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| 15 min |
| Last updated: |
| 4 May 2026 |
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This guide shows you how to install and use the tool with the most common configuration. For advanced options and complete reference information, see the official documentation. Some install guides also include optional next steps to help you explore related workflows or integrations.
Anaconda Distribution is a popular open-source Python distribution. It includes access to a repository with over 8,000 open-source data science and machine learning packages.
You can use the conda command to quickly install and use Python packages.
In this guide, you’ll learn how to install and use Anaconda Distribution on an Arm server.
Confirm you are using an Arm machine by running:
uname -m
The output is similar to:
aarch64
If you see a different result, you are not using an Arm computer running 64-bit Linux.
The installer requires some desktop related libraries. You can meet the dependencies by installing a desktop environment by running the commands for your Linux distribution.
sudo apt update
sudo apt install xfce4 -y
sudo amazon-linux-extras install mate-desktop1.x
To download Anaconda Distribution, run:
The following commands use Anaconda version 2025.12.2. The same commands work with other versions. Replace the file used in these steps with the file for your version of choice. To find the latest version, see Anaconda Distribution release notes .
curl -O https://repo.anaconda.com/archive/Anaconda3-2025.12-2-Linux-aarch64.sh
Depending on the version, the downloaded filename will be of the form Anaconda3-20XX.YY-Linux-aarch64.sh where the XX and YY values represent the year and month of the latest release.
Run the downloaded install script.
The default installation directory is $HOME/anaconda3. Change the installation directory as needed using the -p option to the install script.
To review the license terms before accepting, remove -b.
sh ./Anaconda3-2025.12-2-Linux-aarch64.sh -b
The install takes a couple of minutes to complete.
The batch installation won’t set up the shell. To set up the shell, run:
eval "$($HOME/anaconda3/bin/conda shell.bash hook)"
Test Anaconda Distribution by running the following TensorFlow and PyTorch examples.
Create a new conda environment named tf and install TensorFlow:
conda create -n tf tensorflow -y
Activate the new environment:
conda activate tf
The shell prompt will now show the tf environment.
(tf) ubuntu@ip-10-0-0-251:~$
Run a simple check to make sure TensorFlow is working.
Using a text editor, copy and paste the code below into a text file named tf.py:
import tensorflow as tf
print(tf.__version__)
print(tf.reduce_sum(tf.random.normal([1000,1000])))
exit()
Run the example code:
python ./tf.py
The output is similar to:
2.12.0
tf.Tensor(342.34387, shape=(), dtype=float32)
Create a new conda environment named torch and install PyTorch:
conda create -n torch pytorch -y
Activate the new environment:
conda activate torch
Using a text editor, copy and paste the following code into a text file named pytorch.py:
import torch
print(torch.__version__)
x = torch.rand(5,3)
print(x)
exit()
Run the example code:
python ./pytorch.py
The output is similar to:
2.1.0
tensor([[0.9287, 0.5931, 0.0239],
[0.3402, 0.9447, 0.8897],
[0.3161, 0.3749, 0.6848],
[0.8091, 0.6998, 0.7517],
[0.2873, 0.0549, 0.2914]])
You are ready to use Anaconda Distribution.
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