mathworks/matlab-deep-learning

MATLAB Deep Learning Docker Container

Speed up your deep learning applications by training neural networks in the MATLAB® Deep Learning Container. This container is designed to take full advantage of high-performance NVIDIA® GPUs. It provides a simple and flexible solution to use MATLAB for deep learning workflows in cloud environments such as AWS® or Microsoft® Azure®.

Supported tags

Quick Launch Instructions

This section describes an example workflow to pull the R2026a MATLAB Deep Learning image and launch an interactive MATLAB session from the image.

To pull the R2026a MATLAB image to your machine, execute:

console
docker pull mathworks/matlab-deep-learning:r2026a

To launch the container with the -browser option, execute:

console
docker run -it --rm -p 8888:8888 --shm-size=512M mathworks/matlab-deep-learning:r2026a -browser

Executing this command will display a URL on which you can access MATLAB, for example:

console
http://localhost:8888/index.html

For more information on running the container, see the section on How to use this image.

What is MATLAB?

https://www.mathworks.com/products/matlab.html is a programming platform designed for engineers and scientists. It combines a desktop environment tuned for iterative analysis and design processes with a programming language that expresses matrix and array mathematics directly. For more information, https://www.mathworks.com/discovery/what-is-matlab.html.

The MATLAB Deep Learning Container provides algorithms, pretrained models, and apps to create, train, visualize, and optimize deep neural networks. You can also access tools for image and signal processing, text analytics, and automatically generating C and CUDA® code for deployment on NVIDIA® GPUs in data centers and embedded systems. Specifically, this container provides an Ubuntu-based image with an installation of MATLAB and the following toolboxes:

• Computer Vision Toolbox™
• Deep Learning Toolbox™
• GPU Coder™
• Image Processing Toolbox™
• MATLAB Coder™
• Parallel Computing Toolbox™
• Signal Processing Toolbox™
• Statistics and Machine Learning Toolbox™
• Text Analytics Toolbox™

and the following Support Packages:

• Deep Learning Toolbox Converter for TensorFlow Models
• Deep Learning Toolbox Converter for ONXX Models Format
• Deep Learning Toolbox Importer for Caffe Models
• Deep Learning Toolbox Model for AlexNet Network
• Deep Learning Toolbox Model for GoogLeNet Network
• Deep Learning Toolbox Model for Inception-v3 Network
• Deep Learning Toolbox Model for Inception-ResNet-v2 Network
• Deep Learning Toolbox Model for ResNet-18 Network
• Deep Learning Toolbox Model for ResNet-50 Network
• Deep Learning Toolbox Model for ResNet-101 Network
• GPU Coder Interface for Deep Learning Libraries
• MATLAB Coder Interface for Deep Learning Libraries
• (since R2023a) Deep Learning Toolbox Verification Library

Configure your license

To use the MATLAB Deep Learning Container, you need a license for the MathWorks® products in the container.

To train deep learning models, you need a license for MATLAB, Deep Learning and Parallel Computing toolboxes. If you are licensed to use the additional products in the container, its functionality is extended.

On public cloud instances like Amazon EC2®, you can use a license that is enabled for cloud use. For on-premise DGX use, you can use a concurrent license by specifying the location of the network license manager when you run the container. Individual and Campus-Wide licenses are already configured for cloud use. For other license types, contact your license administrator. You can identify your license type and administrator by viewing your https://www.mathworks.com/login. Administrators can consult https://www.mathworks.com/help/install/administer-network-licenses.html.

How to use this image

This section describes the different options you can use to run the container, depending on your use case. Some options allow you to interact with MATLAB via the command line interface while others let you interact with the MATLAB desktop.

Run MATLAB with GPUs on your host machine

Before you start the container, check that your graphics driver is up to date. See https://www.mathworks.com/help/parallel-computing/gpu-computing-requirements.html for details.

To start the container and run MATLAB with GPUs on your host machine, execute:

console
$ docker run --gpus all -it --rm --shm-size=512M mathworks/matlab-deep-learning:r2026a

By default, a container does not have access to hardware resources of its host. To enable the container to access the GPUs of the host system, use the --gpus flag when you execute the docker run command. Set this flag to all if you want the container to have access to all the GPUs of the host machine.

For more information, see https://docs.docker.com/engine/reference/commandline/container_run/#gpus.

Run MATLAB in an interactive command prompt

To start the container and run MATLAB in an interactive command prompt, execute:

console
$ docker run -it --rm mathworks/matlab-deep-learning:r2026a

Run MATLAB non-interactively in batch mode

To start the container and run the MATLAB command RAND, execute:

console
$ docker run --rm -e MLM_LICENSE_FILE=27000@MyLicenseServer mathworks/matlab-deep-learning:r2026a -batch rand

where you must replace 27000@MyLicenseServer with the correct port number and DNS address for your network license manager.

Alternatively, if your system administrator provides you with a license file, you can mount the license file to the container and point MLM_LICENSE_FILE to the license file path in the container. For example, to start the container and run the MATLAB command RAND with a license file, execute:

console
$ docker run --rm -v /path/to/local/license/file:/licenses/license.lic -e MLM_LICENSE_FILE=/licenses/license.lic mathworks/matlab-deep-learning:r2026a -batch rand

If a valid license file is provided, the container runs the command RAND in MATLAB and exits. For more information on using the network license manager, see https://github.com/mathworks-ref-arch/matlab-dockerfile#use-the-network-license-manager.

