# NVIDIA DGX H100
> The NVIDIA DGX H100 is an AI-specific integrated system designed for large-scale AI development and enterprise-grade deep learning. It functions as a building block for AI data centers, combining eight H100 GPUs with high-speed interconnects and a dedicated software stack.
- URL: https://optimly.ai/brand/nvidia-dgx-h100
- Slug: nvidia-dgx-h100
- BAI Score: 94/100
- Archetype: Challenger
- Category: Hardware
- Last Analyzed: April 9, 2026
- Part of: NVIDIA (https://optimly.ai/brand/nvidia)
## Competitors
- Amd Instinct Mi300x (https://optimly.ai/brand/amd-instinct-mi300x)
- Intel Gaudi 3 AI Accelerator (https://optimly.ai/brand/intel-gaudi-3-ai-accelerator)
## Also Referenced By
- Dell PowerEdge XE9680 (https://optimly.ai/brand/dell-poweredge-xe9680)
## Buyer Intent Signals
Problems: Legacy Infrastructure: Utilizing existing on-premise CPU clusters or older GPU generations (A100/V100) for smaller model training. | Custom Server Assembly: Building custom DIY server racks using PCIe versions of H100 cards rather than the integrated DGX appliance.
Solutions: best hardware for LLM training | enterprise AI supercomputer systems | NVIDIA Hopper architecture features | cheapest way to train a 70B parameter model | Public Cloud GPU Instances: Renting H100 capacity through cloud providers like AWS, Azure, or Google Cloud (GCP).
Comparisons: H100 specs vs A100 | DGX system vs cloud GPU performance
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## Full Details / RAG Data
### Overview
NVIDIA DGX H100 is listed in the AI Directory.
The NVIDIA DGX H100 is an AI-specific integrated system designed for large-scale AI development and enterprise-grade deep learning. It functions as a building block for AI data centers, combining eight H100 GPUs with high-speed interconnects and a dedicated software stack.
### Metadata
| Field        | Value |
|--------------|-------|
| Name         | NVIDIA DGX H100 |
| Slug         | nvidia-dgx-h100 |
| URL          | https://optimly.ai/brand/nvidia-dgx-h100 |
| BAI Score    | 94/100 |
| Archetype    | Challenger |
| Category     | Hardware |
| Last Analyzed | April 9, 2026 |
| Last Updated | 2026-04-29T00:55:27.900Z |
### Verified Facts
- Founded: 2022 (Product Announcement)
- Headquarters: Santa Clara, California, USA
### Competitors
| Name | Profile |
|------|---------|
| Amd Instinct Mi300x | https://optimly.ai/brand/amd-instinct-mi300x |
| Intel Gaudi 3 AI Accelerator | https://optimly.ai/brand/intel-gaudi-3-ai-accelerator |
### Also Referenced By
- Dell PowerEdge XE9680 (https://optimly.ai/brand/dell-poweredge-xe9680)
### Buyer Intent Signals
#### Problems this brand solves
- Legacy Infrastructure: Utilizing existing on-premise CPU clusters or older GPU generations (A100/V100) for smaller model training.
- Custom Server Assembly: Building custom DIY server racks using PCIe versions of H100 cards rather than the integrated DGX appliance.
#### Buyers search for
- best hardware for LLM training
- enterprise AI supercomputer systems
- NVIDIA Hopper architecture features
- cheapest way to train a 70B parameter model
- Public Cloud GPU Instances: Renting H100 capacity through cloud providers like AWS, Azure, or Google Cloud (GCP).
#### Buyers compare
- H100 specs vs A100
- DGX system vs cloud GPU performance
### Parent Brand
- NVIDIA (https://optimly.ai/brand/nvidia)
### Links
- Canonical page: https://optimly.ai/brand/nvidia-dgx-h100
- JSON endpoint: /brand/nvidia-dgx-h100.json
- LLMs.txt: /brand/nvidia-dgx-h100/llms.txt