Cloud Server GPU

Accelerate your activities with artificial intelligence and your machine learning projects optimizing time and costs. Solve complex calculations and manage parallel, massive tasks with our ready-to-use GPU computing solutions.
Ideal for your heavy workloads and for taking maximum advantage from AI, deep learning, big data processing, computer vision.
Extreme power thanks to the use of the NVIDIA graphic processors (NVIDIA H100, A100, Quadro RTX A6000 and L4).

CS GPU H100
Coming Soon

Graphic Processor

NVIDIA H100

Number of GPUs

GPU RAM

80 GB

CPU CORE

16

RAM

120 GB

Disk

1 TB

Hourly Cost

-

Monthly Fee

-
CS GPU L4

Graphic Processor

NVIDIA L4

Number of GPUs

GPU RAM

24 GB

CPU CORE

4

RAM

32 GB

Disk

100 GB

Hourly Cost

0.380

Monthly Fee

279.00

For building the best GPU offer, we have chosen NVIDIA Quadro RTX A6000, A30, L4, A100 graphic processors, that can offer you maximum power with a competitive price."

Projected for tackling complex calculations and modelling, our ready-to-use service, with easy driver installation and 1Gbps bandwidth, is also very flexible and offers a billing model based on the real usage.

Show previous generation CS GPU
CS GPU RTX6000

Graphic Processor

NVIDIA Quadro RTX6000

Number of GPUs

GPU RAM

24 GB

CPU CORE

8

RAM

32 GB

Disk

500 GB

Hourly Cost

0.640

Monthly Fee

460.50
CS GPU A30

Graphic Processor

NVIDIA A30

Number of GPUs

GPU RAM

24 GB

CPU CORE

8

RAM

32 GB

Disk

500 GB

Hourly Cost

0.640

Monthly Fee

460.50

Developers, data scientists, researchers, companies, artists and universities can take advantage of our technology and fuse traditional simulations with artificial intelligence, machine learning, and deep learning.

Try now our Cloud Server GPU instances or ask us for an analysis of your AI projects requirements!

  • What is a GPU cloud server?

    A GPU cloud server is a computer instance that offers high computational power. Without requiring that GPUs are deployed on-premise, in GPU Computing the graphic processing units are integrated in the cloud, enabling complex calculations and projects with data-intensive applications.

    In all cases where a traditional approach, based on multi-core CPUs, cannot support machine learning, scientific computing and 3D visualization, Seeweb high-performance GPU can be beneficial in machine learning, scientific computing, and 3D visualization.

    In particular, for your activities of AI inference and mainstream calculation, thanks to the Tensor Cores of the NVIDIA Ampere and Multi-Instance GPU infrastructure you will be able to accelerate multiple and parallel workloads, such as the AI inference on a large scale and the HPC applications. Fast memory bandwidth and low energy consumption will contribute to creating an elastic data center, with stable performances.

  • What are the advantages of a GPU Cloud Server?

    Activating our GPU servers ready to be used, you can launch your innovative projects reducing latency and integrating technological advantages with a full GDPR compliance: all data is processed in Europe, in our ISO 14001, sustainable Data Centers. Take advantage of GPU instances that guarantee you high power and optimization of the environmental costs.

  • How can I use Seeweb GPU servers for AI?

    The technological stack of our GPU cloud instances has been designed for immediate use. You will not need to invest time in installing drivers and will be able to add space thanks to the complete integration of our services with all the other cloud storage solutions we provide, such as Cloud ScaleOut Filer.

    Furthermore, above all in case you need a particular flexibility in using GPU systems or multi-GPU architectures, our Terraform support will give you the possibility of deploying and managing your infrastructure through the IaC method.

  • How does the billing of Cloud Server GPU work?

    Our GPU servers' billing is based on the real usage. The network traffic or the API calls are free of charge. Once you have chosen and activated the best GPU plan for your AI projects through the cloud control panel, you will be billed only for the hours of use. The billing will start after the product activation, with no advance payment. When you need to stop the project, you can go to your control panel, select the service you wish to cancel and click on the request cancellation button, with no further communications.