Keras

On the record

Backends

Keras 3 runs on JAX, TensorFlow, and PyTorch, and offers an OpenVINO backend for inference.keras.io · read 30 Sep 2026

Community support

Keras provides a Google Group, community meetings, Discord, and a Google AI Forum for discussion and updates.keras.io · read 30 Sep 2026

Compatibility limit

The Keras distribution API supports model parallelism through JAX; TensorFlow and PyTorch support is described as coming soon on the Keras 3 launch page.keras.io · read 30 Sep 2026

Contributions

The Keras site invites code, ideas, and feedback and links to its roadmap, contribution guide, and GitHub repository.keras.io · read 30 Sep 2026

Data inputs

Keras 3 training, evaluation, and prediction routines support tf.data.Dataset, PyTorch DataLoader, NumPy arrays, and Pandas dataframes.keras.io · read 30 Sep 2026

Data integrations

Keras models can use NumPy arrays, Pandas dataframes, TensorFlow tf.data datasets, PyTorch DataLoaders, and Keras PyDataset objects.keras.io · read 30 Sep 2026

Distribution

The distribution API supports data and model parallelism and is currently implemented for the JAX backend.keras.io · read 30 Sep 2026

Examples

The getting-started page offers over 150 example notebooks covering computer vision, natural language processing, and generative AI.keras.io · read 30 Sep 2026

Frameworks

Keras 3 runs on JAX, TensorFlow, or PyTorch, and supports OpenVINO for inference only.keras.io · read 30 Sep 2026

Hyperparameter tuning

KerasTuner includes Bayesian Optimization, Hyperband, and Random Search algorithms and can be extended with new search algorithms.keras.io · read 30 Sep 2026

Installation

Keras installs from PyPI with pip install --upgrade keras; using Keras 3 also requires installing a backend framework.keras.io · read 30 Sep 2026

Intended users

Keras describes its audience as machine learning engineers and presents guides and examples for model development across common ML use cases.keras.io · read 30 Sep 2026

Model building

Developers can build models with the Sequential API, the Functional API, or model subclassing.keras.io · read 30 Sep 2026

Model interoperability

Keras 3 models can be used as PyTorch modules, exported as TensorFlow SavedModels, or instantiated as stateless JAX functions.keras.io · read 30 Sep 2026

Model portability

Keras 3 models can be used as PyTorch modules, exported as TensorFlow SavedModels, or instantiated as stateless JAX functions.keras.io · read 30 Sep 2026

Pretrained models

KerasHub provides implementations of popular model architectures and pretrained checkpoints from Kaggle Models for training and inference.keras.io · read 30 Sep 2026

Product

Keras is a Python deep learning API focused on readable, maintainable code and fast model iteration.keras.io · read 30 Sep 2026

Purpose

Keras is a Python deep learning API designed to make model development concise, readable, and easier to debug.keras.io · read 30 Sep 2026

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