Run MATLAB and interact with it via a web browser

To start the container, execute:

console
$ docker run -it --rm -p 8888:8888 --shm-size=512M mathworks/matlab:r2026a -browser

Running the above command prints text to your terminal containing the URL to access MATLAB. For example:

console
MATLAB can be accessed at:
http://localhost:8888/index.html

Enter the provided URL into a web browser. If prompted to do so, enter credentials for a MathWorks account associated with a MATLAB license. If you are using a network license manager, change to the Network License Manager tab and enter the license server address instead. After you provide your license information, a MATLAB session will start in the browser (this may take several minutes).

To modify the behavior of MATLAB when launched with -browser flag, pass environment variables to the docker run command. For more information, see https://github.com/mathworks/matlab-proxy/blob/main/Advanced-Usage.md.

Some browsers may not support this workflow. For more information, see https://www.mathworks.com/support/requirements/browser-requirements.html.

NOTE: The -browser flag is supported by Docker® images starting from MATLAB R2022a. To access MATLAB in a web browser in custom Docker images with MATLAB or older MATLAB Docker images, for example R2021b, see https://github.com/mathworks/matlab-proxy/blob/main/examples/Dockerfile.

Run MATLAB in desktop mode and interact with it via VNC

To start the MATLAB desktop, execute:

console
$ docker run -it --rm -p 5901:5901 -p 6080:6080 --shm-size=512M mathworks/matlab-deep-learning:r2026a -vnc

To connect to the MATLAB desktop, either:

1. Point a browser to port 6080 of the Docker host machine running this container (http://hostname:6080)
2. Use a VNC client to connect to display 1 of the Docker host machine (hostname:1)

The VNC password is matlab by default. Use the PASSWORD environment variable to change it. If you are using a cloud service provider or your host or client machines are protected by a firewall, you must set up SSH tunnels between your client machine and the Docker host to access the container desktop. For instructions, see the https://www.mathworks.com/help/cloudcenter/ug/create-encrypted-connection-to-remote-applications-and-containers.html.

Run MATLAB desktop using X11

To start the container and run MATLAB desktop using X11, execute:

console
$ xhost +
$ docker run -it --rm -e DISPLAY=$DISPLAY -v /tmp/.X11-unix:/tmp/.X11-unix:ro --shm-size=512M mathworks/matlab-deep-learning:r2026a

The MATLAB desktop window will open on your machine. Note that the command above works only on a Linux operating system with X11 and its dependencies installed.

Run MATLAB with startup options

To override the default behavior of the container and run MATLAB with any set of arguments, such as -logfile, execute:

console
$ docker run -it --rm mathworks/matlab-deep-learning:r2026a -logfile "logfilename.log"

Environment variables

When executing the command docker run you can specify environment variables using the option -e. This section describes all the environment variables that you can specify.

MLM_LICENSE_FILE

Use this environment variable when you want to use either a license file or a network license manager to license MATLAB.

Example:

docker run -it --rm -e MLM_LICENSE_FILE=27000@MyLicenseServer mathworks/matlab-deep-learning:r2026a

docker run -it --rm -e MLM_LICENSE_FILE=/license.dat mathworks/matlab-deep-learning:r2026a

PROXY_SETTINGS

Use this environment variable when you want to use a proxy server to connect to the MathWorks licensing servers.

Example:

docker run -it --rm -e PROXY_SETTINGS=<proxy-server-address> mathworks/matlab-deep-learning:r2026a

You can specify the proxy server address using any of the following forms:

• hostname:12345
• shorthostname:12345
• http://hostname:12345
• http://username:password@hostname:12345
• IPaddress:12345

where hostname is the fully qualified domain name, shorthostname is the relative domain name, and *** is the port number.

PASSWORD

Use this environment variable when you want to change the password used to access the VNC server.

Example:

docker run -it --rm -e PASSWORD=ILoveMATLAB -p 5901:5901 -p 6080:6080 --shm-size=512M mathworks/matlab-deep-learning:r2026a -vnc

Install updates, toolboxes, add-ons in the container and save changes

You can install the latest MATLAB updates or install additional toolboxes and add-ons in this container. For more information, see https://www.mathworks.com/help/cloudcenter/ug/install-updates-toolboxes-support-packages-and-add-ons-in-containers.html.

Security reporting

Follow these instructions to https://github.com/mathworks-ref-arch/container-images/blob/master/SECURITY.md.

Additional information

This container includes commercial software products of The MathWorks, Inc. ("MathWorks Programs") and related materials. MathWorks Programs are licensed under the MathWorks Software License Agreement, available in the MATLAB installation in this container. Related materials in this container are licensed under separate licenses which can be found in their respective folders.

To learn more about MATLAB containers, see https://www.mathworks.com/help/cloudcenter/ug/matlab-container-on-docker-hub.html.

To see the source files used to build this Docker image, see the https://github.com/mathworks-ref-arch/container-images/tree/main/matlab.

To provide suggestions for additional features or capabilities, https://www.mathworks.com/solutions/cloud.html.

Technical support

If you require assistance or have a request for additional features or capabilities, contact https://www.mathworks.com/support/contact_us.html.

Copyright 2021-2026 The MathWorks, Inc.