpenAI’s ChatGPT and Google’s Gemini participated in the 2025 International Math Olympiad (IMO).For the first time, AI achieved “gold-level” scores in the competition.Despite this milestone, AI failed to outperform the top human students.Human competitors showcased superior rigor, creativity, and precision.The event marks progress in AI but reaffirms the unique strengths of human mathematical reasoning. What Happened at the 2025 International Math Olympiad? ChatGPT (OpenAI, experimental model): 35/42 points (gold-level medal)Gemini (Google DeepMind): 35/42 points (gold-level medal)Top Human Contenders: 5 students achieved a perfect 42/42 score Why Is This Newsworthy? First Gold-Level AI Medals: This marks a breakthrough—AI systems have now reached the rarefied top 10% of human IMO scorers.Competition Against the Best: Both AIs were assessed using the same exam, in the same time frame (4.5 hours), under independently observed and graded conditions.Fundamental Questions: Can AI ever tackle creativity, adaptability, and strategic reasoning in math as well as the best young minds? How Do the AI Results Compare to Top Human Contestants? Breakdown of Achievements What Does “Gold-Level” Really Mean at the International Math Olympiad? Gold Medals: Traditionally awarded to about the top 10% of competitors.Perfection Matters: All five humans who achieved perfect scores outperformed even the best AI results. What Makes the International Math Olympiad Such a Benchmark for AI and Human Ability? The Competition Format: Six complex problems over 4.5 hours, demanding deep creativity, proof-writing, and clever insights.Participants: High school students under age 20, selected through rigorous national contests.Why It Matters: Solving IMO problems is seen as a proxy for deep mathematical reasoning—an area where human intuition, perseverance, and fresh perspectives historically dominate. Why Do Humans Still Have the Edge? Creativity in Problem Solving: Many IMO solutions require novel approaches or leaps of insight not found in textbooks or training data.Proof Rigor: Competitors must write formal, stepwise proofs evaluated by experienced mathematicians.Adaptability: Humans can shift strategies if a solution roadblocks, an area where AI still struggles. How Were the AI Models Evaluated? A panel of former IMO medalists independently graded the AI-submitted proofs, holding them to the same standards as competitors.The AI models, according to organizers, received the exact problems under the official contest conditions.There remains some uncertainty about the computational resources used, as contest organizers cannot verify the hardware or human intervention in AI runs. Future transparency is needed here. Why Is This a Big Deal for AI Research? AI’s Progress: From Days Down to Hours Last year, Google’s AI took “two to three days” to work through an IMO-style test. In 2025, both Gemini and ChatGPT worked on the same timescale as humans, closing a major gap in real-world usability. AI’s Limits—and What Comes Next No Perfect Scores Yet: While reaching gold-level is significant, AI models have yet to emulate the best of the best.Qualitative Feedback: IMO graders described many AI solutions as “clear, precise, and easy to follow,” highlighting cleaner mathematical reasoning than seen just a year ago.Verification and Trust: As AI continues to improve, independent verification, clear reporting of computational resources, and standardized testing will be crucial for validating true breakthroughs. What Does This Mean for the Future of AI in Mathematics? AI as a Learning Tool: Such advances may soon let AI act as a more meaningful tutor, coach, or collaborator for math students everywhere.Human-AI Collaboration: The future likely lies in synergistic problem-solving, where AI’s computational brute force complements human inventiveness.