Powerful AI compute accelerator for AI and HPC
Turn complex models into real-time results with GPU speed.
- Fast AI Training
- Neural Network Ready
- Effortless HPC Power
GPU Droplets plan
Reliably run training and inference on AI/ML models, process large data sets and complex neural networks for deep learning use cases, and serve additional use cases like high-performance computing (HPC). The prices listed below are subject to change.
AMD Instinct™ MI300X×8
On-Demand Price
Features
- ✅8× AMD Instinct™ MI300X GPUs
- ✅1,920 GiB system memory
- ✅160 vCPUs
- ✅1.25 TiB NVMe boot storage
- ✅40 TiB NVMe scratch storage
- ✅80,000 GiB transfer bandwidth
NVIDIA H100×8
On-Demand Price
Features
- ✅8× NVIDIA H100 GPUs
- ✅1,920 GiB system memory
- ✅160 vCPUs
- ✅1.25 TiB NVMe boot storage
- ✅40 TiB NVMe scratch storage
- ✅80,000 GiB transfer bandwidth
Features
- ✅1× NVIDIA H100 GPU
- ✅240 GiB system memory
- ✅20 vCPUs
- ✅700 GiB NVMe boot storage
- ✅5 TiB NVMe scratch storage
- ✅15,000 GiB transfer bandwidth
AMD Instinct™ MI300X
On-Demand Price
Features
- ✅1× AMD Instinct™ MI300X GPU,
- ✅240 GiB system memory
- ✅20 vCPUs
- ✅700 GiB NVMe boot storage
- ✅5 TiB NVMe scratch storage
- ✅15,000 GiB transfer bandwidth
NVIDIA RTX 4000 Ada Generation
On-Demand Price
Features
- ✅1× NVIDIA RTX 4000 Ada GPU
- ✅32 GiB system memory
- ✅2 vCPUs
- ✅20 GiB GPU memory
- ✅500 GiB NVMe boot storage
- ✅10,000 GiB transfer bandwidth
NVIDIA RTX 6000 Ada Generation
On-Demand Price
Features
- ✅1× NVIDIA RTX 6000 Ada GPU
- ✅48 GiB GPU memory
- ✅64 GiB system memory
- ✅8 vCPUs
- ✅500 GiB NVMe boot storage
- ✅10,000 GiB transfer bandwidth
Features
- ✅1× NVIDIA L40S GPU,
- ✅48 GiB GPU memory
- ✅64 GiB system memory
- ✅8 vCPUs
- ✅500 GiB NVMe boot storage
- ✅10,000 GiB transfer bandwidth
Why Choose AI compute servers for AI & HPC?
GPU servers combine powerful graphics processors with Cloudoora’s cloud infrastructure, enabling resource-intensive AI and HPC workloads to run efficiently:
Powered by dedicated NVIDIA RTX and A100 GPUs for maximum compute power
Use Cases of AI compute accelerator in AI & HPC
GPU compute for AI excel in compute-heavy environments like:
Deep Learning
Model training and inference for AI applications
Scientific Research
Simulations and complex computational experiments
Video Rendering
High-quality graphics processing and animation
Big Data
Analytics and large-scale data processing
HPC Tasks
High-performance computing for demanding workloads
Game Development
Real-time rendering and physics simulations
Optimized Hardware and Software for AI Workloads
Our AI accelerator cloud are built with premium hardware and pre-configured for AI workloads:
Dedicated RTX and A100 GPUs for high throughput
NVMe SSD storage for fast I/O and data handling
Support for Ubuntu, CUDA, TensorFlow, PyTorch, and more
Multi-region deployments for global reach
Our expert team is available around the clock to help you deploy, optimize, and maintain your GPU workloads with confidence and ease.
24/7 Support for AI & HPC Deployments
Fast, Responsive Support
Live chat, email, and ticket assistance anytime you need help
In-Depth AI & HPC Guides
Comprehensive tutorials and best practices for AI and HPC environments
Continuous Platform Improvementss Updates
Benefit from regular updates, security patches, and performance enhancements to keep your environment secure and efficient.
Start Your AI & HPC Projects with high performance GPU Servers
Deploy powerful AI compute servers to handle the most demanding AI, machine learning, and HPC workloads with ease and speed.
Frequently Asked Questions
A GPU server uses powerful graphics processors (GPUs) to handle complex computations. They are ideal for AI model training, deep learning, big data analytics, and high-performance computing (HPC) tasks because they process data much faster than traditional CPUs.
Both NVIDIA and AMD GPUs deliver excellent performance. NVIDIA H100 and RTX series are widely used for deep learning, while AMD Instinct MI300X offers strong performance for HPC and large-scale AI tasks. The choice depends on your workload and budget.
Yes. Our GPU servers fully support popular AI and machine learning frameworks like TensorFlow, PyTorch, CUDA, and more, so you can deploy and train models seamlessly.
Pricing starts at €1,927.50/month and varies depending on the GPU model (NVIDIA H100, RTX, AMD Instinct, etc.). You only pay for what you use, making it flexible and cost-efficient.
Cloud GPU servers save you upfront hardware costs, provide instant scalability, and include ongoing maintenance and 24/7 support. This makes them more affordable and reliable compared to managing physical servers.
Yes. GPU servers are widely used in scientific simulations, genomics, climate modeling, video rendering, and large-scale data analytics due to their ability to handle complex and parallel computations.
Absolutely. Our GPU droplets can be deployed in multiple regions, giving you low-latency performance and flexibility for global AI, ML, and HPC workloads.
Yes. We offer 24/7 expert support via live chat, email, and tickets to help you deploy, optimize, and maintain your AI and HPC workloads.