> ## Documentation Index
> Fetch the complete documentation index at: https://anaconda.com/docs/llms.txt
> Use this file to discover all available pages before exploring further.

# TensorFlow

[TensorFlow](https://www.tensorflow.org/) enables your data science, machine learning, and artificial intelligence workflows. This page shows how to install TensorFlow using the conda <Tooltip tip="A collection of software tools that automates the process of installing, updating, configuring, and removing packages. Also known as a package management system.">package manager</Tooltip> included in Anaconda and Miniconda.

TensorFlow CPU with conda is supported on 64-bit Windows 7 or later, 64-bit Ubuntu Linux 16.04 or later, and 64-bit macOS 12.0 or later.

TensorFlow GPU with conda is only available though version 2.4.1 (2021). For the latest TensorFlow GPU installation, follow the [installation instructions on the TensorFlow website](https://www.tensorflow.org/install/pip#step-by-step_instructions).

## Install TensorFlow

1. Download and install [Anaconda](/getting-started/anaconda/install/overview) or [Miniconda](/getting-started/miniconda/install/overview).
2. Open a terminal application and use the default bash shell.
3. Choose a name for your TensorFlow environment, such as "tf".
4. Use the following commands to install the current release of TensorFlow. CPU-only is recommended for beginners.

   <Tabs>
     <Tab title="CPU-only TensorFlow">
       ```sh theme={null}
       conda create --name tf tensorflow
       conda activate tf
       ```
     </Tab>

     <Tab title="GPU TensorFlow">
       <Note>
         GPU TensorFlow is only available via conda for Windows and Linux.
       </Note>

       ```sh theme={null}
       conda create --name tf-gpu tensorflow-gpu
       conda activate tf-gpu
       ```
     </Tab>
   </Tabs>

TensorFlow is now installed and ready to use.

For using TensorFlow with a GPU, refer to the [TensorFlow documentation](https://www.tensorflow.org/guide/gpu), specifically the section on [device placement](https://www.tensorflow.org/guide/gpu#manual_device_placement).

## CUDA versions

GPU TensorFlow uses CUDA. For a version compatibility table for GPU TensorFlow on Linux, see [https://www.tensorflow.org/install/source#gpu](https://www.tensorflow.org/install/source#gpu). For Windows, see [https://www.tensorflow.org/install/source\_windows#gpu](https://www.tensorflow.org/install/source_windows#gpu).

GPU TensorFlow conda packages are currently only supported for Windows or Linux.

<Note>
  TensorFlow 2.10 was the last release that supported GPU on Windows Native.
</Note>

To install GPU TensorFlow with a non-default CUDA version like 9.0, run the following commands:

```sh theme={null}
conda create --name tf-gpu-cuda9 tensorflow-gpu cudatoolkit=9.0
conda activate tf-gpu-cuda9
```

## Nightly builds

Advanced users may want to install the latest nightly build of TensorFlow. These
nightly builds are unstable and are only available as pip packages on PyPI.

To install the nightly build of CPU-only TensorFlow:

```sh theme={null}
conda create --name tf-n python
conda activate tf-n
pip install tf-nightly
```

Or, to install the nightly build of GPU TensorFlow on Linux or Windows:

```sh theme={null}
conda create --name tf-n-gpu python
conda activate tf-n-gpu
pip install tf-nightly-gpu
```