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Data on AI Supercomputers | Epoch AI

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Our database of over 500 supercomputers (also known as computing clusters) tracks large hardware facilities for AI training and inference. LAST UPDATED JUNE 05, 2025 Selected insights from this dataset. The computational performance of the leading AI supercomputers has grown by 2.5x annually since 2019. This has enabled vastly more powerful training runs: if 2020’s GPT-3 were trained on xAI’s Colossus, the original two week training run could be completed in under 2 hours. This growth was enabled by two factors: the number of chips deployed per cluster has increased by 1.6x per year, and performance per chip has also improved by 1.6x annually. AI supercomputers have become increasingly expensive. Since 2019, the cost of the computing hardware for leading supercomputers has increased at a rate of 1.9x per year. In June 2022, the most expensive cluster was Oak Ridge National Laboratory Frontier, with a reported cost of $200M. Three years later, as of June 2025, the most expensive superco

Data on GPU clusters | Epoch AI This dataset is deprecated. For data on site-level infrastructure, users, and satellite analysis, explore the AI Data Centers database . Updated Mar. 13, 2026 GPU Clusters Our database of over 500 GPU clusters and supercomputers tracks large hardware facilities, including those used for AI training and inference. This dataset was previously called 'AI Supercomputers' but was renamed to account for its broad coverage of GPU clusters. Download this data Cluster Country Map Table Settings Bubble size Max performance (OP/s) Max performance (OP/s) Performance (16-bit

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