Achieve over 100 teraFLOPS of Deep Learning performance with our NVIDIA V100 GPUs, significantly reducing model training times from weeks to days. Solve previously intractable problems with unprecedented speed and efficiency.
Leverage the raw power of the GPU V100 instances to analyze vast datasets and forecast trends with advanced AI algorithms. The NVIDIA V100 is built to enable rapid discovery of patterns and valuable insights within your data.
Get your artificial intelligence and HPC models running efficiently with our Tesla V100 instances, offering a highly competitive cost-to-performance ratio. Maximize your computational budget without compromising on power.
Exoscale GPU2 is based on NVIDIA Tesla V100 graphic cards known for unmatched performance for Tensor operations. The NVIDIA Volta GPU architecture, which underpins the V100, remains a significant milestone for artificial intelligence (AI) and high-performance computing (HPC). With 640 Tensor Cores, the V100 delivers over 125 TeraFLOPs per second (FP16), providing a substantial boost for many AI workloads.
The Tesla V100 is specifically designed to provide a robust computing engine for data science, machine learning, and deep learning. The combination of both NVIDIA CUDA and Tensor Cores results in a GPU that delivers high performance,
making it an excellent choice for a wide array of compute-intensive applications. While newer architectures exist, the V100 continues to offer a compelling balance of performance, accessibility, and cost-effectiveness.
In a world increasingly shaped by AI, reliable and high-performance infrastructure is essential. Powered by the NVIDIA Tesla V100, you can confidently build and run AI models. Accelerate your progress in computer vision, data analysis, or intelligent assistants with trusted performance and seamless scalability.
Data scientists drive innovation across every industry. Empower their AI and deep learning workflows with GPU V100. Optimized for frameworks like TensorFlow, PyTorch, and Caffe, our NVIDIA Tesla V100 based instances deliver the performance and stability needed for efficient model training and accelerated data analysis.
Accelerate neural network training with the NVIDIA Tesla V100, delivering over 100 teraFLOPS of Tensor Core performance. Ideal for large-scale computer vision, NLP, and other AI workloads.
Use GPU V100 instances to serve AI models with ultra-low latency—perfect for real-time applications like chatbots, fraud detection, and search personalization.
Our NVIDIA V100 instances are offered at a highly attractive cost-performance ratio. Choose between four different options, from 1 to 4 GPUs coming with SSD storage from 100 GB up to 1.6 TB depending on the chosen instance type.
| RAM | CPU Cores | GPU Cards | Min Local Storage | Max Local Storage | Price / Hour ({{ currency | uppercase }}) | |
|---|---|---|---|---|---|---|
| Small | 56 GB | 12 Cores | 1 GPU | 100 GB | 800 GB | {{ prices.opencompute.gpu2.small[currency] | number:8 }} |
| Medium | 90 GB | 16 Cores | 2 GPU | 100 GB | 1.2 TB | {{ prices.opencompute.gpu2.medium[currency] | number:8 }} |
| Large | 120 GB | 24 Cores | 3 GPU | 100 GB | 1.6 TB | {{ prices.opencompute.gpu2.large[currency] | number:8 }} |
| Huge | 225 GB | 48 Cores | 4 GPU | 100 GB | 1.6 TB | {{ prices.opencompute.gpu2.huge[currency] | number:8 }} |
Local Storage is not included in the displayed Instances price, and has a cost of {{ prices.opencompute.volume[currency] | number:8 }} {{ currency | uppercase }} / GiB hour.
Instance needs to be shutdown for hypervisor and platform updates as it cannot be live-migrated.
Available in the following Zones: AT-VIE-1
Please note that GPU instances require account validation: access is provided with priority to established businesses, and is granted after a manual screening process.
Combine the simplicity and scalability of the Exoscale Cloud with the power of NVIDIA GPUs. With our Docker based template you can access the full potential of the NVIDIA GPU Cloud (NGC) and significantly reduce time to solution.
NVIDIA GPU Cloud (NGC) provides a selected set of GPU-optimized software for artificial intelligence applications,
visualizations and HPC. The NGC Catalog includes containers, pre-trained models, Helm charts for Kubernetes deployments
and specific AI toolkits with SDKs.
NGC catalog works with both Exoscale Compute Instances and Exoscale Hosted & Managed Kubernetes.
The image template for Kubernetes worker nodes embeds the optimized version of the container runtime for NVIDIA V100 GPUs—so you can launch workloads without worrying about drivers or CUDA compatibility.
NVIDIA V100 instances come with large SSD storage up to 1.6 TB to accommodate any kind of data.
Each card is provided directly with no resource sharing for bare metal performance.
Each NVIDIA V100 card offers 16GB of dedicated GPU RAM, ideal for loading even the largest datasets. This is further complemented by instance RAM allocations, ensuring smooth data handling and processing.
The GPU2 Tesla V100 is specifically optimized for a wide spectrum of deep learning applications, as well as general AI and High-Performance Computing (HPC) tasks, ensuring maximum efficiency and accelerated training.
Leverage the proven power of NVIDIA Tesla V100 GPUs, offering substantial compute performance for demanding AI and HPC workloads. While newer architectures are available, V100 instances continue to provide a compelling balance of performance, accessibility, and cost-effectiveness.
As a sovereign European Cloud Provider, Exoscale ensures all your data is stored in the country of your chosen zone, fully GDPR compliant.
| Description | Specifications |
|---|---|
| Graphic Card | Tesla V100 |
| Cuda Cores per card | 5120 |
| Tensor Cores per card | 640 |
| GPU memory per card | 16 GB |
| GPU cards | 1-4 |
| CPU cores | 12-48 |
| RAM per instance | 56-225 |
| SSD local storage | max. 1.6 TB (SATA) |
| Zone | AT-VIE-1 |
| Works with | Compute SKS Docker NVIDIA |
When running mission-critical AI, deep learning, or HPC workloads in the cloud, a reliable partner makes all the difference. Our engineers have helped hundreds of customers across Europe migrate, run, and scale demanding workloads on NVIDIA Tesla V100 Instances with Exoscale.
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DiscoverThe NVIDIA V100, built on the pioneering Volta architecture, is a robust data center GPU that remains a powerful choice for AI, deep learning, and high-performance computing. Delivering up to 125 teraFLOPS and equipped with 16 GB of high-bandwidth memory, the Tesla V100 is ideal for a wide range of intensive training and inference workloads, offering a compelling balance of performance and cost-effectiveness.
NVIDIA Tesla V100 GPUs are commonly used to accelerate deep learning, run large-scale data science pipelines, and perform high-throughput AI inference. They’re especially suited for training models in natural language processing, computer vision, and scientific computing.
Yes. You can integrate NVIDIA V100 GPU instances with Exoscale services such as SKS (Managed Kubernetes), DBaaS, and Object Storage. Full Terraform and API support allow for seamless orchestration of your infrastructure.
GPU V100 instances offer dedicated GPU acceleration, which standard compute instances do not. They enable significantly faster processing for machine learning frameworks like TensorFlow or PyTorch and are optimized for both training and real-time inference tasks.
