#55th of 7 in ML frameworks and libraries
keras
Multi-backend deep learning library running on JAX, TensorFlow and PyTorch
- Stars
- 64.4k
- License
- Apache-2.0
- Last commit
- Oct 2026
- Last release
- Jul 2026
- Language
- Python
Checked on GitHub.
Overview
Keras 3 is a high-level Python API for building and training neural networks. The backend is chosen with the KERAS_BACKEND variable or ~/.keras/keras.json. It trains on JAX, TensorFlow or PyTorch, and OpenVINO is supported for inference only. It is meant as a drop-in replacement for tf.keras and accepts tf.data pipelines and PyTorch DataLoaders as input.
Who it is for: ML engineers who want one model API across JAX, TensorFlow and PyTorch
Strengths
- Same model code runs on JAX, TensorFlow or PyTorch by switching one environment variable
- Keras models can be used inside native PyTorch Modules or JAX functions
- Accepts tf.data.Dataset and PyTorch DataLoader inputs regardless of backend
- Drop-in replacement for tf.keras when models are saved in the .keras format
Weaknesses
- Backend must be set before import and cannot be changed afterwards
- OpenVINO backend only supports model.predict(), no training
- Only Linux and macOS are listed as compatible; Windows needs WSL2
- Custom layers or train_step() need conversion to be backend-agnostic
What it needs
- GPU optional
- Needs tensorflow >=2.16.1, jax >=0.4.20, or torch >=2.1.0 (one backend), openvino 2026.2.0 (inference only)
- Models: JAX, TensorFlow, PyTorch, OpenVINO (inference only)
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| #6 | scikit-learnPython library of classical machine learning algorithms built on NumPy and SciPy | 69 out of 100 |