Dedicated GPU Server

A Graphics Processing Unit (GPU) is a single-chip processor primarily used to manage and boost the performance of video and graphics. Our GPU dedicated servers deliver high performance for Android Emulator, Artificial Intelligence, gaming, and machine learning ...

Lite GPU Server

Support for Android emulators, making them highly suitable and user-friendly for beginners who are new to the platform

  • CPU Intel Xeon E5-X3440 2.53 GHz 4 Cores 8 Threads
  • RAM 16 GB RAM
  • Storage 120GB + 960GB SSD
  • Unlimited Bandwidth 100Mbps
  • Dedicated IP Yes
  • Location USA
  • GPU Nvidia GeForce GT710
  • CUDA Cores 192
  • GPU Memory 1GB
  • Performance 1.06 TFLOPS
  • Operating System Windows/ Ubuntu/ CentOS/ Debian/ Fedora
  • Android Emulator All Supported

Basic GPU Server

More power more speed. Can install Android Emulator, BlueStacks, NoxPlayer and MEmu …

  • CPU Intel Xeon E5-2670 3.30 GHz 8 Cores 12 Threads
  • RAM 32 GB RAM
  • Storage 120GB + 960GB SSD
  • Unlimited Bandwidth 100Mbps
  • Dedicated IP Yes
  • Location USA
  • GPU Nvidia Quadro P620
  • CUDA Cores 512
  • GPU Memory 2GB GDDR5
  • Performance 1.5 TFLOPS
  • Operating System Windows/ Ubuntu/ CentOS/ Debian/ Fedora
  • Android Emulator All Supported

Standard GPU Server

Good choice for Android Emulator, Video Editing, Content Creation and rendering 2D, 3D graphics

  • CPU Intel Xeon E5-2670 3.30 GHz 8 Cores 16 Threads
  • RAM 32 GB RAM
  • Storage 120GB + 960GB SSD
  • Unlimited Bandwidth 100Mbps
  • Dedicated IP Yes
  • Location USA
  • GPU Nvidia Quadro P1000
  • CUDA Cores 620
  • GPU Memory 4GB
  • Performance 1.89 TFLOPS
  • Operating System Windows/ Ubuntu/ CentOS/ Debian/ Fedora
  • Android Emulator All Supported

Express GPU Server

Good choice for Android Emulator, Gaming, Video Editing, Content Creation, rendering 2D, 3D graphics

  • CPU Intel Xeon E5-2690 3.80 GHz 8 Cores 16 Threads
  • RAM 64 GB RAM
  • Storage 120GB + 960GB SSD
  • Unlimited Bandwidth 100Mbps
  • Dedicated IP Yes
  • Location USA
  • GPU Nvidia Quadro T1000
  • CUDA Cores 896
  • GPU Memory 8 GB GDDR6
  • Performance 2.5 TFLOPS
  • Operating System Windows/ Ubuntu/ CentOS/ Debian/ Fedora
  • Android Emulator All Supported

Pro DE/FL GPU Server

Unleashing the Power of GTX 1080: Empowering High-Performance Graphics Processing with Unmatched Speed and Precision

  • CPU Intel Core i7-7700 3.60 GHz 4 Cores 8 Threads
  • RAM 64 GB RAM
  • Storage 2 x 512 GB SSD
  • Unlimited Bandwidth 1 Gbit
  • Dedicated IP Yes
  • Location Germany/Finland
  • GPU GeForce GTX 1080
  • CUDA Cores 2560
  • GPU Memory 8GB of GDDR5X
  • Performance 9 TFLOPS
  • Operating System Windows/ Ubuntu/ CentOS/ Debian/ Fedora
  • Android Emulator All Supported

Professional GPU Server

High-performance computing and very large data center workloads. Good choice for deep learning and AI reasoning

  • CPU Dual Intel Xeon E5-2660v2 2.20 GHz 10 Cores 20 Threads
  • RAM 64 GB RAM
  • Storage 120GB + 960GB SSD
  • Unlimited Bandwidth 100Mbps
  • Dedicated IP Yes
  • Location USA
  • GPU Nvidia GeForce GTX 1660
  • CUDA Cores 1408
  • GPU Memory 6GB GDDR6
  • Performance 1.894 TFLOPS
  • Operating System Windows/ Ubuntu/ CentOS/ Debian/ Fedora
  • Android Emulator All Supported

Premium GPU Server

Empowering High-Performance Computing and Large-Scale Data Center Workloads: The Ideal Solution for Deep Learning and AI Reasoning

  • CPU Dual Intel Xeon E5-2660v2: 2.20 GHz 20 Cores 40 Threads
  • RAM 128 GB RAM
  • Storage 120GB + 960GB SSD
  • Unlimited Bandwidth 100Mbps
  • Dedicated IP Yes
  • Location USA
  • GPU Nvidia GeForce RTX 2060
  • CUDA Cores 1920
  • GPU Memory 6GB GDDR6
  • Performance 6.5 TFLOPS
  • Operating System Windows/ Ubuntu/ CentOS/ Debian/ Fedora
  • Android Emulator All Supported

Elite GPU Server

For professionals, it can provide real-time ray tracing, AI accelerated computing and high-performance graphics performance on the desktop

  • CPU Intel Xeon E5-2697v2: 2.70 GHz 2×12 Cores
  • RAM 128 GB RAM
  • Storage 240GB + 2TB SSD
  • Unlimited Bandwidth 100Mbps
  • Dedicated IP Yes
  • Location USA
  • GPU Nvidia RTX A4000
  • CUDA Cores 6144
  • GPU Memory 16GB GDDR6
  • Performance 19.23 TFLOPS
  • Operating System Windows/ Ubuntu/ CentOS/ Debian/ Fedora
  • Android Emulator All Supported

