NVIDIA has published Kumo Tabular on Hugging Face. The model predicts labels for new rows directly from a labeled table, without any training or feature engineering. Three sizes are offered – Small (≈28 M parameters), Medium (≈71 M) and Large (≈215 M). In the TabArena leaderboard it leads with an Elo of 1950 and runs about 17 % faster than the previous best LimiX‑2 when evaluated on a single RTX 6000 Pro GPU. The same models also rank first on BeyondArena, TALENT and ScoringBench.
Why it matters
It lets enterprises replace custom tabular pipelines with a single pretrained model that is both more accurate and quicker to run.
