NVIDIA H100
The NVIDIA H100 is an ideal choice for large-scale AI applications. It uses the NVIDIA Hopper architecture that combines advanced features and capabilities, accelerating AI training and inference on larger models.
NVIDIA H100
Infrastructure and technology partners
Perfect for a range of workloads
Deploying AI based workloads on CUDO Compute is easy and cost-effective. Follow our AI related tutorials.
Deploying rendering based workloads on CUDO Compute is easy and cost-effective
From video editing to image generation, virtualization is ideal for your content creation needs.
Purpose-built H100 clusters, designed and managed by CUDO
Deployed across 16 ISO-certified data centres
From 8 to 1,000+ GPUs in a single deployment
NVIDIA Quantum-X800 InfiniBand or Spectrum-X Ethernet networking
Expert rack-level design, installation, and benchmarking before handoff
24/7 monitoring, management, and engineering support
Compatible with Slurm, Kubernetes, and NVIDIA Base Command
Available at the most cost-effective pricing
Launch your AI products faster with on-demand GPUs and a global network of data center partners
Bare metal
Powered by renewable energy
No noisy neighbors
SpectrumX local networking
300Gbps external connectivity
NVMe SSD storage
Enterprise
Powerful GPU clusters
Scalable data center colocation
Large quantities of GPUs and hardware
Optimize to your requirements
Expert installation
Scale as your demand grows
Specifications
Browse specifications for the NVIDIA H100 GPU
Starting from
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Architecture
NVIDIA Hopper
GPU
8x NVIDIA H100 Tensor Core GPUs
GPU memory
640 GB total (80 GB per GPU), 24 TB/s aggregate bandwidth
FP64 tensor core performance
67 teraFLOPS
FP32
67 teraFLOPS
NVIDIA NVSwitch
4x Fourth-generation NVIDIA NVSwitch
NVIDIA NVLink bandwidth
7.2 TB/s aggregate bidirectional bandwidth (900 GB/s per GPU)
System power usage
~10.2 kW max
CPU
Dual Intel Xeon Platinum 8480C Processors (112 cores total) or AMD EPYC equivalents
System memory
2 TB, configurable to 4 TB
Networking
4x OSFP ports serving 8x single-port NVIDIA ConnectX-7 VPI (Up to 400 Gb/s NVIDIA InfiniBand/Ethernet) 2x dual-port QSFP112 NVIDIA ConnectX-7 VPI (Up to 400 Gb/s NVIDIA InfiniBand/Ethernet)
Management network
10Gb/s onboard NIC with RJ45, 100Gb/s Ethernet NIC. Host baseboard management controller (BMC) with RJ45
Storage
OS: 2x 1.9 TB NVMe M.2, internal storage: 8x 3.84 TB NVMe U.2
Software
NVIDIA AI Enterprise (optimized AI software), NVIDIA Base Command (orchestration and cluster management), NVIDIA DGX OS / Ubuntu / Red Hat Enterprise Linux / Rocky
Rack units (RU)
8
Operating temperature
5-30°C (41-86°F)
Ideal uses cases for the NVIDIA H100 GPU
Explore uses cases for the NVIDIA H100 including AI inference, Deep learning, High-performance computing.
AI inference
Engineers and scientists across various domains can leverage the NVIDIA H100 to accelerate AI inference workloads, such as image and speech recognition. The H100's powerful Tensor Cores enable it to quickly process large amounts of data, making it perfect for real-time inference applications.
Deep learning
The NVIDIA H100 Tensor Core GPU offers a diverse range of use cases for deep learning on larger models. The H100 revolutionizes deep learning for data scientists and researchers, allowing them to handle large datasets and perform complex computations for training deep neural networks.
High-performance computing
Many diverse organizations can deploy the NVIDIA H100 GPU to accelerate high-performance computing workloads, such as scientific simulations, weather forecasting, and financial modeling. With its high memory bandwidth and powerful processing capabilities, the H100 makes it easy to run workloads at every scale.
Blog
Resources
- Emmanuel Ohiri
Resources
- Emmanuel Ohiri
Resources
- Emmanuel Ohiri
Resources
- Emmanuel Ohiri
Resources
- Emmanuel Ohiri
Resources
- Emmanuel Ohiri
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NVIDIA H100 PCIe
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