NVIDIA RTX Virtual Workstation Reviews

We are working with ray tracing on design projects. We are planning to deploy a lot of our own models and are exploring Akamai Cloud, which provides GPUs at a lower cost. We have already taken a few GPUs from NVIDIA, which are running well. We have hosted those machines on-premises, and they are giving good results. On the Python side, we are using FastAPI for REST API purposes. We are planning to build autonomous agents, including automated agents and a multi-agent system.

I find a lot of benefits in using NVIDIA RTX 6000. For instance, there is a memory mechanism they have, similar to RAM. When we take normal EC2 instances, they always follow a waterfall mechanism, but with NVIDIA, it takes multiple requests in parallel. Due to that graphics card or memory in place, it can handle numerous requests at a time without waiting for one to complete before moving to the next. This parallel processing allows us to run multiple requests simultaneously, which is a major advantage I have observed with NVIDIA GPUs.

The real-time ray tracing feature is beneficial because it acts as a cache mechanism; it does not wait and executes within a fraction of microseconds, storing a lot of data. We can apply parallel indexing, and everything is available in memory. Performance-wise, it is very good compared to a normal CPU.

The high-resolution graphics from NVIDIA RTX 6000 helps our work significantly. With this GPU, we can multitask effectively; for instance, we can ask one model to write content for an email while simultaneously deriving an image based on the instructions, and also writing a social media article. This allows us to expect proper responses in a timely manner, with everything happening in parallel and delivering results in seconds.

I am uncertain about areas for improvement regarding NVIDIA RTX Virtual Workstation.

From my perspective, I believe there is room for improvement in the updates or enhancements from the CUDA platform, which we do not see at the moment.

We do not see any platform-side updates from NVIDIA. They are building a lot of different models, but the background platform is still CUDA, and we do not see any updates from it.

For stability, I give it a rating of 10.

For scalability, I also give it a rating of 10.

We are not using any products such as Chief SaaS, Infrascale, Qualys, Varonis, Veeam, or Druva at this time; however, we are planning to build our own agents.

NVIDIA RTX Virtual Workstation is very expensive, and we are looking for alternatives to reduce this pricing.

We are considering alternatives such as Akamai; I recently attended an event there and they have some GPUs, so we are evaluating and exploring options.

We bought one machine from NVIDIA, NVIDIA RTX 6000, which we are using for internal purposes.

The purpose of using NVIDIA RTX 6000 is that we build our own algorithm and we have created one model, an LLM, which we bought the machine for, specifically for model training purposes.

I give this product an overall rating of 10.

I use NVIDIA RTX Virtual Workstation for smooth remote graphics performance and for providing efficient GPU resource support to demanding professional applications.

In a recent project I was doing with 3D modeling and CAD models, NVIDIA RTX Virtual Workstation and NVIDIA GPU made the rendering very smooth.

Accessing resources for deep learning and model training is another way I have used NVIDIA RTX Virtual Workstation.

NVIDIA RTX Virtual Workstation has made 3D modeling very easy and smooth in my organization, increasing the ease of access and enhancing the experience in general.

The positive impact of NVIDIA RTX Virtual Workstation has increased productivity because even though the licensing is an expensive part, the productivity and benefits are high for students, allowing us to have clear, hands-on 3D modeling software that works very smoothly and saves a lot of time.

The best feature of NVIDIA RTX Virtual Workstation for me is the smooth remote graphics and the GPU virtualization capabilities.

The remote graphics and virtualization capabilities of NVIDIA RTX Virtual Workstation make the 3D rendering very clear and provide good graphics, which eases the work because it is all about making things look good.

Regarding NVIDIA RTX Virtual Workstation, I would say the licensing cost is high and deployment may require experienced IT administrators. The organization also needs suitable infrastructure to get the best performance, which is the only drawback.

I have been using NVIDIA RTX Virtual Workstation for the past two years.

NVIDIA RTX Virtual Workstation is stable.

The scalability of NVIDIA RTX Virtual Workstation is very good.

The customer support experience with NVIDIA RTX Virtual Workstation was nice and very smooth.

We have not used a different solution; we started with NVIDIA RTX Virtual Workstation.

The experience with pricing, setup cost, and licensing for NVIDIA RTX Virtual Workstation was very smooth.

The licensing process and the setup cost for NVIDIA RTX Virtual Workstation were smooth.

NVIDIA RTX Virtual Workstation saved a lot of time, and qualitatively, the quality has been amazing.

We did evaluate other options before choosing NVIDIA RTX Virtual Workstation; AMD was another option which was under our radar, but we chose NVIDIA.

The experience with NVIDIA RTX Virtual Workstation has been nice; even though the cost is very high, after it is in the organization, it gives a lot of good modeling outputs, so it has completely improved the experience overall.

The governance and security of NVIDIA RTX Virtual Workstation's AI is fine because as long as it does the work, I am fine.

The accuracy and reliability of output from NVIDIA RTX Virtual Workstation are very high.

NVIDIA RTX Virtual Workstation is deployed on-premises in my organization.

I would say NVIDIA RTX Virtual Workstation is an excellent solution for enterprises that require high performance in workstations and professional GPU workloads.

I gave this review a rating of 10 out of 10.

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.

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.

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.

I have been using NVIDIA RTX Virtual Workstation for more than two years now on different G5 and G6 instances.

NVIDIA RTX Virtual Workstation is very stable.

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.

Customer support is great.

Positive

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.

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.

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.

My experience with pricing, setup cost, and licensing is good as it is pretty straightforward and easy to understand.

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.