TabPFN-2.5 – SOTA foundation model for tabular data
I am excited to announce the release of TabPFN-2.5, our tabular foundation model that now scales to datasets of up to 50,000 samples and 2,000 features - a 5x increase from TabPFN v2, published in the Nature journal earlier this year. TabPFN-2.5 delivers state-of-the-art predictions in one forward pass without hyperparameter tuning across classification and regression tasks. What’s new in 2.5: TabPFN-2.5 maintains the core approach of v2 - a pretrained transformer trained on more than hundred million synthetic datasets to perform in-context learning and output a predictive distribution for…
TabPFN-2.5 – SOTA foundation model for tabular data launched on November 6, 2025 with 73 votes, #407 of 9,796 launches that month and more than 95% of that year's launches.
In plain words
TabPFN-2.5 is a foundation model designed for tabular data analysis that handles datasets up to 50,000 samples and 2,000 features. Built on a transformer pretrained on hundreds of millions of synthetic datasets, it performs classification and regression tasks in a single forward pass without requiring hyperparameter tuning. The model natively supports missing values, categorical and numerical features, text, and handles outliers and uninformative features. It represents a five-fold increase in scale compared to its predecessor.
written from the facts on this page · September 2026
From the sources
The first tabular foundation model, TabPFN, and its successor TabPFNv2 have impacted tabular AI substantially, with dozens of methods building on it and hundreds of applications across different use cases. This report introduces TabPFN-2.5 , the next generation of our tabular foundation model, scaling to 20× data cells compared to TabPFNv2. On industry standard benchmarks with up to 50,000 data points and 2,000 features, TabPFN-2.5 substantially outperforms tuned tree-based models and matches the accuracy of AutoGluon 1.4, a complex four-hour tuned ensemble that even includes the previous TabPFNv2. For production use cases, we introduce a new distillation engine that converts TabPFN-2.5…from priorlabs.ai
In the maker’s words, at launch
I am excited to announce the release of TabPFN-2.5, our tabular foundation model that now scales to datasets of up to 50,000 samples and 2,000 features - a 5x increase from TabPFN v2, published in the Nature journal earlier this year. TabPFN-2.5 delivers state-of-the-art predictions in one forward pass without…
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TabPFN v2 – A SOTA foundation model for small tabular data2025 · nature.com · ▲153I am excited to announce the release of TabPFN v2, a tabular foundation model that delivers state-of-the-art predictions on small datasets in just 2.8 seconds for classification and 4.8 seconds for regression compared to strong baselines tuned for 4 hours. Published in Nature, this model outperforms traditional methods on datasets with up to 10,000 samples and 500 features. The model is available under an open license: a derivative of the Apache 2 license with a single modification, adding an enhanced attribution requirement inspired by the Llama 3 license:…
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