Dell PowerEdge XE7745 with NVIDIA H100 NVL 94GB PCIe (4-GPU)

The Dell PowerEdge XE7745 is a purpose-built GPU-optimized server designed to meet the demands of large-scale AI training, inference, and high-performance computing workloads in enterprise and datacenter environments. Configured with four NVIDIA H100 NVL 94GB PCIe GPUs, this system delivers exceptional parallel compute density within a 4U rack form factor, leveraging NVIDIA's Hopper architecture to accelerate transformer-based AI models, deep learning frameworks, and scientific simulation pipelines at scale.

Each NVIDIA H100 NVL GPU in this configuration features 94GB of HBM2e memory and the second-generation Transformer Engine with FP8 precision support, enabling significantly faster training convergence for large language models and generative AI applications compared to prior generations. The H100 NVL PCIe variant allows flexible multi-GPU configurations without requiring NVLink SXM board topology, making it well-suited for enterprise deployments that prioritize PCIe interconnect compatibility and broad ecosystem support across AI software frameworks including PyTorch, TensorFlow, and RAPIDS.

The PowerEdge XE7745 platform is engineered to support AMD EPYC processors, high-bandwidth DDR5 memory, and enterprise-grade storage and networking options, providing a balanced host architecture that prevents CPU-to-GPU bottlenecks during intensive data ingestion and preprocessing stages. The system integrates Dell's OpenManage systems management tooling and iDRAC with Lifecycle Controller for remote monitoring, firmware management, and operational visibility, making it a production-ready infrastructure platform for AI-centric datacenter deployments across enterprise, research, and cloud-adjacent environments.

Ideal for

• Large language model (LLM) pre-training and fine-tuning for enterprise generative AI initiatives
• High-throughput AI inference serving for real-time natural language processing and computer vision applications
• Scientific high-performance computing including molecular dynamics, computational fluid dynamics, and climate modeling
• Multi-tenant GPU virtualization for internal AI platform-as-a-service deployments using NVIDIA vGPU or MIG partitioning
• Data analytics acceleration with GPU-native frameworks such as NVIDIA RAPIDS for large-scale tabular and graph data processing
• Video encoding, rendering pipeline acceleration, and media processing in broadcast and digital content enterprise environments

Technical specifications

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