The NVIDIA® V100 Tensor Core is one of the most powerful data center GPUs, built to accelerate AI, high-performance computing (HPC), data science, and graphics. Powered by the NVIDIA Volta architecture, it delivers the performance of up to 100 CPUs in a single GPU. Available in 16 GB and 32 GB variants, the V100 significantly reduces training time and boosts productivity for data scientists, researchers, and engineers. With less time spent optimizing memory usage, teams can focus on building the next breakthrough in AI and machine learning. The V100 revolutionized compute performance, making large-scale, data-intensive tasks faster and more efficient. Now available for rent, the Tesla V100 offers flexible access to enterprise-grade performance—no upfront hardware investment needed.
Built on NVIDIA's Volta architecture, the Tesla V100 integrates 640 Tensor Cores and 5,120 CUDA cores, delivering up to 125 teraflops of deep learning performance. This architecture enables significant acceleration for AI and HPC workloads.
The V100's Tensor Cores are designed to accelerate deep learning training and inference, offering up to 12x performance improvement over previous-generation GPUs.
Equipped with 16 GB or 32 GB of HBM2 memory, the Tesla V100 provides up to 900 GB/s memory bandwidth, facilitating rapid data access and processing for large-scale computations.
NVIDIA NVLink technology allows multiple V100 GPUs to be interconnected with up to 300 GB/s total bandwidth, enabling high-speed communication between GPUs for scalable performance.
The V100 supports mixed-precision computing, combining FP16 and FP32 operations to accelerate AI workloads while maintaining accuracy, leading to faster training times.
ECC memory support ensures data integrity by detecting and correcting memory errors, which is critical for mission-critical applications in data centers.
With NVIDIA Virtual Compute Server (vCS) software, the V100 enables secure and efficient GPU virtualization, allowing multiple users to share GPU resources effectively.
E2E’s GPU Cloud is suitable for a wide range of uses.
No hidden or additional charges. What you see on pricing charts is what you pay.
We are offering pay as you go model to long tenure plans. Easy upgrade allowed. Option to increase storage allowed.
We are NVIDIA Certified Elite Cloud Service provider partner. Build or launch pre-installed software Cloud GPUs to ease your work
E2E Cloud GPUs have super simple one click support for NGC containers for deploying NVIDIA certified solutions for AI/ML/NLP/Computer Vision and Data Science workloads.
We are using NVIDIA certified hardware for GPU accelerated workloads.
For over a decade, we have delighted our customers with stellar infrastructure and support.
E2E Networks Ltd is an India-focused Cloud Computing Company, pioneering the introduction of contract-less cloud computing for Indian startups and SMEs. The E2E Networks Cloud has been employed by numerous successfully scaled-up startups such as Zomato, Cardekho, Healthkart, Junglee Games, 1mg, and many others. It played a crucial role in facilitating their growth from the startup stage to achieving multi-million Daily Active Users (DAUs).
32 GB.
Monthly prices shown are calculated using an assumed usage of 730 hours per month; actual monthly costs may vary based on the number of days in a month.
The Tesla V100 is designed for accelerating AI training, inference, high-performance computing (HPC), and data science workloads. It’s ideal for researchers, data scientists, and developers working on deep learning, simulations, and large-scale data processing.
The Tesla V100 is available in two configurations: 16 GB and 32 GB of HBM2 memory, offering up to 900 GB/s memory bandwidth for fast data throughput.
The V100 delivers up to 12x higher performance for AI workloads compared to the previous generation (e.g., P100), thanks to its Tensor Cores, Volta architecture, and NVLink interconnect.
Yes! You can rent the V100 GPU for flexible, cost-effective access without needing to invest in hardware, ideal for short-term projects or scaling up temporarily.
Absolutely. The V100’s Tensor Cores and mixed-precision capabilities make it highly efficient for AI inference, delivering fast and accurate results in production environments.
Yes, with NVIDIA Virtual Compute Server (vCS), the V100 supports secure, multi-tenant GPU virtualization for data center environments.
