Supermicro SuperServer SYS-821GH-TNR2 8U HGX B200

The Supermicro SuperServer SYS-821GH-TNR2 is an 8U rackmount server engineered around the NVIDIA HGX B200 platform, integrating eight NVIDIA Blackwell B200 SXM6 GPUs interconnected via NVLink and NVSwitch fabric for unified high-bandwidth memory pooling and peer-to-peer GPU communication at scale. The system is built on the Intel Xeon Scalable (Emerald Rapids) processor platform, supporting dual CPUs and delivering the extreme compute density and memory bandwidth demanded by frontier AI training, large-scale inference, and high-performance data analytics workloads.

Each NVIDIA B200 GPU in the HGX baseboard delivers 192 GB of HBM3e memory per GPU, yielding up to 1.5 TB of aggregate GPU memory across the eight-GPU tray. The fifth-generation NVLink fabric provides up to 1.8 TB/s bidirectional GPU-to-GPU bandwidth, enabling tight coupling for massive model parallelism without CPU bottlenecks. The SYS-821GH-TNR2 is designed to support high-speed networking via ConnectX-7 or BlueField-3 class NICs and CX-series InfiniBand or 400GbE interconnects, fitting naturally into GPU cluster fabrics for distributed deep learning and scientific simulation.

Supermicro's 8U chassis for this platform is engineered for dense datacenter deployment with high-efficiency redundant power supplies, hot-swap storage bays, and an optimized airflow design rated for the sustained thermal envelope of eight B200 GPUs under continuous AI workloads. The server targets hyperscale AI infrastructure operators, sovereign AI programs, financial modeling at scale, and enterprise organizations building on-premises large language model training or inference stacks requiring the highest available single-node GPU memory capacity.

Ideal for

• Large language model (LLM) pre-training and fine-tuning requiring multi-hundred-billion parameter model capacity within a single node
• Enterprise-scale generative AI inference serving with high-throughput, low-latency SLA requirements across multiple concurrent model deployments
• High-performance computing (HPC) and scientific simulation workloads such as molecular dynamics, climate modeling, and computational fluid dynamics
• Multi-modal AI model development combining vision, language, and structured data requiring extreme unified GPU memory capacity
• Sovereign AI and national AI research programs deploying on-premises GPU clusters with InfiniBand or high-speed Ethernet scale-out fabrics
• Financial services quantitative modeling, risk simulation, and real-time analytics pipelines leveraging GPU-accelerated compute at datacenter scale

Technical specifications

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