Sold by: NVIDIA
Deployed on AWS
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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Overview
NVIDIA RTX Workstation performance: The latest GPU instances powered by NVIDIA RTX ray tracing and NVIDIA Virtual GPU technologies with support for professional graphics workloads such as 3D visualization and interactive rendering. ISV Certifications: Get proven NVIDIA RTX benefits from the cloud and leverage RTX ISV certifications. IT Speed and Agility. Spin up a GPU-accelerated virtual workstation in minutes, without having to manage endpoints or back-end infrastructure. Flexibility in the Cloud: Scale up and down as your business needs change and pay for only what you need based on hourly usage. Always-Up-to-Date: Your NVIDIA RTX Virtual Workstation image is always optimized with the latest patches and upgrades. Enterprise-Grade Security: Get the same RTX experience from anywhere, with the assurance that sensitive data is protected in the cloud with redundancy and compliance.
Highlights
- Fractional GPUs offerings powered by NVIDIA L4 Tensor Core GPUs are available from 1/8 to 1/2 GPU, providing scalable and cost-effective options for graphics workloads.
- Powering compute-intensive workloads such as real-time rendering, CAE, CAD, GIS, digital twin, virtual reality, and AI development
- Enabling geographically dispersed teams to collaborate in real-time with greater flexibility and business agility.
Details
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Delivery method
Delivery option
64-bit (x86) Amazon Machine Image (AMI)
Latest version
Operating system
Win2022 20348.169
Deployed on AWS
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Features and programs
Financing for AWS Marketplace purchases
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.
Pricing
This product is available free of charge. Free subscriptions have no end date and may be canceled any time.
Additional AWS infrastructure costs may apply. Use the AWS Pricing Calculator to estimate your infrastructure costs.
Vendor refund policy
Not refundable.
Legal
Vendor terms and conditions
Upon subscribing to this product, you must acknowledge and agree to the terms and conditions outlined in the vendor's End User License Agreement (EULA) .
Content disclaimer
Vendors are responsible for their product descriptions and other product content. AWS does not warrant that vendors' product descriptions or other product content are accurate, complete, reliable, current, or error-free.
Delivery details
64-bit (x86) Amazon Machine Image (AMI)
Amazon Machine Image (AMI)
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.
Additional details
Usage instructions
The GPU driver is already built-in, ready to use. Quickstart guide: https://docs.nvidia.com/vgpu/qvws/latest/qvws-quick-start-guide-amazon-web-services-ec2/index.html
Support
Vendor support
AWS infrastructure support
AWS Support is a one-on-one, fast-response support channel that is staffed 24x7x365 with experienced and technical support engineers. The service helps customers of all sizes and technical abilities to successfully utilize the products and features provided by Amazon Web Services.
Updated weekly
By Arara Solutions
By HP, Inc.
Top
10
In Media & Entertainment, Collaboration & Productivity
Top
10
In Image, Video
Top
10
In Collaboration & Productivity, Media & Entertainment, High Performance Computing
Sentiment is AI generated from actual customer reviews on AWS and G2
Functionality
Ease of use
Customer service
Cost effectiveness
Positive reviews
Mixed reviews
Negative reviews
AI generated from product descriptions
GPU Acceleration Technology
NVIDIA RTX ray tracing and NVIDIA Virtual GPU technologies with support for professional graphics workloads including 3D visualization and interactive rendering
Fractional GPU Allocation
Fractional GPU offerings powered by NVIDIA L4 Tensor Core GPUs available from 1/8 to 1/2 GPU for scalable graphics workloads
Supported Workload Types
Support for compute-intensive workloads including real-time rendering, CAE, CAD, GIS, digital twin, virtual reality, and AI development
ISV Certification Support
NVIDIA RTX ISV certifications enabling proven RTX benefits and compatibility with certified professional applications
Security and Compliance
Enterprise-grade security with data protection, redundancy, and compliance measures for cloud-based workstation access
Remote Desktop and Application Streaming
High-performance remote desktop and application streaming capability for accessing graphical interfaces and applications remotely.
GPU Driver Support
NVIDIA Tesla GPU Driver installed and configured for GPU-accelerated computing workloads.
Graphical User Interface
Gnome desktop environment providing a graphical user interface on Ubuntu 22.04 Server.
Operating System
Ubuntu 22.04 Server as the base operating system with long-term support.
Remote Display Protocol
Utilizes PCoIP protocol to stream interactive desktop displays between Amazon Web Services and end-user devices on Amazon G4 or G5 instances
Multi-Endpoint Connectivity
Supports connection from multiple endpoint types including PCoIP Zero Clients, PCoIP-enabled Thin Clients, PCs, Macs, laptops, and tablets
GPU Acceleration
Supports NVIDIA GPU acceleration on Amazon G4 and G5 instances for enhanced performance
Network Resilience
Maintains high performance across variable network conditions without requiring large file downloads
Image Quality Standards
Delivers true 4:4:4 color accuracy and lossless image quality for remote desktop streaming
Standard contract
No
Customer reviews
Manush Madan
A rock-solid, plug-and-play platform enabling scalable, reliable multimodal AI inference and fine-tuning while saving significant time, with minor room for improvement.
