Our public datasets catalog over 3000 machine learning models. Explore data and graphs showing the growth and trajectory of AI from 1950 to today.

LLMs have come a long way on high school math contests but have yet to show that they can solve the hardest problems found on these contests.

Models that fit on consumer GPUs match the performance of frontier AI within a year or less.

The private sector’s share of global AI computing capacity has grown from 40% in 2019 to 80% in 2025. Though many leading early supercomputers such as Summit were run by government and academic labs, the total installed computing power of public-sector clusters has only increased at 1.8x per year, rapidly outpaced by private-sector clusters, whose total computing power has grown at 2.7x per year. The rising economic importance of AI has spurred the private sector to build more and faster clusters for training and inference. As of May 2025, the largest known public AI supercomputer, Lawrence Livermore’s El Capitan, achieves less than a quarter of the computational performance of the largest known industry cluster, xAI’s Colossus.

Our database of over 500 GPU clusters and supercomputers tracks large hardware facilities, including those used for AI training and inference.

GPT-5 compute estimate Guesstimate model link: https://www.getguesstimate.com/models/26145 Pretraining Training compute of LLMs during pretraining is closely approximated by 6 * number of active parameters * number of tokens the model was trained on. Active parameters GPT-5 is likely a “mid-si...

In the past 12 months, AI’s abilities have improved steadily across a range of skills including coding, visual and common sense reasoning, and math.