NVIDIA DGX H100: The Most Trusted AI Platform
The NVIDIA DGX H100 is the most trusted and widely deployed AI system in enterprise environments. With 8x H100 SXM5 GPUs, the Hopper architecture delivers exceptional performance for both training and inference workloads. Thousands of DGX H100 systems power AI workloads across enterprises, research institutions, and cloud service providers worldwide, making it the industry standard for production AI.
Technical Specifications
| Component | Detailed Specification |
|---|---|
| GPU | 8x NVIDIA H100 SXM5 (80GB or 96GB variants available) |
| Total GPU Memory | 640GB / 768GB HBM2e |
| GPU Memory Bandwidth | 3.35 TB/s per GPU |
| CPU | 2x Intel Xeon Platinum 8480C (56 Cores each, 2.0GHz) |
| System Memory | 2TB DDR5-4800 |
| Storage | 30TB NVMe cache (8x 3.84TB) + 2x 1.92TB boot |
| Network | 8x ConnectX-7 400G InfiniBand |
| Management | Dual 1GbE BMC, IPMI |
| Power | 10x 3000W Titanium PSUs |
| Form Factor | 8U DGX chassis |
| Software | NVIDIA AI Enterprise, Base Command Manager, NGC |
Key Features
- Transformer Engine – dedicated hardware for transformer model acceleration
- Fourth-gen NVLink – 900 GB/s GPU-to-GPU bandwidth
- Confidential Computing support for secure AI workloads
- MIG (Multi-Instance GPU) for GPU partitioning
- DPX instructions for dynamic programming acceleration
Deployment Highlights
- Most production-proven DGX platform – thousands deployed globally
- Extensive ISV certification ecosystem – all major AI software validated
- Global installed base – largest community of DGX practitioners
- Mature software stack and tools with years of refinement
- Simplified procurement and support through global channels
Ideal Workloads
The DGX H100 powers production AI training at scale, enterprise inference serving, financial services algorithm development, healthcare and life sciences research, government and defense AI applications, and cloud service provider infrastructure.
Track Record
The DGX H100 has powered some of the world's most significant AI achievements, from large language models to scientific breakthroughs. Its reliability, performance, and software ecosystem make it the safe choice for organizations deploying AI in production.
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