Use HOSTKEY GPU servers as the foundation for resource-intensive projects, from training neural networks and ML models to 3D rendering and complex data analytics. You get a highly configurable infrastructure with NVIDIA accelerators, high-speed NVMe drives and powerful CPUs that easily adapt to growing workloads and the demands of your tasks.
Haven't you found the right pre-configured server yet? Use our online configurator to assemble a custom GPU server that fits your unique requirements.
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Order a GPU server with pre-installed software and get a ready-to-use environment in minutes.
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Custom dedicated server with cutting-edge GPU cards like the RTX A4000 / A5000 / A6000 / 5090 / 6000 PRO
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Pre-configured GPU dedicated servers based on professional cards like the RTX A4000 / A5000 / A6000 / 5090 or more budget-friendly options from previous generations.
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The GPU card in virtual servers is dedicated to the VM and its resources are not shared among other clients. GPU performance in virtual machines matches GPU performance in dedicated servers.
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W. Frederik Hermansstraat 91, 1011 DG, Amsterdam, The Netherlands
Order: hostkey.com
Address:
W. Frederik Hermansstraat 91, 1011 DG, Amsterdam, The Netherlands
Order: hostkey.com
Address:
W. Frederik Hermansstraat 91, 1011 DG, Amsterdam, The Netherlands
Order: hostkey.com
Rent instant server with RTX A5000 GPU in 15 minutes!
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Get a GPU Server Designed for Your Workload
Let us know your requirements and get a custom GPU server configuration optimized for AI, rendering or data-intensive tasks.
This is a dedicated server equipped with graphics accelerators used for parallel computing. It is suitable for tasks that require high performance when working with data, graphics, or models.
GPU servers are best suited for AI and machine learning, rendering, video processing, big data analytics and scientific computing. They are effective wherever parallel processing speed is crucial.
The main difference is the presence of a GPU, which significantly accelerates computations compared to regular CPU servers. This is especially noticeable in tasks with heavy mathematical workloads and processing massive data sets.
Focus on the type of workload: for model training, the GPU class and VRAM size are important; for analytics, a balance of CPU and memory; for storage, fast NVMe drives. Also consider scalability and budget.
Yes, you can customize the server to your requirements: choose the GPU model, processor parameters, RAM amount, storage type and operating system.
Yes, you can rent a GPU for short periods, hourly or monthly. This is convenient for model testing, rendering, or temporary tasks without long-term commitments. You pay only for actual usage, and access to modern graphics cards is provided almost immediately.
In most cases, the server is deployed automatically and becomes available within minutes of ordering. This allows you to get up and running quickly without lengthy setup.
Yes, you can increase resources if needed, add a GPU, expand memory, or increase storage. Scaling occurs without complex migrations.
Various payment models are available: hourly, monthly, or based on specific configurations. This allows for flexible cost management and selection of the optimal option for your needs.
GPU dedicated servers are designed for computationally intensive workloads such as AI, deep learning, and rendering. Compared to CPU-based servers, they deliver significantly faster processing thanks to parallel computing.
GPU VPS is a cost-effective option for smaller workloads or testing environments.
Dedicated GPU servers are better suited for large-scale AI training, rendering, and high-load applications.
Both options provide dedicated GPU resources and stable performance depending on your project requirements.
With HOSTKEY, you can deploy GPU servers quickly using a control panel or API.
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