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GPU Server

Our GPU Servers master your AI challenges.

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The Power You Need for Your AI Tasks

You would like to run a Large Language Model (LLM) that works with human language on the basis of deep learning models? Our GPU servers meet the requirements of high-performance computing – and are also available as a managed option.

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Highlights

Advantages at a Glance

Performance

The computing power of a base system, paired with the power of up to two entry-level or production-level graphics cards

Upgradability

On request, we can equip your GPU server with up to 2 TB RAM, 4x NVME, 8x SATA and two GPUs

Modern hardware

We offer the latest graphics cards and state-of-the-art hardware components for our GPU servers

Managed Server

We also offer GPU servers as a managed variant, where we take on server management for you – we are happy to make you an offer

Swiss location

You can be sure that your data will remain in Switzerland and that your provider follows and embodies a sensitive approach to information security

Hypervisor option

You can also use our base system without a GPU, for virtualisation purposes

Information

About the Product

In contrast to conventional servers, GPU servers offer a drastic increase in performance for complex calculations. This type of server performs the majority of calculations in graphics processors. This is why GPUs are also the most important components for High Performance Computing (HPC). These types of servers are increasingly being used for machine learning or large language models in particular.

More about GPU Server
CPU versus GPU
Nowadays, graphics cards are not only used for image processing, but increasingly in specialised servers for applications such as artificial intelligence (AI), rendering, computer-aided design (CAD), visualizations or simulations. Thanks to the many processor cores (also known as shaders) in GPUs, they can perform many similar operations at the same time. This means that tasks can be processed quickly and cost-effectively.
Nine GPU Server
Our base system comes pre-equipped with powerful components, so you don’t have to make any compromises. The base system can also be used without a GPU as a powerful hypervisor system for virtualisation. Or you can have your Nine GPU Server equipped with one or even two graphics cards – depending on your requirements, you can choose between an entry-level and a production-level model. As a further option, we also offer our Nine GPU servers as managed servers and take care of maintenance, management, monitoring, updates and much more for you – do not hesitate to contact us for an offer.
State-of-the-Art Hardware
When selecting the hardware components, we focussed primarily on an optimal price-benefit ratio in the interest of our customers. We began by examining various options, including the H100 from Nvidia, compared their value proposition and availability, and decided on the aforementioned configurations. As flexibility is very important to us at Nine, we can also install further professional components on request. Please note that availability can fluctuate due to the very high demand for GPU servers.
Case Studies

Use Cases for GPU Servers

Pupil AG

Nine operates the reliable and stable infrastructure for PUPIL, an all-in-one solution for digital school management, based on its own Nine Kubernetes Engine (NKE), so that Pupil AG can focus on its core business.

Pupil AG

ayyah

Nine operates the highly available infrastructure for the Ayyah software based on the Nine Kubernetes Engine (NKE) so that Ayyah AG can focus on customer needs and software development.

ayyah

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