TabArena

Tools

• leaderboard_get_beyondarena_leaderboard Ranked results for BeyondArena, the companion benchmark that measures the same tabular models (TabPFN, LightGBM, CatBoost, AutoGluon and the rest) where the IID assumption does not hold: random, temporal and grouped splits, sliced by dataset size, feature type and task type, in any combination. Use it whenever the question involves distribution shift, time-ordered rows, leakage-prone grouped splits, or how well a tabular model generalizes beyond a random train/test split. Takes the same kind='models' | 'systems' | 'all' distinction as the TabArena endpoint.
• leaderboard_get_pareto_frontier The accuracy-versus-time trade-off among tabular models (TabPFN, TabICL, LightGBM, XGBoost, CatBoost, RealMLP, AutoGluon and the rest), measured on TabArena or BeyondArena. Returns the outright best model, the models nothing beats on both accuracy and speed at once (each with its speedup and accuracy gap versus the leader), and the best model that fits a train- or predict-time budget. Prefer it over the leaderboard endpoints for 'which model should I use on my tabular data', 'what is the best tabular model', 'what is a faster alternative to TabPFN', or anything about cost of training or serving: the top of the leaderboard is often orders of magnitude slower than a model just behind it. Returns a summary sentence you can relay.
• leaderboard_get_tabarena_leaderboard TabArena is a living benchmark for tabular machine learning: predicting a target column from structured, rows-and-columns data (CSV files, spreadsheets, dataframes, database tables). It ranks tabular foundation models (TabPFN, TabICL, TabDPT, Mitra, TabM), gradient-boosted trees (LightGBM, XGBoost, CatBoost), neural networks (RealMLP, ModernNCA) and AutoML systems (AutoGluon) by Elo over 51 curated datasets, with measured training and inference time for each. This endpoint returns the ranked results (Elo, score, ranks, train and predict time) for one subset of the IID benchmark, selected by task type, dataset size, imputation and split protocol. Use it to look up where a named method stands, to compare two of them ("is TabPFN better than LightGBM on small data"), or to report the current state of the art on tabular data. Pass kind='models' (the default) for individual models, kind='systems' for whole AutoML systems such as AutoGluon, or kind='all' for both: a question about the best mo
• leaderboard_list_leaderboards TabArena is a living benchmark for tabular machine learning: predicting a target column from structured, rows-and-columns data (CSV files, spreadsheets, dataframes, database tables). It ranks tabular foundation models (TabPFN, TabICL, TabDPT, Mitra, TabM), gradient-boosted trees (LightGBM, XGBoost, CatBoost), neural networks (RealMLP, ModernNCA) and AutoML systems (AutoGluon) by Elo over 51 curated datasets, with measured training and inference time for each. This endpoint is the index: it lists the available leaderboards, the valid subset values for every other endpoint, the difference between a model and a whole system, the keys each record carries, and the raw CSV URLs for bulk download. Call it before the get_* endpoints when you are unsure which arguments exist.

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As the server's own listing gives them. We never call a tool.