Dell PowerEdge XE9680 H100 SXM5 GPU Server (8x H100)

The Dell PowerEdge XE9680 is a purpose-built 8-socket GPU server designed to house eight NVIDIA H100 SXM5 80GB GPUs in a high-density, thermally optimized 8U chassis. Powered by NVIDIA's Hopper architecture, each H100 SXM5 GPU delivers up to 3.9 TFLOPS of FP64 Tensor Core performance and 3,958 TFLOPS of FP8 Tensor Core throughput, with a 700W TDP per GPU. The server leverages NVIDIA NVLink 4th Generation interconnects and NVSwitch 3.0 fabric, providing 900 GB/s of all-to-all GPU bandwidth across all eight accelerators — enabling the GPUs to function as a unified, high-bandwidth compute pool rather than discrete independent devices.

The XE9680 is engineered around dual 4th Gen Intel Xeon Scalable processors and supports up to 8TB of DDR5 system memory across 32 DIMM slots, feeding the GPU complex without CPU memory bandwidth becoming a bottleneck. The chassis accommodates PCIe Gen 5 connectivity for high-throughput NIC and storage I/O, and supports NVIDIA Quantum-2 InfiniBand or high-speed Ethernet networking to enable multi-node GPU cluster formation for large-scale distributed training. Internal NVMe SSD storage options and a redundant, hot-plug power subsystem rated for the full 10kW-class load of eight H100 SXM5 accelerators are integrated into the design.

As a validated Dell and NVIDIA joint reference platform, the XE9680 is supported by Dell's OpenManage systems management ecosystem and is compatible with NVIDIA AI Enterprise software, CUDA 12.x, cuDNN, TensorRT, and the full NVIDIA NGC catalog of containerized AI frameworks. The system is positioned as a foundational infrastructure node for on-premises AI factories, sovereign AI deployments, and large-scale HPC clusters serving enterprise buyers across the UAE, GCC, EMEA, and APAC regions.

Ideal for

• Large language model (LLM) pre-training and fine-tuning at scale, leveraging NVLink-connected GPU memory pooling up to 640GB aggregate HBM3 capacity across all eight H100 SXM5 GPUs
• High-performance deep learning inference for latency-sensitive enterprise AI applications, utilizing TensorRT optimization and H100 Transformer Engine with FP8 precision
• Generative AI workloads including image synthesis, multimodal model serving, and retrieval-augmented generation (RAG) pipelines requiring sustained high-throughput GPU compute
• Computational fluid dynamics (CFD), finite element analysis (FEA), and molecular dynamics simulations in scientific HPC environments demanding FP64 double-precision GPU performance
• Multi-node distributed training clusters for foundation model development, interconnected via NVIDIA Quantum-2 InfiniBand at 400Gb/s for low-latency collective communication operations
• Sovereign AI and on-premises AI factory deployments for government, financial services, and regulated industries requiring dedicated, air-gapped GPU infrastructure under direct organizational control

Technical specifications

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