GPU Dedicated Servers

Dedicated vs. Virtualized

When you want to achieve the highest performance possible, virtualization just gets in the way. Besides the virtualization overhead, virtualized cloud instances especially suffers from slow I/O and you can't truly utilize the expensive GPUs. Go with a dedicated solution instead and get the most out of powerful GPUs, while paying a fraction of what AWS/GCP/Azure would cost.

To compare Geforce, Quadro and Tesla series specs and Octanebench performance, check our GPU comparison list.

Looking for a cloud GPU server to use as a remote desktop? We offer GPU servers with Windows 10 Pro and Microsoft RDP.

GPU Servers (Nvidia GeForce 10 Series)

GPU	Processor	Ram	Storage	Location & BW	Price
1x GTX1080 Ti	Xeon 8 Core 2.6 GHz	32 GB	500 GB SSD	Turkey, 1 Gbps	$175/mo	Contact Us
2x GTX1080 Ti	Intel 4 Core 3.4 GHz	32 GB	500 GB SSD	Turkey, 1 Gbps	$289/mo	Contact Us
4x GTX1080 Ti	AMD 12 Core 3.5 GHz	96 GB	1 TB NVMe	Turkey, 1 Gbps	$749 / mo	Contact Us
4x GTX1080 Ti	AMD 12 Core 3.5 GHz	128 GB	500 GB NVMe + 2 TB HDD	Turkey, 1 Gbps	$749 / mo $199 / wk	Contact Us

GPU Servers (Nvidia GeForce 20 Series)

GPU	Processor	Ram	Storage	Location & BW	Price
1x RTX2080 Ti	AMD 8 Core 3.6-4.4 GHz	64 GB	500 GB SSD	Turkey, 1 Gbps	$285/mo	Contact Us
2x RTX2080 Ti	AMD 6 Core 3.4-3.9 GHz	64 GB	500 GB SSD	Turkey, 1 Gbps	$585/mo	Contact Us

Why Choose Us?

The Support Experience

Get support when you need it. And talk to a single person, who can address all your questions, give informed advice, and take care of a problem you face.

Dedicated Hardware

Get root access to the GPU server. Unlike virtualized solutions, use unshared resources and achieve the absolute best performance out of GPUs,

No Surprises Pricing

You pay a flat-rate and you always know what you're paying up front. No hidden charges.

Long-Term Discounts

Make your GPU server rental more affordable... Purchase 3, 4, 6, 9 or 12 months blocks of time and save huge.

NVIDIA GeForce GTX 1080 Ti

Nvidia GeForce GTX 1080 Ti is based on the Pascal GP102 graphics processor (the same chip used by Tesla P40)

GeForce GTX 1080 Ti GPUs are good for Deep Learning, animation rendering, video transcoding and real time video processing.

11 GB memory (484 GB/s bandwidth)
3584 Nvidia CUDA cores
11.3 teraFLOPS (FP32)

NVIDIA GeForce RTX 2080 Ti

Nvidia GeForce RTX 2080 Ti is based on the TU102 graphics processor (the same processor used by Titan RTX). In addition to CUDA cores, RTX 2080 Ti has 544 tensor cores that accelerates machine learning applications. The card also has 68 ray tracing cores which dramatically improves GPU ray tracing performance and it's supported in VRAY, OctaneRender and Redshift.

GeForce RTX 2080 Ti GPUs are good for Deep Learning, animation rendering, real time ray tracing, video transcoding and VR/AR design.

11 GB memory (616 GB/s bandwidth)
4352 Nvidia CUDA cores
13.5 teraFLOPS (FP32)

NVIDIA Tesla V100

Nvidia Tesla V100 is based on Nvidia Volta architecture and offers the performance of up to 100 CPUs in a single GPU. V100 has two versions, PCle and SXM2, with 14 and 15.7 TFLOPS FP32 performance respectively. It comes with either 16GB or 32GB memory, and 32GB one enables AI teams to fit very large neural network models into the GPU memory.

Nvidia Tesla V100 GPUs are good for Machine Learning, Deep Learning, Natural Language Processing, molecular modeling and genomics. Tesla GPUs are the only choice for applications that require double precision such as physics modelling or engineering simulations.

32 GB memory (900 GB/s bandwidth)
5120 Nvidia CUDA cores
15.7 teraFLOPS (FP32)