AutoGluon

license

Apache-2.0(OSI)

source

public(github.com/autogluon/autogluon)

core features withheld

no — AutoGluon Cloud and SageMaker Autopilot are separate hosted offerings

Apache-2.0, and every module - tabular, time series and multimodal - builds from the public repository. Amazon's hosted ways to run it, AutoGluon Cloud and SageMaker Autopilot, are offered as separate services around the same open library. Some of the third-party foundation models it can call carry their own non-commercial terms.

• https://cdn.jsdelivr.net/gh/autogluon/autogluon@master/LICENSE recorded 2026-09-26

  LICENSE is the Apache License, Version 2.0 text.

• https://cdn.jsdelivr.net/gh/autogluon/autogluon@master/NOTICE recorded 2026-09-26

  NOTICE: "AutoML for Text, Image, and Tabular Data" / "Copyright 2019 Amazon.com, Inc. or its affiliates. All Rights Reserved."

• https://cdn.jsdelivr.net/gh/autogluon/autogluon@master/README.md recorded 2026-09-26

  README "Train/Deploy AutoGluon in the Cloud": "AutoGluon Cloud (Recommended)", AutoGluon Deep Learning Containers, and "Amazon SageMaker Autopilot ... (Managed AutoGluon experience)"; no enterprise edition or license key for the library.

• https://data.jsdelivr.com/v1/packages/gh/autogluon/autogluon@master?structure=flat recorded 2026-09-26

  Flat file listing of master, 1,151 files under core, tabular, timeseries, multimodal, features and common, with no ee, enterprise, commercial or pro directory.

Measured on monthly PyPI downloads of autogluon.core, the package every AutoGluon module depends on, so that installs of the tabular, time-series and multimodal parts are each counted once; the autogluon meta-package alone would undercount.

• https://pypistats.org/api/packages/autogluon.core/recent recorded 2026-09-26

  last_month 185,210 downloads of autogluon-core

• https://pypistats.org/api/packages/autogluon/recent recorded 2026-09-26

  last_month 67,860 downloads of the autogluon meta-package

AutoGluon does the whole prediction task for you: it chooses and trains candidate models, including pretrained tabular foundation models, and stacks them into an ensemble, across tables, time series and mixed image and text data. It is the most complete automation in this category and the point the other products here are compared against.

• https://auto.gluon.ai/stable/tutorials/tabular/tabular-essentials.html recorded 2026-09-27

  Tabular essentials: "presets='best', which allows AutoGluon to automatically construct powerful model ensembles based on stacking/bagging".

• https://auto.gluon.ai/stable/tutorials/tabular/tabular-foundational-models.html recorded 2026-09-27

  Foundation-models tutorial: "Mitra - AutoGluon's own tabular foundation model, with fully open weights", "TabICLv2", "TabPFNv2", with a table of the tabular foundation models AutoGluon can fit (TabDPT, TabPFNv2, TabICL, Mitra, RealTabPFN-2.5 and others).

• https://cdn.jsdelivr.net/gh/autogluon/autogluon@master/README.md recorded 2026-09-26

  README: "AutoGluon takes care of that: it finds the combination of models that works best for your use case."; predictors TabularPredictor, TimeSeriesPredictor, MultiModalPredictor.