Supermicro GPU Server SYS-820GH-TNGR (8x GPU 4U HGX H100 SXM5)

The Supermicro SYS-820GH-TNGR is a 4U HGX H100 SXM5 GPU server engineered to deliver maximum AI and HPC compute density in enterprise and hyperscale datacenter environments. Built around NVIDIA's HGX H100 SXM5 baseboard, it integrates eight NVIDIA H100 SXM5 80GB GPUs interconnected via NVLink 4.0 and NVSwitch technology, providing 900 GB/s GPU-to-GPU bandwidth and a combined 640GB of HBM3 GPU memory. The system supports dual 4th Gen Intel Xeon Scalable processors and is designed for tightly coupled, high-throughput AI training and large-scale scientific simulation workloads where GPU interconnect fabric performance is critical.

The SYS-820GH-TNGR features a high-bandwidth memory and I/O architecture supporting up to 8TB of DDR5 ECC RDIMM system memory across 32 DIMM slots, alongside PCIe 5.0 expansion for accelerated host-to-GPU data paths. The server incorporates Supermicro's advanced hybrid cooling infrastructure, supporting both air-cooled and direct liquid cooling configurations to manage the substantial thermal output of eight H100 SXM5 accelerators. Redundant 3000W Titanium-level power supplies ensure continuous operation at enterprise uptime standards, with full IPMI 2.0 and Redfish-compliant out-of-band management via Supermicro's IPMI BMC.

Targeted at AI research institutions, cloud service providers, financial modeling organizations, and enterprise AI infrastructure teams, the SYS-820GH-TNGR supports frameworks including PyTorch, TensorFlow, JAX, and NVIDIA's NeMo and TensorRT ecosystems. Its dense 4U form factor optimizes rack utilization for GPU compute clusters, and it is compatible with NVIDIA Base Command Manager and standard HPC cluster management stacks. Omnixon Global supplies this platform to enterprise buyers across the UAE, GCC, EMEA, and APAC regions.

Ideal for

• Large language model (LLM) pre-training and fine-tuning at scale using transformer architectures requiring high GPU memory capacity and NVLink interconnect bandwidth
• Deep learning inference serving for real-time AI applications demanding maximum throughput across concurrent model instances
• High-performance scientific computing and computational fluid dynamics simulations leveraging tightly coupled multi-GPU parallelism
• Generative AI model development including diffusion models, multimodal AI, and reinforcement learning from human feedback (RLHF) pipelines
• Financial risk modeling and quantitative analysis workloads requiring accelerated Monte Carlo simulations and large matrix operations
• Enterprise AI infrastructure deployment within GPU compute clusters for national laboratories, research universities, and cloud-native AI platforms

Technical specifications

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