Google has announced that its advanced AI model, Gemini 2.5 Deep Think, achieved a gold medal-level performance at the 2025 International Collegiate Programming Contest (ICPC) World Finals.
The AI correctly solved 10 out of 12 complex coding problems, securing the second-highest overall score and outperforming the vast majority of human competitors. This achievement marks a significant step toward artificial general intelligence (AGI) and showcases the model’s potential to revolutionize fields like software development and scientific research.
A new milestone in AI problem-solving
The ICPC World Finals, held on September 4, 2025, in Baku, Azerbaijan, is considered the most prestigious university-level coding competition globally. Teams from nearly 3,000 universities were tasked with solving a series of intricate problems within a five-hour time limit, where only perfect solutions are accepted.
Gemini 2.5 Deep Think operated as an automated team of AI agents, with multiple instances proposing, coding, and testing solutions collaboratively. This multi-agent approach allowed it to tackle complex challenges systematically.
Innovative solution to an “unsolvable” problem
One of the most impressive feats was Gemini’s solution to “Problem C,” a complex optimization challenge that no human team managed to solve during the competition.
The problem involved finding the optimal way to distribute liquid through a network of ducts. In under 30 minutes, Gemini developed a novel strategy using the minimax theorem, a concept from game theory, to find the solution. Google compared this moment to AlphaGo’s famous “Move 37” in its 2016 match against Go champion Lee Sedol, where the AI made a creative and unexpected move that proved decisive.
A major step for AGI
This achievement in competitive coding follows Gemini’s success at the International Mathematical Olympiad in July 2025, where it also earned a gold medal. In its announcement, Google stated that these combined breakthroughs represent “a profound leap in abstract problem-solving—marking a significant step on our path toward artificial general intelligence (AGI).”
The company emphasized that the skills demonstrated by Gemini—breaking down complex problems, creating multi-step logical plans, and executing them flawlessly—are the same ones required for critical scientific and engineering tasks, such as designing new drugs or microchips. Google envisions a future where AI systems like Gemini collaborate with human experts, proposing unconventional ideas to accelerate scientific discovery and solve long-standing technical problems.
While large language models have already had a significant impact on software development, Gemini’s performance suggests a move toward more autonomous, reasoning-focused AI that can tackle real-world challenges with human-like ingenuity. Although the model failed to solve two problems that human teams did, its overall success points to a future where human-AI partnerships could drive innovation across industries.
