NVIDIA DGX B200: The Sweet Spot in Enterprise AI
The NVIDIA DGX B200 represents the sweet spot in the DGX portfolio, offering exceptional price-performance for organizations building out AI infrastructure. With 8x B200 GPUs and balanced system architecture, it handles both training and inference workloads with ease. The B200 is optimized for organizations that need versatility—capable of training medium-to-large models while also excelling at high-throughput inference serving.
Technical Specifications
| Component | Detailed Specification |
|---|---|
| GPU Complex | 8x NVIDIA B200 GPUs with fourth-gen NVLink |
| GPU Memory | 144GB HBM3e per GPU (1.15TB aggregate) |
| CPU | 2x Intel Xeon Platinum 8570 (56 Cores each, 2.5GHz base) |
| System Memory | 1.5TB DDR5-5600 (configurable up to 2TB) |
| OS Storage | 2x 1.92TB NVMe SSD (RAID-1) |
| Data Storage | 6x 3.84TB NVMe SSD (configurable) |
| Network Fabric | 8x ConnectX-7 400G InfiniBand (upgradeable to 800G) |
| Power Supply | 10x 3000W Titanium PSUs (redundant) |
| Form Factor | 8U rack chassis |
| Software | NVIDIA AI Enterprise, Base Command Manager Lite |
Key Features
- Optimized for mixed workloads – seamlessly handles training and inference
- Lower TCO for volume deployments – ideal for scaling AI capacity
- Full DGX software compatibility – same enterprise stack as B300
- Scalable clustering – up to 256 DGX B200 nodes in SuperPOD
- Balanced memory-to-compute ratio for diverse AI models
Performance Highlights
- Training Throughput: 3.5x faster than previous generation for LLMs
- Inference Performance: 5x lower latency for transformer models
- Energy Efficiency: 2.3x better performance-per-watt
Ideal Workloads
The DGX B200 is ideal for enterprise AI training with models up to 100B parameters, high-throughput inference serving, retrieval-augmented generation (RAG) pipelines, computer vision and video analytics, financial services risk modeling, and recommender systems.
Request a Quote
Contact Omnixon Global for competitive pricing on the NVIDIA DGX B200. Our team provides custom configurations and deployment support for your AI infrastructure.