NVIDIA Isaac Sim™ Development Workstation (Linux) is preconfigured with the software tools for accelerating and scaling your robotic simulation workloads from synthetic data generation to software-in-loop testing of your robotics stack.
NVIDIA Isaac Sim™ is a reference application built on the NVIDIA Omniverse™ platform that enables developers to simulate and test AI-driven robotics solutions in physically based virtual environments.
The NVIDIA Isaac Sim™ Development Workstation (Linux) AMI enables users to provision a workstation with graphical capabilities within AWS, eliminating the need to run Omniverse-based applications locally on an RTX-enabled workstation.
The NVIDIA Isaac Sim™ Development Workstation (Linux) AMI includes all the essential development tools and drivers to scale your robotics simulations:
NVIDIA Isaac Sim™
Visual Studio Code
Docker
Certified NVIDIA GPU drivers
This AMI uses the EC2 g6e instance featuring NVIDIA L40s RTX and the g7e instance featuring NVIDIA RTX Pro 6000 GPUs.
This GPU-optimized AMI for Isaac Sim™ is free to use on AWS. (Infrastructure costs will apply.)
Use of the Isaac Sim™ workstation requires membership in the NVIDIA developers program, which developers can sign up for free at https://developer.nvidia.com. NVIDIA Isaac Sim is a free reference application built on NVIDIA Omniverse Kit. With a membership to the NVIDIA Developer Program, a free developer license is provided for Kit, which allows Isaac Sim to be freely used for non-production use.
The NICE DCV client is required to connect to this virtual machine.
Highlights
All the essential development tools and drivers for NVIDIA Isaac Sim are pre-configured and ready to use.
AWS Marketplace now accepts line of credit payments through the PNC Vendor Finance program. This program is available to select AWS customers in the US, excluding NV, NC, ND, TN, & VT.
The software itself is free. You pay only for the AWS EC2 instance that runs the workstation, billed by the hour. Pricing follows the instance you choose across three families: g6e, g7e, and g7. Within each family, sizes run from xlarge up to 48xlarge. Larger sizes add more compute, GPU, and memory, so the hourly rate rises with size. Pick the family and size that match your simulation workload. You can start small and move to a larger instance as your needs grow.
Top-of-mind questions for buyers
What do I actually get for each hourly instance, and what does the software itself add?
Each hourly rate covers one running AWS EC2 GPU instance from the g6e, g7e, or g7 family. The instance provides the GPU, CPU, and memory that run the simulation. The Isaac Sim software comes pre-installed on the workstation at no software charge.
Am I charged when the workstation instance is stopped or idle?
Hourly charges apply while the instance runs. A fully stopped instance stops accruing hourly compute charges. Underlying AWS storage for the workstation disk may still bill while stopped. The software carries no charge in any state.
How do I choose between the g6e, g7e, and g7 instance families?
All three families run the same pre-configured Isaac Sim workstation. They differ in GPU, CPU, and memory per size. Match the family and size to your simulation load. Larger sizes run heavier scenes and more sensors, and their hourly rate rises with size.
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An AMI is a virtual image that provides the information required to launch an instance. Amazon EC2 (Elastic Compute Cloud) instances are virtual servers on which you can run your applications and workloads, offering varying combinations of CPU, memory, storage, and networking resources. You can launch as many instances from as many different AMIs as you need.
Version release notes
NVIDIA Isaac Sim Development Workstation (Linux)- 2026 Q2 Refresh
Additional details
Usage instructions
Prerequisites:
To create and use Workstation instances you will need:
AWS Account
AWS Key Pair created for authentication
AWS security group to control access to ports
Port 22 for SSH
Port 8443 for connecting with NICE DCV
PuTTY application is installed. This enables SSH connection to the AMI instance from Windows.
NICE DCV client installed
Launch the AMI:
Navigate to the AWS Omniverse AMI marketplace product page
To create your own AWS instance, click the View purchase options button
If you have not already subscribed to the software, you will need to Accept Terms the first time
When the subscription is completed, click the Continue to Configuration button
On the Configure this software page list, click the Continue to Launch button
On the Subscribe to page click Launch your software
Under Setup click the Launch from EC2 Console option
Under Launch click the Launch from EC2 button
On the Launch an instance page
Name your instance
The AMI from catalog is automatically set to the correct AMI (no action required)
Choose the Instance type. (g6e, g7, and g7e instance types are supported.)
Set Key Pair (login) select or create your Key Pair file. For Linux use .ppk. For Windows use .pem
Set Network settings select either Select existing security group or Create security group option. For more information, select the info link
Set Configure storage to a minimum of 512GiB
In the Summary section on the right side of the page, click Launch instance
On the Instances page, select the new Instance ID to display the information panel
It takes a few minutes for the instance state to change from Initializing to Running
Linux only: Use PuTTY to connect to the running instance and NICE DCV to display the desktop GUI:
Copy the Public IP Address of your instance from the Instance summary panel
Start the PuTTY application
Paste the Public IP address in the Host Name (or IP address) field
Under Category click Connection > SSH > Auth > Credentials then browse to your Key Pair location containing the .ppk file
Click Open to connect to the instance
When prompted to login as enter ubuntu as the username
In order to RDP into the AMI using NICE DCV, the default password must be changed using the sudo passwd ubuntu command. The output received should follow the format Session: console (owner:ubuntu type:console)
To ensure that a DCV session is running on the intended AWS instance enter the sudo dcv list-sessions command
Start the NICE DCV client application
Enter the public IP address assigned to your AWS instance in the Hostname/IP Address field in NICE DCV, then click Connect
Click Trust and Connect when prompted
Enter ubuntu as the username in the Username field
Enter the password that was previously set in the Password field
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NVIDIA AI Enterprise is an end-to-end, cloud-native software platform that accelerates data science pipelines and streamlines development and deployment of production-grade AI applications, including generative AI.
The NVIDIA GPU-Optimized AMI is an environment for running the GPU-accelerated deep learning and HPC containers from the NVIDIA NGC catalog. The deep learning containers from NGC catalog require this AMI for GPU acceleration on AWS P5d, P4d, P3, G4dn, G5 GPU instances.
The NVIDIA Omniverse™ Development Workstation (Linux) provides a pre-configured environment containing the software and drivers required to accelerate Omniverse development.
NVIDIA RTX Virtual Workstation delivers unmatched NVIDIA RTX performance for AI-enhanced and graphics-intensive applications in the cloud, offering workstation-grade power. Key advantages include ISV certifications with the NVIDIA RTX platform, streamlined IT infrastructure management, exceptional scalability, and access to the latest NVIDIA vGPU drivers and security patches.
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