NVIDIA H200 SXM5 141GB HBM3e – Dell PowerEdge XE9680

The NVIDIA H200 SXM5 141GB HBM3e, integrated into the Dell PowerEdge XE9680, represents the current pinnacle of GPU-accelerated computing for enterprise data centers. Built on NVIDIA's Hopper architecture, the H200 advances on its predecessor by delivering 141GB of HBM3e memory with a 4.8TB/s memory bandwidth — a substantial increase that directly addresses the memory capacity and throughput demands of large-scale generative AI inference, LLM training, and high-performance computing workloads. The SXM5 form factor enables high-bandwidth NVLink and NVSwitch interconnects, allowing the eight GPUs within the XE9680 chassis to function as a tightly coupled accelerator fabric.

The Dell PowerEdge XE9680 is purpose-engineered as an 8-GPU AI and HPC platform, providing the mechanical, thermal, and power infrastructure required to sustain full H200 SXM5 performance at data center scale. The system supports NVLink interconnects delivering up to 900GB/s GPU-to-GPU bandwidth, and integrates PCIe Gen 5 host connectivity alongside high-speed InfiniBand or Ethernet networking options for cluster-scale deployments. The chassis design accommodates the substantial thermal envelope of eight H200 GPUs operating concurrently under sustained AI training workloads.

For organizations deploying foundation model training, large-language model inference at scale, scientific simulation, or AI-driven data analytics, the H200 SXM5 141GB within the XE9680 platform delivers the memory capacity needed to host multi-hundred-billion parameter models on a single node while reducing inter-node communication overhead. The combination of HBM3e memory technology, Hopper Transformer Engine with FP8 precision support, and the dense 8-GPU SXM5 configuration makes this platform a strategic infrastructure investment for enterprise AI, research institutions, and cloud service providers operating across the UAE, GCC, EMEA, and APAC regions.

Ideal for

• Training and fine-tuning large language models (LLMs) and foundation models with hundreds of billions of parameters on a single node
• High-throughput generative AI inference serving for enterprise-scale natural language processing, code generation, and multimodal applications
• Computational fluid dynamics, molecular dynamics, and climate modeling HPC workloads requiring sustained double-precision throughput
• AI-driven drug discovery and genomics research demanding large in-memory datasets and high memory bandwidth
• Deep learning recommendation model (DLRM) training and serving for large-scale e-commerce and digital media platforms
• Enterprise data center consolidation of GPU compute for mixed AI training and HPC simulation workloads within a single high-density 9U chassis

Technical specifications

Available from Omnixon Global. Submit an RFQ and our team will confirm configuration and availability for your order.