Dedicated Server Hosting with NVIDIA Tesla

Dedicated servers equipped with professional NVIDIA Tesla GPU cards are ideal options for AI, Deep Learning, and HPC - configurable with up to 2x GPUs for massively parallel computing. Find the right NVIDIA Tesla GPU server for your workload.

What Can Be Run on Tesla GPU Hosting Servers

The Tesla accelerator provides a powerful foundation for customers to leverage best-in-class software and solutions for deep learning.

When to choose a Tesla GPU Hosting

Here are the most use cases on dedicated servers with Tesla GPU.
AI and Deep Learning projects
The Nvidia Tesla K80 is a server solution from 2014. It has 24 GB of RAM split between 2 cards and a 2946 CUDA core, and all this is great for AI and Deep Learning projects.
Data Analytics
HPC and Data Analytics
Count on NVIDIA Tesla K40 GPU Accelerators to solve your most demanding HPC and big-data challenges. They feature 1.4 TFLOPS performance, 12 GB memory, and ultra-fast 288 GB/s throughput, giving you the power to process large datasets while delivering up to 10X acceleration compared to CPUs.

Tesla GPUs Specifications & Performance

Tesla GPU hosting servers make your entire PC experience beyond fast.
Specsk80K40cM40A30 PCIeA40 PCIeA100 SXM4 80 GBV100 PCIe 16 GB
GPU ArchitectureKepler 2.0KeplerMaxwell 2.0AmpereAmpereAmpereVolta
CUDA Cores49922880307235841075269125120
Core clock speed562 MHz745 MHz948 MHz930 MHz1305 MHz1275 MHz1246 MHz
Boost clock speed824 MHz876 MHz1114 MHz1440 MHz1740 MHz1410 MHz1380 MHz
FP16 performance------10.32 TFLOPS37.42 TFLOPS77.97 TFLOPS28.26 TFLOPS
FP32 performance8.73 TFLOPS5.05 TFLOPS6.84 TFLOPS10.32 TFLOPS37.42 TFLOPS19.49 TFLOPS14.13 TFLOPS
FP64 performance2.91 TFLOPS1.68 TFLOPS0.21 TFLOPS5.161 TFLOPS0.58 TFLOPS9.746 TFLOPS7.07 TFLOPS
Memory24GB GDDR5 with ECC12GB GDDR512 GB GDDR524 GB HBM2e48 GB GDDR6 with ECC80 GB HBM2e16 GB HBM2
Memory Bandwidth480 GB/s288 GB/s288 GB/s933.1 GB/s696 GB/s2039 GB/s900 GB/s
Memory Bus Width384 bit384 bit384 bit3072 bit384 bit5120 bit4096 Bit
Memory Clock Speed5012 MHz6008 MHz6008 MHz1215 MHz1812 MHz1593 MHz1758 MHz
System InterfacePCIe 3.0x16PCIe 3.0x16PCIe 3.0x16PCIe 4.0 x16PCIe 4.0 x16PCIe 4.0 x16PCIe 3.0 x16
DirectX12 (11_1)12 (11_0)12 (12_1)N/A12 (12_2)N/A12.0
Shader Model5.15.16.4N/A6.7N/A5.0
OutputsNo outputsNo outputsNo outputsNo outputs3x DisplayPort 1.4aNo outputsNo outputs
Release dateNov 17th, 2014Oct 8th, 2013Nov 10th, 2015Apr 12th, 2021Oct 5th, 2020Nov 16th, 2020Jun 21st, 2017
What Nvidia is happy to talk about is the growing gap in floating point performance and memory bandwidth between CPUs and Nvidia Tesla series GPU cards, which is illustrated on the left. Thus far, over 280 applications in modeling, simulation, data analytics, machine learning, and other workloads have been ported to the CUDA environment so Nvidia Tesla series cards can accelerate them.

GPU Features in NVIDIA Tesla GPU Hosting Server

Hosted dedicated servers with Tesla GPU deliver superior performance over integrated graphics.
Massively Multi-threaded Computing Architecture
Massively Multi-threaded Computing Architecture
Executes thousands of concurrent processing threads for high throughput parallel processing of mathematically intensive problems.
NVIDIA GPU Computing Drivers
NVIDIA GPU Computing Drivers
It helps with the management of the GPU resources and an extensive runtime library for enhanced data management and program execution and offers a high-speed data transfer path and streamlined driver for computing, independent of the graphics driver.
Supercomputing Performance
Supercomputing Performance
Peak performance of over 500 gigaflops per GPU on floating point operations in data-intensive applications.
Multi-GPU Computing
Multi-GPU Computing
Multiple Tesla GPUs can be controlled by a single CPU via the GPU computing driver, delivering incredible throughput on computing applications. The power of the GPU to solve large-scale problems can be multiplied by splitting the problem across multiple GPUs.

Dedicated Servers with Tesla GPU Hosting Pricing

Telsa K80/K40 pairs with Intel® Xeon® Processor E5 Family CPU and 64GB+ RAM, delivering high performance for your engineering and HPC applications.

