GPU cloud server
Scalable cloud GPU for AI, rendering, and VDI
Launch a high-performance GPU cloud server on VMware infrastructure and run GPU-accelerated workloads for AI, inference, VDI, rendering, 3D graphics, and development tasks.
Scroll down to learn more.
Quick
start
Easy
to manage
GDPR
compliance
VMware Infrastructure
When the CPU Is Not Enough, the GPU Takes Over
Benefits of a GPU Server
Businesses, developers, AI teams, designers, and engineers use GPU cloud computing when standard CPU-based infrastructure is not enough for graphics, model processing, inference, rendering, or virtual workstation workloads. With Serverspace cloud GPU you get:
- flexible VMware server configuration;
- NVIDIA GPU profiles with different GPU memory options;
- the ability to match GPU resources to your actual workload;
This makes Serverspace a practical choice for teams that need GPU resources on demand and want to deploy GPU-enabled virtual machines without investing in dedicated hardware.
Choose the Right GPU for Your Workload
Our VMware infrastructure offers different NVIDIA GPU models for workloads ranging from basic graphics tasks to demanding AI and rendering applications. Select the GPU that best fits your needs.
NVIDIA A16
Designed for cloud workspaces, remote desktops, and multi-user environments that require access to business applications, web browsers, video conferencing, and everyday graphics workloads.
NVIDIA RTX PRO 6000 — COMING SOON
Designed for AI inference, neural networks, 3D design, rendering, video processing, and data analysis that require high performance, advanced acceleration, and large video memory capacity.
Pay Only for the vRAM You Need
There is no need to rent an entire GPU. With Serverspace, you choose the exact amount of video memory your workload requires – from lightweight projects to demanding AI and rendering applications.
NVIDIA A16
- 4 GB of video memory
- 8 GB of video memory
- 16 GB of video memory
NVIDIA RTX PRO 6000
Coming soon- 12 GB of video memory
- 24 GB of video memory
- 48 GB of video memory
- 96 GB of video memory
GPU in Action
A GPU server accelerates workloads where traditional CPU resources are not enough, including AI, graphics, video processing, virtual workstations, and parallel computing.
AI workload
AI Inference
Run neural network models to process text, images, video, user requests, and internal AI services.
Virtual workspace
VDI and Remote Workstations
Access work environments, business applications, and graphical interfaces without requiring powerful local computers.
Render pipeline
3D and Rendering
Accelerate visualization, modeling, and animation, architectural scenes, product graphics, and creative pipelines.
Media workflow
Video and Media
Process video content, perform encoding, generation, image analysis, and run multimodal tasks.
Data workflow
Data Science
Run experiments, process datasets, execute models, perform complex calculations, and prepare data.
Simulation
Simulations and Computing
Engineering tasks, digital prototyping, process modeling, and compute-intensive workloads.
Why us?
Support available anytime
Get answers to your questions anytime, day or night. Our tech specialists respond within just 15 minutes.
Boundless traffic
Leverage boundless bandwidth to tackle enterprise obstacles bring even the most extensive initiatives to life.
Blazing SSDs
Speedy hardware replicates data thrice and almost imperceptible lag takes you to a new level.
Powerful processors
Our VPS servers are driven by Intel 3.1 GHz processors, making them remarkably speedy and consistent.
How to manage?
Build your cloud, manage VMs, and integrate essential services all on one platform: our intuitive management console ensures accessibility for everyone no matter the experience level. Plus - registration does not require a linked card!
How to Create a GPU Server
GPU deployment guide. The entire process takes just a few simple steps.
1
Access the Control Panel
Log in to the Serverspace Control Panel, go to the VMware section, select the GPU service, and click "Create server".
2
Choose the GPU and vRAM
Choose the graphics card and specify the amount of vRAM required for your workload.
3
Configure and Launch
Choose the operating system, configure the CPU, RAM, and disk, confirm the configuration, and start running your workloads.
More questions?
What is the difference between the NVIDIA A16 and the RTX PRO 6000 Blackwell?
The NVIDIA A16 is ideal for virtual workstations, remote desktops, and VDI environments.
The NVIDIA RTX PRO 6000 Blackwell is the better choice for AI, advanced graphics, rendering, video processing, simulations, and large-scale data workloads.
How is GPU server usage billed?
The cost of one hour of GPU usage is charged in advance at the beginning of each hour. Other virtual machine resources, including CPU, RAM, and storage, follow the standard Serverspace Pay-As-You-Go model and are billed every 10 minutes.
Can I use the GPU to train AI models?
Yes. The NVIDIA RTX PRO 6000 Blackwell is suitable for inference, training, and fine-tuning machine learning, deep learning, and generative AI models.
Can I scale a GPU server?
Yes. As your workload grows, you can adjust the server configuration, add more resources, or change the amount of vRAM. Everything can be managed directly from the control panel without migration or complex reconfiguration.
Earn money for each referral
Here's how to become a member:
Join
Sign up to the Serverspace control panel - instant setup, no binding terms.
Promote
Promote Serverspace easily with our built-in marketing tools.
Earn rewards!
Earn 10% from each referral’s purchases during their first year, and 5% for as long as they stay active.
How much?
You are not tied to rates and can order any cloud server configuration with unlimited traffic included.
€
/mo
€
/hr