Reviewed on Jan 10, 2026
Review from a verified AWS customer
What is our primary use case?
My main use case for NVIDIA RTX Virtual Workstation involves using it for AI inference and also training LoRAs or fine-tuning models, where I am using generative AI for images and video using inference tools like ComfyUI and other Windows-based tools, and I am also trying to fine-tune certain models.
NVIDIA RTX Virtual Workstation helps with my generative AI workflows by coming pre-loaded with the right drivers, and I use the CUDA toolkit and ComfyUI mostly for inference while utilizing open models.
For audio tools, I am fine-tuning the model that is also open source, which makes stability and predictability the best aspects for my use case.
I use all these generative AIs on my projects as well as my clients' projects, and I even fine-tune from the results and data provided by the client.
What is most valuable?
The best features NVIDIA RTX Virtual Workstation offers are that it is plug-and-play and ready to use, meaning I can just load my applications, my ComfyUI application, and other software without needing to worry about additional setups, making reliability and stability stand out for me.
The plug-and-play aspect has helped me significantly by firstly reducing time, and secondly, I need not hire additional specialists because it is easy for everyone to use.
The reliability is impressive as it works every time, and I can switch between instances, between G5 and G4 instances, depending upon my workloads, ensuring zero crashes and consistent performance.
NVIDIA RTX Virtual Workstation has positively impacted my organization by providing two main benefits: time-saving and improved quality, allowing me to complete tasks that would take days in just hours while using different open models that update regularly.
A specific example of a project where I saw a significant difference in time saved is during the prep work for a video game I am developing. The characters, the settings, and all workflows are done quickly, allowing me to present it to my client so they can develop a full storyline and environment, accomplishing in two weeks what typically takes months and with better quality than before.
What needs improvement?
Sometimes the CUDA toolkit had different versions that would not run, but updating it or running it in a virtual Python environment resolves the issue, which could be a Windows problem. These are minor issues, nothing major.
I would like to see support for more NICE DCV, specifically Amazon NICE DCV on the go, as I install remote desktop features beyond what is provided by Windows.
For how long have I used the solution?
I have been using NVIDIA RTX Virtual Workstation for more than two years now on different G5 and G6 instances.
What do I think about the stability of the solution?
NVIDIA RTX Virtual Workstation is very stable.
What do I think about the scalability of the solution?
NVIDIA RTX Virtual Workstation's scalability is excellent as I can switch between instances depending on workload, using smaller G4 instances or scaling up to maximum G6E instances, and it works flawlessly.
How are customer service and support?
Customer support is great.
How would you rate customer service and support?
Positive
Which solution did I use previously and why did I switch?
Previously, I used NICE DCV initially, then I switched to regular vanilla Windows instances before finally adopting NVIDIA RTX Virtual Workstation, which is the best among the options.
Before choosing NVIDIA RTX Virtual Workstation, I evaluated other options, including regular Windows servers where I had to install all the drivers myself, which was cumbersome, and NICE DCV instances because they came with Amazon DCV installed. However, I faced certain driver and CUDA issues before finally finding NVIDIA RTX Virtual Workstation, which runs out of the box and is plug-and-play.
How was the initial setup?
Deploying NVIDIA RTX Virtual Workstation in my environment is very easy. I just buy it from the AWS Marketplace , spin up the instance, and it is ready to go.
My experience with the configuration process is good as it is fairly straightforward and easy.
What was our ROI?
I have seen a return on investment in terms of time saved and better quality, with fewer employees needed to accomplish the same work, enabling me to handle more projects simultaneously.
What's my experience with pricing, setup cost, and licensing?
My experience with pricing, setup cost, and licensing is good as it is pretty straightforward and easy to understand.
What other advice do I have?
I purchased NVIDIA RTX Virtual Workstation through the AWS Marketplace .
I rate NVIDIA RTX Virtual Workstation a five on a scale of one to five.
I give it a five because it provides everything I need, including predictability, stability, and reliability, all while being plug-and-play.
NVIDIA RTX Virtual Workstation integrates flawlessly with other AWS services I use, allowing seamless switches between instances.
My experience with the procurement process is easy and straightforward as I just go to the marketplace, search for NVIDIA RTX Virtual Workstation, and purchase it without any hassle.
The metering and billing experience follows predictability and is straightforward, as I utilize it for other AWS services too, making it easy to navigate in the billing section.
I rate customer support a ten, as I have not used it much but score it highly whenever I have.
I would advise others looking into NVIDIA RTX Virtual Workstation to use the Win Server 2022 version rather than the 2025 version due to certain bugs and reliability issues present in 2025.
If anyone is using NVIDIA GPUs and CUDA for AI-related and graphic-intensive workloads, NVIDIA RTX Virtual Workstation is the best workstation instance.
I rate this product overall as a five out of five.