Deploy high-performance NVIDIA H200 GPUs
Run demanding AI workloads on powerful NVIDIA H200 GPUs with fast deployment, high-performance infrastructure, and scalable cloud compute designed for modern machine learning applications.
- Optimized for AI & LLM workloads
- High-performance GPU infrastructure
- Scalable cloud deployment
- Enterprise-grade compute performance
Starting at
€2.30 per GPU / hour
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NVIDIA H200 GPU Architecture
The NVIDIA H200 GPU is built on the Hopper architecture and delivers exceptional performance for modern AI workloads. With massive HBM3e memory capacity and extremely high memory bandwidth, H200 GPUs are designed to handle large language models, deep learning training, and high-performance computing tasks.
AI and HPC Performance
NVIDIA H200 GPUs are optimized for demanding AI and HPC environments where large datasets and complex computations require powerful acceleration.
Whether running AI training pipelines, LLM inference, or scientific simulations, H200 GPUs provide the compute performance needed to process large workloads efficiently while maintaining low latency and high scalability.
NVIDIA H200 GPUs Use Cases
AI Model Training
Train large-scale machine learning and deep learning models using the massive compute power of NVIDIA H200 GPUs. Ideal for training transformer models, neural networks, and large datasets.
LLM Inference
Deploy and run large language models (LLMs) such as GPT-style models, chatbots, and AI assistants with high-performance GPU inference.
High Performance Computing (HPC)
Accelerate scientific simulations, research workloads, and complex computational tasks that require massive parallel processing.
AI Data Processing
Process and analyze large datasets for AI pipelines, including preprocessing, feature extraction, and large-scale data analytics.
Rendering and Simulation
Run GPU-intensive workloads such as 3D rendering, video processing, and physics simulations that require powerful parallel GPU computing.
Flexible H200 GPU Pricing
H200 GPU
Flexible on-demand GPU compute for AI training, inference workloads, and high-performance applications.$2.30 per GPU / hour
Best Price
Top Featured
NVIDIA H200 GPU acceleration
141GB HBM3e GPU memory
Hourly pay-as-you-go billing
High-performance NVMe storage
Fast 10–100Gbps networking
Ideal for AI training and inference
Scalable GPU cloud infrastructure
Deploy within minutes
Optimized for LLM workloads
Enterprise GPU Infrastructure
Need large-scale GPU capacity for AI training clusters or enterprise workloads?$ Custom Pricing
For multi-GPU deployments and dedicated clusters Top Featured
Multi-GPU H200 clusters
Dedicated GPU servers
Custom CPU, RAM, and storage configurations
High-speed GPU networking infrastructure
Designed for AI training and HPC workloads
Enterprise-grade performance and reliability
Scalable AI compute environments
Priority technical support
Enterprise Features of NVIDIA H200 GPU Servers
Extreme AI Training Performance
Leverage the massive compute power of NVIDIA H200 GPUs to train large-scale AI models, deep neural networks, and complex machine learning workloads with exceptional speed and efficiency.
Large HBM3e GPU Memory
H200 GPUs provide high-capacity HBM3e memory designed for demanding AI workloads, large language models, and high-performance data processing pipelines.
Optimized for LLM Workloads
Run modern large language models and AI inference workloads efficiently with GPU architecture optimized for transformer models and generative AI applications.
High-Speed GPU Infrastructure
Our GPU servers are deployed on high-performance infrastructure with NVMe storage and fast networking, ensuring low latency and maximum compute performance.
Scalable GPU Deployment
Easily scale your compute environment from a single GPU instance to multi-GPU workloads depending on your AI training or inference requirements.
Flexible Cloud or Dedicated Deployment
Choose between on-demand cloud GPU instances for flexible workloads or dedicated GPU servers for long-running AI training and enterprise deployments.
Need Help Choosing the Right GPU Infrastructure?
GPU Server Frequently Asked Questions
Find answers to common questions about NVIDIA H200 GPU servers, deployment options, Preisgestaltung, and AI workload capabilities.
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Our Object Storage infrastructure is hosted in high-performance European data centers. This ensures low latency, strong data protection standards, and full compliance with GDPR regulations. Additional locations may be added in the future as the platform expands.
Uploading data to Object Storage (ingress traffic) is completely free. You can upload files, Backups, or application data without any transfer costs.
The included monthly quota also includes outgoing traffic. Additional outgoing traffic beyond the included amount is billed separately.
No. The included storage and traffic quota applies to the total usage across all buckets in your account, not per bucket.
You can create multiple buckets and distribute your data across them while still using the same shared quota.
Storage usage is calculated using TB-hours (TB-h). This method measures both the amount of stored data and the duration it remains stored.
Our Object Storage service is fully S3-compatible, which means it works with a wide range of existing tools and SDKs.
You can manage buckets, upload files, and control permissions using tools such as:
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AWS CLI
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rclone
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S3 compatible SDKs
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Backup software supporting S3 APIs
This allows easy integration with existing workflows and applications.
Incoming traffic (Uploads) is free of charge.
Outgoing traffic beyond the included quota is billed at $1.20 per TB. This makes it suitable for backups, application storage, and scalable data workloads.
Object Storage is designed for scalable data workloads and is commonly used for:
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Backup and disaster recovery
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Media storage (Bilder, videos, assets)
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Static website files
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Application data storage
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Log and archive storage
It is ideal for handling large amounts of unstructured data.
You can create multiple buckets within your Object Storage account to organize your data. Buckets allow you to separate projects, Anwendungen, or environments while managing everything under the same storage quota.
Ja. Our Object Storage platform uses redundant storage infrastructure to protect your data against hardware failures. Data is stored across multiple storage nodes to ensure durability and high availability. This redundancy helps prevent data loss and keeps your files accessible even if a hardware component fails.
Ja. Our Object Storage is fully S3-compatible, meaning it supports the same API structure used by Amazon S3. This allows you to use existing tools and integrations such as AWS CLI, rclone, backup software, and S3 SDKs without modifying your workflow.