ACCELERATED PARALLEL PROCESSING

GPU-Accelerated Bare Metal Servers

Power your most demanding AI, machine learning, and rendering workloads with our GPU bare metal servers, featuring high-end NVIDIA GPUs for massive parallel processing capabilities.

LIMITED TIME OFFER

Get up to 15% OFF GPU Servers

+ Free Setup & Dedicated IP!

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GPU Server Infrastructure

Choose Your GPU Server

Instantly deployable servers with powerful NVIDIA GPUs for accelerated computing.

GPU-Render

10% OFF$439

For 3D rendering, encoding & design.

$399/mo
Deploy Server
  • 1x NVIDIA RTX A6000 (48GB)
  • AMD EPYC 7443P (24 Cores)
  • 128 GB DDR4 ECC RAM
  • 2 x 2TB NVMe (RAID-1)
  • 50 TB Bandwidth @ 10 Gbps
  • 1 Dedicated IP Address
  • 24/7 Hardware Support
Most Popular

GPU-AI

12% OFF$899

For AI model training & machine learning.

$799/mo
+ Free SetupLimited Deal
Deploy Server
  • 1x NVIDIA A100 (40GB HBM2)
  • AMD EPYC 7543P (32 Cores)
  • 256 GB DDR4 ECC RAM
  • 2 x 4TB NVMe (RAID-1)
  • 30 TB Bandwidth @ 10 Gbps
  • Full Root & IPMI
  • 24/7 Priority Support

GPU-HPC

15% OFF$1749

For scientific & high-performance computing.

$1499/mo
Deploy Server
  • 2x NVIDIA A100 (80GB HBM2)
  • Dual AMD EPYC 7543P (64 Cores)
  • 512 GB DDR4 ECC RAM
  • 4 x 4TB NVMe (RAID-10)
  • 50 TB Bandwidth @ 10 Gbps
  • Full Root & IPMI Access
  • 24/7 Priority Support
Instant Deployment

Your GPU Server, Ready in Minutes

Get instant access to your physical GPU server. Our automated system provisions your chosen hardware and installs your selected OS in minutes, fully licensed and ready for your applications.

  • Automated provisioning in under 30 minutes
  • 1-Click installs for Ubuntu, Debian, and more
  • Full Root (SSH) access provided upon deployment
  • Install drivers & frameworks like TensorFlow/PyTorch
Deploy Your Server
Server Deployment

> Step 1: Select GPU Spec & Location

> Step 2: Choose OS (e.g., Ubuntu 22.04)

> Step 3: Click 'Deploy Server'

✓ Server provisioned successfully!

IP Address: 192.168.1.101
Root Password: ****************
Setup time: 25 minutes
HOSTDATOS GPU Server Architecture

The GPU Advantage

Harness the power of thousands of processing cores to accelerate your most complex computational tasks.

Massive Parallel Processing

NVIDIA GPUs contain thousands of cores, allowing them to perform thousands of operations simultaneously, drastically cutting down processing time.

Enterprise-Grade NVIDIA GPUs

We use data center-grade NVIDIA A100 and RTX A6000 cards, built for 24/7 reliability and maximum performance.

High-Speed NVMe Storage

Ultra-fast NVMe SSDs ensure your GPU is never waiting for data, eliminating I/O bottlenecks for your training and rendering tasks.

Full Root Access

Install any OS, framework (like TensorFlow or PyTorch), and NVIDIA drivers you need. You have complete control over the software stack.

Use Cases

For Computationally Intensive Workloads.

GPU servers are the ideal solution for tasks that can be parallelized across thousands of cores.

AI & Machine Learning

Train complex deep learning and neural network models in a fraction of the time compared to CPU-only servers. Perfect for TensorFlow and PyTorch.

3D Rendering & VFX

Dramatically reduce render times for complex 3D scenes and visual effects. Ideal for Blender, V-Ray, and other rendering engines.

Scientific & Technical Computing

Run complex simulations, data analysis, and computational fluid dynamics (CFD) workloads that benefit from CUDA acceleration.

Video Transcoding & Streaming

Encode and transcode high-resolution video streams in real-time for live events, VOD platforms, and video processing pipelines.

Big Data Analytics

Accelerate data processing and analytics workloads on large datasets using frameworks like RAPIDS AI and Apache Spark with GPU support.

Password Recovery & Cryptography

Perform high-speed cryptographic analysis and password recovery tasks for security auditing and digital forensics.

Expert Assistance

Setup & Configuration Support.

Getting a GPU server ready for your specific workload can be complex. Our senior engineers can assist with OS installation, driver setup, and framework configuration to get you started faster.

  • Assistance with NVIDIA driver and CUDA toolkit installation
  • Help with setting up TensorFlow, PyTorch, and other frameworks
  • Available as a professional service add-on
Consult an Engineer →
Seamless Server Migration
GPU Servers from $399/month

Accelerate Your Most Demanding Workloads.

Harness the power of NVIDIA GPUs for AI, rendering, and high-performance computing.
Deploy your server in minutes with a 7-Day money-back guarantee.

Deploy Your GPU Server Talk to Sales →

Bare Metal Servers

Raw hardware performance.

Linux Dedicated

For open-source stacks.

Windows Dedicated

For .NET & MSSQL apps.

Managed Servers

White-glove management.

GPU Servers

For AI, ML & rendering.

Storage Servers

For backups & big data.

GPU Server FAQs

A GPU server is a dedicated server equipped with powerful Graphics Processing Units (GPUs). They are used for tasks that can be broken down into many smaller, simultaneous operations (parallel processing). This makes them ideal for AI/machine learning, 3D rendering, scientific computing, and big data analytics.
Yes. You get full root and IPMI access to the server. This allows you to install any compatible operating system (like Ubuntu, which is popular for AI/ML) and the specific NVIDIA drivers and CUDA toolkit versions required by your software.
The NVIDIA A100 is a top-tier data center GPU optimized for AI training and HPC, featuring HBM2 memory for maximum data throughput. The NVIDIA RTX A6000 is a powerful professional visualization GPU, excellent for 3D rendering and video editing, while also being very capable for AI inference and lighter training tasks.
Our GPU servers are unmanaged by default, giving you full control. We provide 24/7 support for hardware, network, and power issues. We also offer professional services for initial setup, OS installation, and driver configuration if you need assistance getting started.
Our GPU servers come with high-speed, low-latency network connections, typically starting at 10 Gbps. This is crucial for transferring large datasets for training or downloading large assets for rendering projects. Generous bandwidth allocations are included with each plan.
Yes. With full root access, you can use technologies like Docker containers or NVIDIA's Multi-Instance GPU (MIG) feature (on supported cards like the A100) to partition the GPU's resources and run multiple isolated workloads simultaneously, maximizing your hardware utilization.
Yes, all our GPU dedicated servers are covered by our 7-day money-back guarantee. If you are not satisfied with the performance or service for any reason within the first week, you can request a full refund.