NVIDIA B100 SXM6 192GB HBM3e GPU Accelerator

The NVIDIA B100 SXM6 192GB HBM3e GPU Accelerator is built on NVIDIA's Blackwell architecture, representing a significant generational leap in compute density and memory bandwidth for large-scale AI and high-performance computing workloads. Featuring 192GB of HBM3e memory across the SXM6 form factor, the B100 delivers exceptional throughput for training and inference of frontier-scale AI models, scientific simulation, and data-intensive enterprise applications. The Blackwell GPU architecture introduces a second-generation Transformer Engine and support for FP4 and FP8 precisions alongside FP16, BF16, and FP64, enabling flexible numerical formats tuned to specific workload requirements.

Designed for deployment in high-density SXM6-based server platforms, the B100 integrates with NVLink and NVSwitch interconnect fabrics to enable multi-GPU scaling with high-bandwidth, low-latency GPU-to-GPU communication across a node. This makes it particularly well suited for distributed training of large language models and multi-modal foundation models where inter-GPU bandwidth is a critical bottleneck. The SXM6 interface provides substantially higher power delivery and signaling bandwidth compared to PCIe-attached solutions, unlocking the full compute potential of the Blackwell die.

Manufactured by Gigabyte under manufacturer part number 900-2G300-0000-000, this accelerator targets enterprise data centers, cloud infrastructure operators, and AI research institutions requiring the highest available GPU compute density per rack unit. Omnixon Global supplies this product to enterprise buyers across the UAE, GCC, EMEA, and APAC regions, supporting modern AI infrastructure build-outs at scale.

Ideal for

• Large language model (LLM) pre-training and fine-tuning at scale, leveraging FP8 Transformer Engine acceleration and high-bandwidth HBM3e memory
• Generative AI inference serving for enterprise deployments requiring sustained high-throughput token generation with low latency
• High-performance computing (HPC) workloads including molecular dynamics, climate modeling, and computational fluid dynamics benefiting from FP64 double-precision performance
• Multi-modal foundation model development combining vision, language, and structured data modalities within memory-intensive training pipelines
• Enterprise AI platform build-outs in sovereign cloud and on-premises data centers across regulated industries such as financial services, energy, and healthcare
• Scientific research and national laboratory workloads demanding the highest available GPU memory capacity and NVLink-based multi-GPU scaling

Technical specifications

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