ASUS RS720Q-E12-RS8U 2U Quad-Node GPU Microserver

The ASUS RS720Q-E12-RS8U is a 2U quad-node GPU microserver engineered for high-density enterprise compute, AI inference, and parallel processing workloads. Built on the Intel Xeon Scalable (Sapphire Rapids) platform, the chassis houses four independent server nodes within a single 2U rack footprint, each node capable of supporting independent processors, memory, storage, and GPU expansion. This architecture delivers exceptional compute density, making it a purpose-built solution for hyperscale datacenters and enterprise AI infrastructure seeking to maximize per-rack throughput without proportionally expanding physical footprint.

Each node in the RS720Q-E12-RS8U is designed to accommodate discrete GPU acceleration, enabling distributed AI training, large-scale inference serving, and high-performance computing tasks across all four nodes simultaneously. The system supports PCIe Gen 5 connectivity, providing the necessary bandwidth headroom for modern GPU workloads and NVMe storage devices. Enterprise-grade reliability features including redundant power supply configurations and ASUS ASMB management controllers provide out-of-band IPMI-based server management, supporting ASUS Control Center and industry-standard DCIM tooling for lifecycle management across large-scale deployments.

The RS720Q-E12-RS8U is positioned as a converged, high-density platform suitable for organizations deploying GPU-accelerated workloads at scale, including generative AI model serving, scientific simulation, media transcoding, and financial analytics. Its multi-node design allows independent node management, failure isolation, and workload segmentation while sharing a common chassis infrastructure, reducing cabling complexity and power distribution overhead compared to equivalent single-node deployments. Omnixon Global supplies this platform to enterprise and datacenter customers across UAE, GCC, EMEA, and APAC regions.

Ideal for

• Large-scale AI inference serving with multiple independent GPU-accelerated nodes operating concurrently within a single 2U chassis
• Distributed deep learning training across quad-node configurations, enabling parallel workload segmentation for faster model iteration
• High-density HPC cluster deployments in space-constrained datacenter environments requiring maximum compute-per-rack-unit efficiency
• Enterprise media and content processing pipelines, including GPU-accelerated video transcoding and rendering at datacenter scale
• Multi-tenant cloud or managed service infrastructure where workload and billing isolation across independent nodes is operationally required
• Scientific research computing environments demanding flexible, independently configurable nodes for diverse simulation and data analytics workloads

Technical specifications

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