Supermicro 900-5X172-2540-110 NVIDIA HGX H200 SXM5 Tray EMEA Variant

The Supermicro 900-5X172-2540-110 is an NVIDIA HGX H200 SXM5 tray assembly configured for the EMEA market, delivering the full capability of NVIDIA's Hopper-generation H200 GPU architecture in a high-density, multi-GPU tray form factor. Built around the NVIDIA H200 SXM5 GPU, this tray integrates HBM3e memory with a total capacity of 141 GB per GPU across the HGX baseboard, offering substantially higher memory bandwidth than its H100 predecessor — reaching up to 4.8 TB/s per GPU. The SXM5 interface ensures maximum interconnect performance via NVLink 4.0, enabling tight GPU-to-GPU communication across the full eight-GPU HGX configuration at aggregate NVLink bandwidths suited to the most demanding distributed AI training runs.

The HGX H200 tray is designed for direct integration into compatible Supermicro server platforms, including the Supermicro MGX and HGX server lines, making it the foundational compute substrate for large-scale AI infrastructure deployments. The EMEA variant designation (part number suffix -110) reflects regional compliance and configuration targeting European, Middle Eastern, and African deployment environments. The tray assembly includes the NVIDIA HGX H200 baseboard populated with eight H200 SXM5 GPUs, NVLink interconnects, and the associated power and thermal interfaces required for rack-scale deployment.

Enterprise and hyperscale operators adopting the 900-5X172-2540-110 gain access to a compute node capable of running frontier large language model (LLM) training and inference, multimodal AI, and high-performance computing (HPC) workloads at scale. The H200's expanded HBM3e memory pool addresses the memory-capacity bottlenecks that constrain LLM deployment on earlier GPU generations, enabling larger model parameter counts to reside entirely in GPU memory, reducing offload overhead and accelerating throughput for both batch and real-time inference scenarios.

Ideal for

• Large-scale generative AI and large language model (LLM) training across hundreds of billions of parameters, leveraging the full 8x H200 SXM5 NVLink fabric for distributed tensor and pipeline parallelism
• High-throughput LLM inference serving for enterprise AI platforms, where the 141 GB HBM3e per GPU eliminates the need for model sharding across nodes in many frontier model deployments
• Scientific HPC simulation workloads including molecular dynamics, climate modelling, and computational fluid dynamics that require both high memory bandwidth and large addressable GPU memory
• Multimodal AI development encompassing vision-language models, video understanding, and diffusion-based generative models that impose heavy combined compute and memory demands
• AI-driven drug discovery and genomics pipelines requiring sustained double-precision floating-point throughput alongside large in-memory datasets
• Sovereign AI infrastructure buildouts in EMEA-region datacenter facilities requiring regionally compliant, rack-integrated GPU tray assemblies at hyperscale density

Technical specifications

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