Diamond GPU Server

Achieve an excellent balance between function, performance and reliability, and assist designers, engineers and artists to realize their vision

  • CPU Dual Intel Xeon E5-2697v2 2.70 GHz 24 Cores 32 Threads
  • RAM 128 GB RAM
  • Storage 120GB + 2TB SSD
  • Unlimited Bandwidth 100Mbps
  • Dedicated IP Yes
  • Location USA
  • GPU Nvidia A5000
  • CUDA Cores 8192
  • GPU Memory 24GB
  • Performance 27.8 TFLOPS
  • Operating System Windows/ Ubuntu/ CentOS/ Debian/ Fedora
  • Android Emulator All Supported

This high-performance server is equipped with an Intel Core i5-13500 Raptor Lake-S processor and an Nvidia RTX™ 4000 SFF Ada Generation GPU

CPU CPU Speed RAM Storage Bandwidth Location /Mo
Intel Core i5-13500 Raptor Lake-S 4.8 GHz 14 cores 256 GB DDR5 ECC 2 x 1.92 TB NVMe SSD Datacenter Edition (Gen 3) 1Gbps Unlimited Germany $253 Configure

SSD-Based Drives

You can never go wrong with our own top-notch dedicated servers, loaded with the latest Intel Xeon processors, terabytes of SSD disk space and 128 GB of RAM per server.

Control Panel

PreVPS provides KVM over IP (IPMI) for all dedicated GPU servers. The Intelligent Platform Management Interface (IPMI) system provides management and monitoring capabilities independently.

Full Root Access

With full root access, you will be able to take full control of your server very easily and quickly. To use all the power provided effectively, you will have to have very little technical knowledge.

99.9% Uptime

With enterprise-class data centers and infrastructure, we provide a 99.9% uptime guarantee for our servers and network.

Integrated GPU and Discrete GPU

GPUs come in two basic types. One is an integrated(or embedded) GPU that is built onto and shares memory with the CPU. The other is a discrete GPU that has its own card and memory. Our GPU servers employ the discrete GPUs.

FAQs

What is GPU Server?

A GPU server is a server packed with a GPU (graphics processing unit). GPU, also called graphics card or video card, is a specialized electronic circuit that accelerates the process of creating and rendering computer graphics, video, ect. It performs rapid mathematical calculations while freeing the CPU to perform other tasks.

GPU Server vs. GPU VPS

When renting a VPS with the GPU you have direct access to the GPUs. However, it’s working on the same primary server with other VPSs. But a GPU dedicated hosting server is your own, personal computer. You can use it for anything you want with high-performance SSD drives for AI, gaming, and machine learning.

What Is the Difference Between Integrated Graphics and Discrete Graphics?

A graphics processing unit (GPU) is a processor dedicated solely to graphics processing operations. One of the main functions of the GPU is to lighten the load on the central processing unit (CPU), especially when running a graphics intensive game or application. A GPU can be either integrated or discrete. See below for more information.

Integrated graphics
Integrated graphics is a GPU built into the processor. Integrated graphics hardware doesn’t use a separate memory bank for graphics/video. Instead, the GPU uses system memory that is shared with the CPU. Since integrated graphics is built into the processor, it typically uses less power and as a result creates less heat, which can result in a longer battery life. Processors with integrated graphics are most commonly found in smaller form factor systems such as laptops and Intel® NUCs.

Discrete graphics
Discrete graphics is a GPU that is a separate from the processor. Discrete graphics has its own dedicated memory that is not shared with the CPU. Since discrete graphics is separate from the processor chip, it consumes more power and generates a significant amount of heat. However, since a discrete graphics has its own memory source and power source, it provides higher performance than integrated graphics. Discrete graphics cards are most commonly found in desktop PCs. Laptops and small form factor PCs can also contain discrete graphics cards.

What Are GPUs Used For?

GPUs are best suited for repetitive and highly-parallel computing tasks. Beyond video rendering, GPUs excel in machine learning, Artificial Intelligence, and many other types of scientific computations.

GPUs for Gaming
Rendering scenarios, such as video games, require GPUs for graphics acceleration and real-time rendering, and also require massive computing capacities, memory, and storage. With advanced display technologies, such as 4K screens and high refresh rates, along with the rise of virtual reality gaming, demands on graphics processing are growing fast. GPUs can have hundreds or thousands of small cores and are perfect for 2D and 3D calculations and rendering 3D graphics. With better graphics performance, games can be played at higher resolution, at faster frame rates, or both.

GPUs for Video Editing and Content Creation
Working with video editing, visual effects, and animation requires a high-performing PC to efficiently handle the resource-heavy tasks and avoid waiting for projects to render and encode. GPUs usually have hundreds or thousands of small cores. These highly task-parallel, specialized computing cores are perfectly used for graphics processing, making it faster and easier to render video and graphics in higher-definition formats.

GPU for Machine Learning
Artificial Intelligence and Machine Learning operations often require processing massive amounts of images or videos. Because GPUs incorporate an extraordinary amount of computational capability, they can deliver incredible acceleration in workloads that take advantage of the highly parallel nature of GPUs, such as image recognition.

What does a GPU server do?

A GPU server is a server packed with GPU that is often used for machine learning, video editing, and gaming applications.

What is the difference between a CPU and a GPU?

A CPU commonly consists of only 4 or 8 fast and flexible cores that are optimized to handle a wide range of tasks sequentially. Whereas, a GPU have thousands of relatively simple cores that are designed for parallel processing. For high performance, we will need both CPU and GPU.

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