AI Platform & vGPU Servers: High-Performance Hosting for ML/HPC
Forge your next breakthrough with dedicated, virtualized GPU compute power, specifically engineered for demanding Machine Learning (ML), Data Science, and High-Performance Computing (HPC) workloads. Our platform is the only solution where unparalleled speed meets CyberWAF’s proactive, AI-powered WAF defense.
Unleash Uncompromising vGPU Compute Power
Experience guaranteed performance with dedicated NVIDIA™ H200 resources. Our vGPU servers bypass the overhead of physical hardware, providing the isolated, high-speed processing essential for training deep neural networks and running complex simulations.
Intelligent Infrastructure: Security Designed for AI
Your computational investments deserve protection. The CyberWAF AI Platform integrates proactive WAF defense and Layer 7 DDoS mitigation, ensuring your valuable GPU time is never wasted on malicious bot traffic or sophisticated attacks.
Tailored for Your Most Demanding Workloads
Whether you’re accelerating data science, executing large-scale 3D rendering, or pushing the boundaries of machine learning inference, our scalable vGPU plans deliver the reliability and dedicated VRAM you need to achieve faster time-to-market.
Dedicated vGPU Power: Select Your Ideal Configuration
Scale your ambition with guaranteed access to dedicated NVIDIA™ H200 VRAM and high-core AMD EPYC™ processors. Compare our two flexible plans below to find the perfect balance of computational strength for your machine learning models and data analysis projects.
GPU 7 GB VRAM
- NVIDIA™ H200
- 7 GB VRAM (dedicated)
- AMD EPYC™ 9535
- 8 vCore (dedicated)
- 16 GB DDR5 RAM (ECC)
- 512 GB NVMe SSD
GPU 14 GB VRAM
- NVIDIA™ H200
- 14 GB VRAM (dedicated)
- AMD EPYC™ 9535
- 12 vCore (dedicated)
- 32 GB DDR5 RAM (ECC)
- 1 TB NVMe SSD
🚀 High-Performance vGPU Solutions — Tailored for Demanding Workloads
Our cloud-based vGPU products deliver uncompromising GPU power for compute-intensive tasks, making them ideal for:
- 🧠 AI inferencing
- 🎥 Video processing & encoding
- 📊 Big Data & analytics
- 🎨 3D rendering & visualizations
With dedicated vGPU allocation per virtual machine, you get guaranteed resources and consistently high performance — without the overhead of physical GPU hardware.
⚡ Your Advantages with vGPU
🚀 GPU Power for Demanding Workloads
Accelerate compute-intensive applications with root servers enhanced by dedicated GPU power. From rendering and CAD to AI inferencing — faster results, greater efficiency.
🎨 Graphics-Intensive Applications from the Cloud
Run professional 3D designs, simulations, visualizations, and video production — all without owning hardware. Maximum performance, instantly available. Flexible. Scalable. Cloud-native.
🔒 Secure & Isolated Performance
Every VM gets its own dedicated vGPU. No resource sharing. No compromises. Full control and high security for every workload.
💰 Cost-Efficient Alternative to Physical GPUs
Avoid high upfront costs and long setup times. Our vGPU servers deliver tailored performance at a fraction of the price — ideal for AI, video encoding, and data analytics.
🛡️ GDPR-Compliant Data Protection
We’re ISO-certified and fully GDPR-compliant. Your data is hosted in certified data centers under strict security and privacy protocols — so you stay in control.
Frequently Asked Questions (FAQ)
Have technical questions about VRAM allocation, supported hypervisors, or compliance? We’ve compiled answers to the most common queries regarding our high-performance vGPU servers. If your question is not listed below, please contact our 24/7 technical support team.
What are vGPU servers and for which scenarios are the new products suitable?
vGPU servers are powerful root servers with permanently assigned, virtualized GPU performance (vGPU). They are particularly suitable for compute-intensive applications such as AI inferencing, video processing, 3D visualizations and data-driven analyses.
Do the vGPU products support CUDA Technology?
Yes, the NVIDIA™ H200 GPUs used support the CUDA platform and thus enable GPU-accelerated computing processes and parallel data processing.
Which images are used to deploy the vGPU servers?
The vGPU servers are currently provided exclusively with an Ubuntu image. This is because the required NVIDIA drivers are not freely available and are officially supported primarily on Ubuntu. As a result, no alternative images are offered at this time, and the vGPU servers can only be operated with the supplied Ubuntu image.
How are the servers billed?
Billing is monthly, based on a minimum contract term of just one month. So you remain flexible with full cost control.
Which hypervisor is used for instance virtualization?
The vGPU instances also use the KVM hypervisor in the Linux kernel – for stable and high-performance virtualization.
Can I upgrade my vGPU server plan without reinstalling the operating system or losing data?
Yes. Our platform is designed for seamless scaling. You can upgrade your vGPU plan (e.g., from 7 GB VRAM to 14 GB VRAM) directly through the Client Area. The upgrade typically requires a brief server reboot for the new hardware allocation to take effect, but your data and operating system configuration will remain intact.
Can I use a custom Docker image or container orchestration (Kubernetes) with the vGPU servers?
Yes. Since the vGPU servers are provided with a dedicated Ubuntu image, you have root access to install any necessary containerization technology. This allows you to deploy and manage complex environments using Docker, Docker Swarm, or Kubernetes (for large-scale model deployment and inference).
CyberWAF
Protect Your Website Fast.
About
WAF Platform
Privacy Policy
My Account
Login
Support
