NVIDIA H200 SXM5 141GB HBM3e GPU Accelerator

The NVIDIA H200 SXM5 141GB HBM3e GPU Accelerator, carrying manufacturer part number 900-21020-0000-000, is built on NVIDIA's Hopper GPU architecture and represents a significant advancement over its H100 predecessor. It features 141GB of HBM3e high-bandwidth memory — nearly double the capacity of the H100 SXM5 80GB — delivering a memory bandwidth of 4.8TB/s. The SXM5 form factor connects via NVLink 4.0, enabling multi-GPU configurations with up to 900GB/s of bidirectional NVLink bandwidth per GPU, making it purpose-built for scale-out AI infrastructure and large-scale high-performance computing clusters.

The H200 SXM5 integrates 80 billion transistors across 528 fourth-generation Tensor Cores, delivering up to 3,958 TFLOPS of FP8 Tensor Core performance and 1,979 TFLOPS at FP16 Tensor Core precision. It supports the Transformer Engine, which dynamically applies FP8 and FP16 mixed-precision computation to accelerate the training and inference of large language models and generative AI workloads. Confidential Computing support via NVIDIA's hardware TEE (Trusted Execution Environment) allows enterprises to run sensitive AI workloads in an isolated, hardware-enforced secure environment without sacrificing performance.

Designed for deployment in NVIDIA HGX H200 server platforms, this GPU is available through Omnixon Global for enterprise buyers across the UAE, GCC, EMEA, and APAC regions. The H200 SXM5 is ideal for AI model training at scale, scientific simulation, genomics research, and real-time inference serving where memory capacity and bandwidth are the primary bottlenecks. Its expanded HBM3e pool enables inference of frontier-scale large language models — such as those exceeding 70 billion parameters — that previously required multi-node configurations, consolidating workloads and improving total cluster efficiency.

Ideal for

• Large language model (LLM) training and fine-tuning for models with 70B+ parameters, leveraging 141GB HBM3e to keep model weights and optimizer states on a single GPU
• Generative AI inference serving for real-time or batch processing of foundation models, benefiting from 4.8TB/s memory bandwidth to reduce token latency
• High-performance computing (HPC) simulations in computational fluid dynamics, climate modeling, and molecular dynamics where FP64 throughput and memory capacity are critical
• Genomics and drug discovery workloads including protein structure prediction and large-scale bioinformatics pipelines requiring sustained high-memory-bandwidth compute
• Multi-GPU deep learning research using NVLink 4.0 interconnects to scale training across eight GPUs within a single HGX H200 node with full NVLink mesh topology
• Confidential AI workloads in regulated industries — such as finance and healthcare — using NVIDIA's hardware Trusted Execution Environment to protect model IP and sensitive data in use

Technical specifications

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