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Buy GPUs
Server graphics cards are now an indispensable part of modern data centres and enterprise infrastructures. Whether for AI training, deep learning, high-performance computing (HPC) or graphics-intensive virtualisation – high-performance server GPUs deliver the parallel computing power that conventional processors alone cannot provide. Our range includes professional server GPUs from leading manufacturers, designed for continuous operation in data centres.
We offer a wide selection of NVIDIA server graphics cards from various product ranges. The NVIDIA A100 and NVIDIA H100 set new standards in AI acceleration and machine learning, whilst the NVIDIA L40S and NVIDIA A30 offer versatile options for inference workloads and visualisation. The tried-and-tested NVIDIA Tesla and NVIDIA RTX server GPUs are ideal for professional virtual workstations and rendering tasks. We also stock AMD Instinct accelerators, which have been specifically developed for data-intensive HPC applications.
Businesses benefit from dedicated GPU accelerators through drastically reduced computation times for parallel workloads. Typical applications include real-time AI inference, scientific simulations, video transcoding and Virtual Desktop Infrastructure (VDI). The massively parallel architecture of modern server GPUs enables tasks to be completed many times faster than with purely CPU-based systems.
Technically, the latest server graphics cards are characterised by generous HBM memory, high memory bandwidth, support for PCIe 4.0 and PCIe 5.0, and advanced features such as Multi-Instance GPU (MIG) and NVLink interconnect. ECC-protected graphics memory and passive cooling ensure maximum reliability in 24/7 operation.
Refurbished server GPUs offer a cost-effective alternative to buying new. Every refurbished graphics card is thoroughly tested, cleaned and supplied with a warranty. This means you get professional-grade GPU computing power at a significantly reduced price – ideal for setting up test environments, expanding existing GPU clusters or getting started with AI projects in a cost-effective way.