GPU server rental

Available GPU servers

Compare servers by GPU model, video memory size, processor, RAM and disk subsystem.

Choose a GPU server for your task

GPUs accelerate parallel computing and help process models, graphics, video and large datasets faster.

• Machine learning

  Model training, hypothesis testing, dataset processing and computational experiments.

• LLMs and AI applications

  Language model inference, AI agents, RAG systems and enterprise AI services.

• Image generation

  Running Stable Diffusion, FLUX and other models for creating and processing visual content.

• 3D rendering

  Scene rendering, architectural visualization, animation and complex 3D graphics.

• Video processing

  Encoding, transcoding, editing and automated video processing.

• Scientific computing

  Simulation, data analysis and other tasks that require high-speed parallel computing.

Why GPUs accelerate computing

A regular processor performs a wide range of sequential operations. A GPU consists of a large number of compute units and handles tasks that can be executed in parallel more efficiently.

• Fast data processing

  A GPU executes a large number of operations simultaneously and speeds up computing related to models, graphics and video.

• Dedicated resources

  The server's GPU is not shared with other users and is fully available to your project.

• Predictable performance

  The configuration and available resources remain constant throughout the entire rental period.

• Control over the environment

  Install the drivers, libraries, frameworks, containers and other software you need.

Software for working with GPUs

Install the drivers, libraries and applications you need. Software compatibility depends on the GPU model and the selected operating system.

• CUDA
• Docker
• NVIDIA Container Toolkit
• PyTorch
• TensorFlow
• Jupyter
• Stable Diffusion
• FLUX
• Blender
• FFmpeg

The client installs and configures software independently unless otherwise agreed when placing the order.

Advantages of a dedicated GPU server

• All GPU power is yours

  The GPU and all other resources of the physical server are used only by your project.

• Suitable for constant load

  Use the server for long training runs, continuous inference, video processing or rendering.

• Full root access

  Manage the operating system, drivers, libraries and environment settings yourself.

• Fast local storage

  Store models, datasets and computation results on the server's drives without transferring data to third-party services.

• Custom selection

  Request a configuration with the GPU model, RAM size, processor and disk subsystem you need.

• 24/7 support

  PSB Hosting specialists are available around the clock and will help resolve issues related to the service.

How to rent a GPU server

1. 1

   Define your task

   Specify what the GPU will be used for: machine learning, inference, rendering, video or other computing.

2. 2

   Choose a configuration

   Compare the GPU model, video memory size, processor, RAM and storage.

3. 3

   Place an order

   Choose a ready-made server or send a request for a custom configuration.

4. 4

   Set up the environment

   Get access to the server and install the drivers, libraries, containers and applications you need.