Gigabyte NVIDIA B200 SXM6 192GB HBM3e GPU Compute Module

The Gigabyte NVIDIA B200 SXM6 192GB HBM3e GPU Compute Module (GV-NB200SXM6-192G) is built on NVIDIA's Blackwell architecture, representing a significant generational leap in GPU compute density for enterprise data centers. The B200 SXM6 form factor integrates 192GB of HBM3e memory across a unified high-bandwidth memory subsystem, delivering exceptional memory capacity and bandwidth suited to the most demanding large-scale AI training and inference workloads. The Blackwell architecture introduces a second-generation Transformer Engine and fifth-generation NVLink interconnect, enabling multi-GPU configurations to operate at scale with low-latency, high-throughput communication between accelerators.

Designed for deployment in NVLink-connected GPU computing systems such as the NVIDIA GB200 NVL-class platforms, the B200 SXM6 module supports FP8, FP16, BF16, TF32, and FP64 precision formats, making it versatile across mixed-precision AI training, high-fidelity scientific simulation, and petascale inference serving. The SXM6 connector interface provides high-bandwidth power and signal delivery, enabling the GPU to sustain peak compute throughput within thermally managed server node environments. Gigabyte's implementation of this module targets hyperscale operators, national laboratories, and enterprise AI infrastructure teams requiring maximum per-node compute performance.

The GV-NB200SXM6-192G is purpose-built for integration into high-density GPU compute nodes within modern AI factories and HPC clusters. Its 192GB HBM3e memory capacity allows very large language models, multimodal foundation models, and complex simulation workloads to reside entirely on-device, minimizing data movement overhead. With NVLink 5 support enabling multi-GPU memory pooling across connected B200 modules, enterprise teams can address model parallelism at scale, supporting next-generation AI research and production inference infrastructure across data center environments in the UAE, GCC, EMEA, and APAC regions.

Ideal for

• Large-scale generative AI and large language model (LLM) training requiring high memory capacity and ultra-high memory bandwidth per GPU node
• High-throughput enterprise AI inference serving for transformer-based foundation models, including multimodal and mixture-of-experts architectures
• High-performance computing (HPC) and scientific simulation workloads demanding FP64 double-precision compute alongside AI acceleration in the same hardware platform
• Multi-GPU distributed training deployments leveraging NVLink 5 for high-bandwidth peer-to-peer GPU communication and memory pooling across accelerator nodes
• Enterprise data center AI factory builds requiring maximum compute density per rack unit within thermally managed SXM6-compatible server node enclosures
• Government, research institution, and national laboratory GPU cluster deployments targeting petascale AI and simulation workloads with long model residency requirements

Technical specifications

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