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Install OpenVINO™ Runtime on Linux From YUM Repository

docs/articles_en/get-started/install-openvino/install-openvino-yum.rst

2026.1.25.3 KB
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Install OpenVINO™ Runtime on Linux From YUM Repository

.. meta:: :description: Learn how to install OpenVINO™ Runtime on Linux operating system, using the YUM repository.

.. note::

Note that the YUM distribution:

  • offers both C/C++ and Python APIs
  • is dedicated to Linux users only
  • additionally includes code samples

Before installing OpenVINO, see the :doc:System Requirements page <../../../about-openvino/release-notes-openvino/system-requirements>.

Install OpenVINO Runtime ########################

Step 1: Set Up the Repository +++++++++++++++++++++++++++++

  1. Create a YUM repository file (openvino.repo) in the /tmp directory as a normal user:

    .. code-block:: sh

    tee > /tmp/openvino.repo << EOF [OpenVINO] name=Intel(R) Distribution of OpenVINO baseurl=https://yum.repos.intel.com/openvino enabled=1 gpgcheck=1 repo_gpgcheck=1 gpgkey=https://yum.repos.intel.com/intel-gpg-keys/GPG-PUB-KEY-INTEL-SW-PRODUCTS.PUB EOF

  2. Move the new openvino.repo file to the YUM configuration directory, i.e. /etc/yum.repos.d:

    .. code-block:: sh

    sudo mv /tmp/openvino.repo /etc/yum.repos.d

  3. Verify that the new repository is set up properly.

    .. code-block:: sh

    yum repolist | grep -i openvino

    You will see the available list of packages.

To list available OpenVINO packages, use the following command:

.. code-block:: sh

yum list 'openvino*'

Step 2: Install OpenVINO Runtime Using the YUM Package Manager ++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++

Install OpenVINO Runtime

.. tab-set::

.. tab-item:: The Latest Version :sync: latest-version

  Run the following command:

  .. code-block:: sh

     sudo yum install openvino

.. tab-item:: A Specific Version :sync: specific-version

  Run the following command:

  .. code-block:: sh

     sudo yum install openvino-<VERSION>.<UPDATE>.<PATCH>

  For example:

  .. code-block:: sh


     sudo yum install openvino-2026.1.0

Check for Installed Packages and Version

Run the following command:

.. code-block:: sh

yum list installed 'openvino*'

.. note::

You can additionally install Python API using one of the alternative methods (:doc:conda <install-openvino-conda> or :doc:pip <install-openvino-pip>).

Congratulations! You've just Installed OpenVINO! For some use cases you may still need to install additional components. Check the :doc:list of additional configurations <./configurations> to see if your case needs any of them.

With the YUM distribution, you can build OpenVINO sample files, as explained in the :doc:guide for OpenVINO sample applications <../../../get-started/learn-openvino/openvino-samples>. For C++ and C, just run the build_samples.sh script:

.. tab-set::

.. tab-item:: C++ :sync: cpp

  .. code-block:: sh

     /usr/share/openvino/samples/cpp/build_samples.sh

.. tab-item:: C :sync: c

  .. code-block:: sh

     /usr/share/openvino/samples/c/build_samples.sh

Uninstalling OpenVINO Runtime ##############################

To uninstall OpenVINO Runtime via YUM, run the following command based on your needs:

.. tab-set::

.. tab-item:: The Latest Version :sync: latest-version

  .. code-block:: sh

     sudo yum autoremove openvino

.. tab-item:: A Specific Version :sync: specific-version

  .. code-block:: sh

     sudo yum autoremove openvino-<VERSION>.<UPDATE>.<PATCH>

  For example:

  .. code-block:: sh

     sudo yum autoremove openvino-2026.1.0

What's Next? #############

Now that you've installed OpenVINO Runtime, you're ready to run your own machine learning applications! Learn more about how to integrate a model in OpenVINO applications by trying out the following tutorials:

  • Try the :doc:C++ Quick Start Example <../../../get-started/learn-openvino/openvino-samples/get-started-demos> for step-by-step instructions on building and running a basic image classification C++ application.

    .. image:: https://user-images.githubusercontent.com/36741649/127170593-86976dc3-e5e4-40be-b0a6-206379cd7df5.jpg :width: 400

  • Visit the :ref:Samples <code samples> page for other C++ example applications to get you started with OpenVINO, such as:

    • :doc:Basic object detection with the Hello Reshape SSD C++ sample <../../../get-started/learn-openvino/openvino-samples/hello-reshape-ssd>
    • :doc:Object classification sample <../../../get-started/learn-openvino/openvino-samples/hello-classification>

You can also try the following things:

  • Learn more about :doc:OpenVINO Workflow <../../../openvino-workflow>.
  • To prepare your models for working with OpenVINO, see :doc:Model Preparation <../../../openvino-workflow/model-preparation>.
  • See pre-trained deep learning models on Hugging Face <https://huggingface.co/OpenVINO>__.
  • Learn more about :doc:Inference with OpenVINO Runtime <../../../openvino-workflow/running-inference>.
  • See sample applications in :doc:OpenVINO toolkit Samples Overview <../../../get-started/learn-openvino/openvino-samples>.
  • Take a glance at the OpenVINO product home page <https://software.intel.com/en-us/openvino-toolkit>__ .