NVIDIA Kumo Tabular is an open foundation model for tabular data prediction, available on Hugging Face under the OpenMDW-1.1 license. It predicts labels for new rows in a single forward pass without training, tuning, or feature engineering, using a Transformer architecture with column, row, and in-context attention. The model, pretrained on artificial data in three sizes (28M–215M parameters), ranks first on four benchmarks and addresses enterprise machine learning tasks historically dominated by gradient-boosted trees.