NVIDIA B200 PCIe 192GB HBM3e

The NVIDIA B200 PCIe 192GB HBM3e is a flagship data center GPU built on NVIDIA's Blackwell architecture, delivering a generational leap in compute density and memory bandwidth for the most demanding AI training, inference, and high-performance computing workloads. Featuring 192GB of HBM3e memory across a 8192-bit memory bus, the B200 PCIe provides exceptional memory capacity for large language model (LLM) training and inference, scientific simulation, and deep learning tasks that require holding massive parameter counts and datasets entirely on-device.

The Blackwell architecture introduces the second-generation Transformer Engine with support for FP4 and FP8 precision, dramatically accelerating transformer-based AI workloads compared to previous generations. The B200 PCIe form factor enables deployment in standard PCIe Gen5 server platforms without requiring NVLink-based SXM infrastructure, broadening compatibility across a wide range of enterprise server ecosystems while still delivering industry-leading throughput for inference and training tasks.

With a manufacturer part number of 900-21001-0050-000, the NVIDIA B200 PCIe 192GB HBM3e is purpose-built for enterprise data centers, AI supercomputing clusters, and cloud infrastructure operators in regions including the UAE, GCC, EMEA, and APAC. Omnixon Global supplies this GPU to enterprise and institutional buyers requiring verified, NVIDIA hardware at scale.

Ideal for

• Large language model (LLM) training and fine-tuning requiring high on-device memory capacity for multi-billion to trillion-parameter models
• Generative AI inference serving at scale, including real-time text, image, and multimodal model deployment in enterprise environments
• High-performance scientific computing and simulation workloads such as molecular dynamics, climate modeling, and computational fluid dynamics
• AI-driven drug discovery and genomics pipelines requiring sustained FP64 and mixed-precision compute throughput
• Enterprise data analytics and machine learning pipelines where GPU-accelerated data processing must operate on very large in-memory datasets
• National AI infrastructure and sovereign cloud deployments in GCC and EMEA requiring dense, high-capacity GPU compute nodes

Technical specifications

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