keras

# Keras 3: Deep Learning for Humans

Keras 3 is a multi-backend deep learning framework, with support for JAX, TensorFlow, PyTorch, and OpenVINO (for inference-only).
Effortlessly build and train models for computer vision, natural language processing, audio processing,
timeseries forecasting, recommender systems, etc.

- **Accelerated model development**: Ship deep learning solutions faster thanks to the high-level UX of Keras
and the availability of easy-to-debug runtimes like PyTorch or JAX eager execution.
- **State-of-the-art performance**: By picking the backend that is the fastest for your model architecture (often JAX!),
leverage speedups ranging from 20% to 350% compared to other frameworks. [Benchmark here](https://keras.io/getting_started/benchmarks/).
- **Datacenter-scale training**: Scale confidently from your laptop to large clusters of GPUs or TPUs.

Join nearly three million developers, from burgeoning startups to global enterprises, in harnessing the power of Keras 3.


## Installation

### Install with pip

Keras 3 is available on PyPI as `keras`. Note that Keras 2 remains available as the `tf-keras` package.

1. Install `keras`:

```
pip install keras --upgrade
```

2. Install backend package(s).

To use `keras`, you should also install the backend of choice: `tensorflow`, `jax`, or `torch`. Additionally,
The `openvino` backend is available with support for model inference only.

3. (Optional) Install remote file access support.

To save to and load from Google Cloud Storage (`gs://` paths) without TensorFlow, install the `gcs` extra:

```
pip install "keras[gcs]"
```

### Local installation

#### Minimal installation

Keras 3 is compatible with Linux and macOS systems. For Windows users, we recommend using WSL2 to run Keras.
To install a local development version:

1. Install dependencies:

```
pip install -r requirements.txt
```

2. Run installation command from the root directory.

```
python pip_build.py --install
```

3. Run API generation script when creating PRs that update `keras_export` public APIs:

```
./shell/api_gen.sh
```

## Backend Compatibility Table

The following table lists the minimum supported versions of each backend for the latest stable release of Keras (v3.x):

| Backend    | Minimum Supported Version |
|------------|---------------------------|
| TensorFlow | 2.16.1                    |
| JAX        | 0.4.20                    |
| PyTorch    | 2.6.0                     |
| OpenVINO   | 2026.2.0                  |

#### Adding GPU support

The `requirements.txt` file will install a CPU-only version of TensorFlow, JAX, and PyTorch. For GPU support, we also
provide a separate `requirements-{backend}-cuda.txt` for TensorFlow, JAX, and PyTorch. These install all CUDA
dependencies via `pip` and expect a NVIDIA driver to be pre-installed. We recommend a clean Python environment for each
backend to avoid CUDA version mismatches. As an example, here is how to create a JAX GPU environment with `conda`:

```shel