HPE ProLiant Compute XD685 Server

The HPE ProLiant Compute XD685 is a purpose-built, high-density accelerated compute server designed to meet the rigorous demands of generative AI training, large language model development, and deep learning at enterprise and hyperscale levels. The system is architected around an eight-GPU configuration, supporting either the NVIDIA HGX H200 SXM5 platform with NVLink interconnect or the AMD Instinct MI325X accelerators, giving organizations flexibility to align their AI infrastructure investment with their preferred GPU ecosystem. The server is designed for rack-dense deployment within HPE's broader AI Supercomputing portfolio, integrating seamlessly with HPE Cray networking and storage fabrics for end-to-end AI cluster buildouts.

At its core, the XD685 leverages AMD EPYC processors to deliver the PCIe bandwidth, memory capacity, and I/O throughput required to keep eight high-performance accelerators fully fed. The system supports high-bandwidth NVLink or Infinity Fabric interconnects between GPUs depending on the accelerator configuration, enabling collective operations and model-parallel training to scale efficiently across nodes. HPE's thermal and power delivery architecture is engineered to sustain the extreme power envelopes associated with eighth-generation GPU accelerators, incorporating advanced direct liquid cooling readiness and high-efficiency power supply redundancy.

The XD685 is a central building block for organizations constructing on-premises AI supercomputing clusters, national AI research infrastructure, and enterprise AI factories. Its integration with HPE GreenLake for HPC and AI provides a consumption-based operational model, while HPE's Integrated Lights-Out (iLO) management delivers deep telemetry, remote management, and security root-of-trust capabilities. The platform is validated for deployment with HPE Slingshot high-speed interconnect fabric, enabling low-latency, high-bandwidth GPU-to-GPU communication across multi-rack AI training clusters essential for frontier model development.

Ideal for

• Training large language models and transformer-based foundation models requiring sustained multi-node GPU parallelism across thousands of accelerators
• Generative AI model development including diffusion models, multimodal AI, and reinforcement learning from human feedback pipelines at enterprise scale
• National and institutional AI research supercomputing clusters requiring dense GPU packing per rack unit with high-speed fabric connectivity
• Enterprise AI factories running simultaneous fine-tuning workloads across multiple business units with shared accelerated infrastructure
• High-performance scientific simulation and computational fluid dynamics workloads that benefit from GPU-accelerated numerical solvers
• Financial services AI platforms performing large-scale risk modeling, fraud detection training, and quantitative research requiring GPU-accelerated compute

Technical specifications

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