Basic GPU - K80

For high-performance computing and large data workloads, such as deep learning and AI reasoning.
  • 64GB RAM
  • Eight-Core Xeon E5-2690report
  • 120GB + 960GB SSD
  • 100Mbps-1Gbpsreport
  • OS: Windows / Linux
  • GPU: Nvidia Tesla K80
  • Microarchitecture: Turing
  • Max GPUs: 2report
  • CUDA Cores: 4992
  • GPU Memory: 24GB GDDR5
  • FP32 Performance: 8.73 TFLOPSreport

Advanced GPU - V100

For high-performance computing and large data workloads, such as deep learning and AI reasoning.
  • 128GB RAM
  • Dual 12-Core E5-2690v3report
  • 240GB SSD + 2TB SSD
  • 100Mbps-1Gbpsreport
  • OS: Windows / Linux
  • GPU: Nvidia V100
  • Microarchitecture: Volta
  • Max GPUs: 1
  • CUDA Cores: 5,120
  • Tensor Cores: 640
  • GPU Memory: 16GB HBM2
  • FP32 Performance: 14 TFLOPSreport

Enterprise GPU - A40

Accelerate data science and computation-based workloads. A40 is very suitable for AI and deep learning projects.
  • 256GB RAM
  • Dual 18-Core E5-2697v4report
  • 240GB SSD + 2TB NVMe + 8TB SATA
  • 100Mbps-1Gbpsreport
  • OS: Windows / Linux
  • GPU: Nvidia A40
  • Microarchitecture: Ampere
  • Max GPUs: 1
  • CUDA Cores: 10,752
  • Tensor Cores: 336
  • GPU Memory: 48GB GDDR6
  • FP32 Performance: 37.48 TFLOPSreport

Alternatives to Dedicated Servers with Tesla GPU

If you want to do image rendering, video editing, or play games, these would be better alternatives.
RTX A5000 Hosting

RTX A5000 Hosting

Achieve an excellent balance between function, performance, and reliability. Assist designers, engineers, and artists to realize their visions.
RTX 3060 Ti Hosting

RTX 3060 Ti Hosting

For professionals. It delivers real-time ray tracing, AI accelerated computing, and high-performance graphics to desktops.
Geforce GT 730 Hosting

Geforce GT 730 Hosting

Mainly suitable for home games and Android emulators, such as BlueStacks and MEmu Play.

FAQ of NVIDIA Tesla Series Hosting

Answers to more questions about the Tesla GPU cards can be found here.

Is the Tesla GPU hosting server self-managed?

Yes, but our experienced staff is always here and willing to help you with any problems you have with your rental GPU dedicated server. Please reach us online in a live chat or in an email if you need help

How long will it take to set up GPU dedicated servers with Tesla GPU?

The delivery time for dedicated servers is approximately 20 to 40 minutes. However, in situations where stock is limited, servers may not be able to be delivered until the stock is replenished. If you need a server urgently, please do not hesitate to get in touch with us.

What is NVIDIA Tesla series?

NVIDIA Tesla was the name of Nvidia's line of products. The Nvidia Tesla series is targeted at stream processing or general-purpose graphics processing units (GPGPU), named after pioneering electrical engineer Nikola Tesla. Its products began using GPUs from the G80 series, and have continued to accompany the release of new chips.

What are NVIDIA Tesla GPU servers used for?

NVIDIA Tesla is a line of GPU accelerator boards optimized for high-performance, general-purpose computing. Tesla GPUs are used for parallel scientific, engineering, and technical computing, and they are designed for deployment in supercomputers, clusters, and workstations.

Can NVIDIA Tesla GPU hosting server be used for gaming?

Tesla GPU servers are designed for High-Performance Computing (HPC) and are aimed at an enterprise market. Therefore, gaming isn't exactly the plug-n-play experience of NVIDIA's consumer line. For starters, the K80 doesn't have IO to output to a display where you need to use either motherboard graphics or another GPU as your display adapter. Even then, the Tesla needs to be configured with specialized software. However, if you don't already own one, buy a RTX 2060 instead.

Are NVIDIA Tesla GPU hosting servers good for rendering?

NVIDIA Tesla GPU servers will render Blender scenes just fine. Though for just rendering, you might not see much of an advantage since the Tesla's main benefit is its ability to do double-precision floating point numbers quickly (Blender only uses single precision).

Are NVIDIA Tesla GPU hosting servers good for video editing?

NVIDIA Tesla GPUs are not your ordinary graphics cards -- they won't work for video editing. They have one job, and that is computing (number crunching), high-precision computing to the 17th decimal place. These cards DO NOT have any output ports on them -- you cannot connect any monitors to them.

Can you use a Tesla k80 server for Premiere Pro?

The NVIDIA Tesla GPU server is designed for data centers and extreme computing applications, such as web servers. It isn't the right kind of card for what you intend to use it for. Even if you could, they can only accelerate GPUs on the Kepler architecture (as in Geforce 600 and 700 series) and certainly not integrated graphics or discrete graphics cards from any other architecture.
For this, a standard consumer GPU (especially with Nvidia's CUDA cores) will do fine for Adobe applications, especially something from the 16/20/30 series for their H.265 encoding compatibility. an RTX 3070 can chew through 10 minutes of 4K video, rendering it in about 15-20 minutes, often less.

Can I use a Tesla K80 server for rendering with Blender?

Yes, you can. But if you're planning to use it at home or in an office environment, you should take into account the fact that the K80 boards are built for a data center environment. They don't have video output, so you'll need a secondary graphics card to connect your monitor.