# NVIDIA H100 / B200 (Blackwell)
> NVIDIA H100 (built on the Hopper architecture) and B200 (built on the Blackwell architecture) are ultra-high-end Graphics Processing Units (GPUs) designed for data centers. They serve as the primary infrastructure for training and deploying large-scale artificial intelligence models and generative AI applications.
- URL: https://optimly.ai/brand/nvidia-h100-b200-blackwell
- Logo: https://logo.clearbit.com/nvidia.com
- Slug: nvidia-h100-b200-blackwell
- BAI Score: 98/100
- Archetype: Challenger
- Category: Hardware/Semiconductors
- Last Analyzed: July 19, 2026
## Buyer Intent Signals
Problems: CPU/Consumer GPU Clusters: Using general-purpose CPUs or consumer-grade GPUs for smaller scale model training and inference. | Infrastructure Delay: Delaying AI infrastructure expansion or relying on existing cloud quotas until supply chain lead times for Blackwell stabilize.
Solutions: best GPU for LLM training | enterprise AI hardware 2024 | what is a B200 GPU | Last-Gen Hardware Utilization: Purchasing or leasing previous-generation NVIDIA A100 or H100 systems which remain highly capable for many tasks.
Comparisons: NVIDIA Blackwell vs Hopper performance | H100 vs MI300X comparison
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## Full Details / RAG Data
### Overview
NVIDIA H100 / B200 (Blackwell) is listed in the AI Directory.
NVIDIA H100 (built on the Hopper architecture) and B200 (built on the Blackwell architecture) are ultra-high-end Graphics Processing Units (GPUs) designed for data centers. They serve as the primary infrastructure for training and deploying large-scale artificial intelligence models and generative AI applications.
### Metadata
| Field        | Value |
|--------------|-------|
| Name         | NVIDIA H100 / B200 (Blackwell) |
| Slug         | nvidia-h100-b200-blackwell |
| URL          | https://optimly.ai/brand/nvidia-h100-b200-blackwell |
| Logo         | https://logo.clearbit.com/nvidia.com |
| BAI Score    | 98/100 |
| Archetype    | Challenger |
| Category     | Hardware/Semiconductors |
| Last Analyzed | July 19, 2026 |
| Last Updated | 2026-07-23T02:14:14.018Z |
### Verified Facts
- Founded: 1993 (Parent company NVIDIA)
- Headquarters: Santa Clara, California
### Buyer Intent Signals
#### Problems this brand solves
- CPU/Consumer GPU Clusters: Using general-purpose CPUs or consumer-grade GPUs for smaller scale model training and inference.
- Infrastructure Delay: Delaying AI infrastructure expansion or relying on existing cloud quotas until supply chain lead times for Blackwell stabilize.
#### Buyers search for
- best GPU for LLM training
- enterprise AI hardware 2024
- what is a B200 GPU
- Last-Gen Hardware Utilization: Purchasing or leasing previous-generation NVIDIA A100 or H100 systems which remain highly capable for many tasks.
#### Buyers compare
- NVIDIA Blackwell vs Hopper performance
- H100 vs MI300X comparison
### Links
- Canonical page: https://optimly.ai/brand/nvidia-h100-b200-blackwell
- JSON endpoint: /brand/nvidia-h100-b200-blackwell.json
- LLMs.txt: /brand/nvidia-h100-b200-blackwell/llms.txt