The AI Index 2025, compiled by Stanford HAI at Stanford University, counts notable AI models released from 2014 to 2024 by institution. Among universities, Stanford University and Carnegie Mellon University (CMU) had 25 each, Tsinghua University and the University of California, Berkeley, had 22 each, and MIT had 15.
This article uses those figures as a guide to examine five universities with active AI research.
Model counts are not the answer to choosing a university
“Which university should I attend to study AI?” It is a question that students weighing their options and professionals looking to hire talent or find collaborators have probably considered at least once. But the figures that are easiest to find come with pitfalls.
The number of notable AI models used here counts how many prominent models have emerged from research institutions. It is not a measure of how many students major in AI or how comprehensive a university’s courses are. Rather than a ranking, it is best viewed as a starting point for gauging the momentum of research at each university.
Stanford and CMU tied for the top spot
Stanford University and CMU had the highest total among universities, with 25 models each. Over the 11 years from 2014 to 2024, both schools produced 25 notable models.
Stanford crosses disciplinary boundaries
Any discussion of Stanford must include Stanford HAI, established in 2019. It is positioned as an interdisciplinary organization that conducts research across multiple schools under the banner of rethinking AI from a human-centered perspective.
AI is no longer a field confined to computer science. As its connections with medicine, law, economics and ethics grow, an approach that does not take school boundaries as a given from the outset is well suited to the times.
CMU matches Stanford
CMU also had 25 models, putting it level with Stanford in terms of model count. The tie also suggests that the center of AI research is not concentrated at a single university.
Rather than seeing the tie as a failure to settle which school is better, it is probably more accurate to view it as two universities pursuing different paths side by side.
Tsinghua and Berkeley follow with 22 each
Next are China’s Tsinghua University and the University of California, Berkeley, in the United States, with 22 models each. They trail Stanford and CMU by just three.
What makes this lineup interesting is that universities from both the United States and China feature among the leaders. The figures at the university level also show that AI research is not confined to any one country. When looking for a place to study abroad or a research partner, it may be worth broadening your perspective across countries and regions.
MIT stands out for the breadth of its research
MIT had 15 notable AI models, a modest figure compared with the top four universities. But a look at the breadth of its research reveals another side.
The official website of MIT’s Computer Science and Artificial Intelligence Laboratory (CSAIL) lists 68 projects, 27 research groups and 111 people in AI and machine learning. Research applying machine learning to fields such as robotics, medicine and language processing is also one of its main pillars.
Some universities make their mark with one major model, while others broaden the range of applications through numerous research groups. A measure based solely on model counts cannot capture the depth of the latter approach.
How to choose beyond the numbers
Across the five universities, the largest gap in model counts is 10. Choosing a university based on that difference alone may be a little rash.
What matters is considering which fields you want to apply AI to. If you value connections with society, look for a university with an interdisciplinary organization; if you want a broad range of applications, consider an institute with many research groups. Shifting your focus from the numbers to the research structure behind them can change how a university looks.
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