NVIDIA DGX H200: Unleashing Memory-Bound AI Performance

The NVIDIA DGX H200 harnesses the power of NVIDIA H200 Tensor Core GPUs with 141GB HBM3e memory per GPU, providing a total of 1,128GB of high-bandwidth GPU memory. This system is specifically designed for models that exceed traditional GPU memory capacity, enabling larger batches, longer context windows, and reduced model parallelization overhead. The H200 represents the evolution of the Hopper architecture, optimized for the most memory-demanding AI workloads.

Technical Specifications

ComponentDetailed Specification
GPU8x NVIDIA H200 141GB SXM5 (HBM3e memory)
Total GPU Memory1,128 GB HBM3e
GPU Memory Bandwidth4.8 TB/s per GPU
CPU2x Intel Xeon Platinum 8480C (56 Cores each, 2.0GHz base)
System Memory2TB DDR5-4800
Storage30TB NVMe cache + 2x 1.92TB boot NVMe
Network8x ConnectX-7 400G InfiniBand
Power10x 3000W Titanium PSUs
Form Factor8U DGX chassis
CoolingLiquid-cooled option available
SoftwareNVIDIA AI Enterprise, Base Command Manager

Memory Advantage

Performance vs H100

Ideal Workloads

The DGX H200 excels in massive language models with 100B+ parameters, long-context applications with 50K+ token sequences, generative AI with large batch sizes, memory-bound HPC simulations, graph neural networks on large graphs, and multi-modal models combining vision and language.

Why Choose DGX H200?

When your AI models are memory-bound rather than compute-bound, the DGX H200 delivers transformative performance. The massive HBM3e capacity enables researchers to explore larger models, longer sequences, and more complex architectures without the complexity of heavy parallelization strategies.

Request a Quote

Contact Omnixon Global for competitive pricing on the NVIDIA DGX H200. Our team can help you determine the optimal configuration for your memory-intensive AI workloads.