Supermicro SYS-821GE-TNHR2 8x H100/H200 SXM GPU Server

The Supermicro SYS-821GE-TNHR2 is a purpose-built 8U GPU server designed to house up to eight NVIDIA H100 or H200 SXM form-factor GPUs, delivering exceptional parallel compute density for the most demanding enterprise AI, HPC, and large-scale inference workloads. Built around the NVIDIA Hopper architecture, the SXM-attached GPUs communicate via NVLink 4.0, enabling high-bandwidth, low-latency GPU-to-GPU interconnects that are essential for training large language models and multi-node deep learning pipelines. The platform supports dual 4th Gen Intel Xeon Scalable processors and is engineered to meet the thermal and power requirements of sustained, full-rack GPU utilization in production datacenter environments.

Each NVIDIA H100 SXM GPU integrated into this system delivers 80 GB of HBM2e memory with up to 3.35 TB/s memory bandwidth, while the H200 SXM variant upgrades that capacity to 141 GB of HBM3e memory at up to 4.8 TB/s bandwidth, making either configuration well-suited for memory-intensive generative AI and scientific simulation tasks. The server supports PCIe Gen 5.0 connectivity and includes high-speed network interface options including NVIDIA ConnectX-7 adapters to integrate with InfiniBand NDR or Ethernet-based GPU clusters. Redundant power supply units and hot-swap drive bays further align the platform with enterprise availability requirements.

Supermicro's SYS-821GE-TNHR2 is designed for deployment in hyperscale datacenters, national research laboratories, and enterprise AI infrastructure where consistent throughput and high GPU utilization rates are operational priorities. The system is available through Omnixon Global, serving enterprise buyers across the UAE, GCC, EMEA, and APAC regions, providing access to this high-density compute platform for organizations accelerating their AI and HPC infrastructure buildouts.

Ideal for

• Large language model (LLM) pre-training and fine-tuning requiring high GPU memory capacity and NVLink-scale multi-GPU bandwidth
• Generative AI inference serving for production deployments where throughput-per-server and memory footprint are critical
• High-performance computing simulations in computational fluid dynamics, molecular dynamics, and climate modeling
• Multi-modal AI research pipelines combining vision, language, and speech models within a single high-density server chassis
• Enterprise AI model development requiring rapid iteration cycles across frameworks such as PyTorch and TensorFlow with GPU-direct storage
• Sovereign AI and national research datacenter deployments demanding dense compute per rack unit with full hardware redundancy

Technical specifications

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