ASUS RS700A-E11-RS12U 12-Bay GPU Server

The ASUS RS700A-E11-RS12U is a 1U rack-mounted GPU server engineered for high-density AI inference, deep learning training, and HPC workloads demanding exceptional compute throughput within a compact footprint. Built on the AMD EPYC 7003 series processor platform (codenamed Milan), it supports dual-socket CPU configurations and accommodates up to 12 front-accessible NVMe or SAS/SATA drive bays, making it suitable for data-intensive enterprise and datacenter deployments. The platform supports PCIe 4.0 across its expansion architecture, enabling high-bandwidth connectivity between CPUs, GPUs, and storage subsystems.

The RS700A-E11-RS12U supports multiple GPU or accelerator cards through its rear-facing PCIe slots, with the chassis and power subsystem designed to handle the thermal and electrical demands of modern accelerator hardware. Dual redundant power supply units ensure operational continuity in mission-critical environments, while the system's thermal design incorporates high-airflow cooling to sustain sustained GPU and CPU performance under full load. The server supports large memory configurations via its DDR4 DIMM slots across both sockets, providing the memory bandwidth required for large-scale model training and real-time inference pipelines.

Targeted at enterprises deploying AI infrastructure, GPU-accelerated analytics, and scientific computing clusters, the RS700A-E11-RS12U integrates ASUS ASMB10-iKVM out-of-band management for remote monitoring, power control, and BIOS configuration without requiring physical access. Its 1U form factor maximizes rack density in datacenter environments across AI research institutions, cloud service providers, and enterprise IT departments operating across regions including the UAE, GCC, EMEA, and APAC.

Ideal for

• Large-scale deep learning model training using GPU accelerators for AI research and enterprise MLOps pipelines
• High-throughput AI inference serving for real-time natural language processing, computer vision, and recommendation systems
• HPC simulation and scientific computing workloads requiring high CPU core counts paired with GPU acceleration
• GPU-accelerated data analytics and in-memory processing for financial modeling and enterprise business intelligence
• Virtualized GPU workloads supporting multiple concurrent users in VDI or cloud-hosted AI development environments
• Edge datacenter and regional AI deployment nodes requiring high compute density within constrained rack space

Technical specifications

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