NVIDIA B300 GPU (Blackwell Ultra) 288GB HBM3e

The NVIDIA B300 GPU, based on the Blackwell Ultra architecture, represents NVIDIA's most advanced data center accelerator at the time of its announcement. Built on the second-generation Blackwell architecture with enhanced compute and memory capabilities, the B300 features 288GB of HBM3e memory — a substantial increase over its predecessor — delivering the high-bandwidth, large-memory capacity demanded by frontier AI training, large-scale inference, and high-performance computing workloads. The GPU is engineered to handle trillion-parameter-class models within a single accelerator, reducing the complexity and latency overhead associated with multi-GPU model parallelism.

The B300 integrates NVIDIA's fifth-generation NVLink interconnect fabric, enabling high-speed GPU-to-GPU communication across NVLink-connected systems with aggregate bandwidth well beyond traditional PCIe-attached configurations. This makes the B300 particularly well-suited for tightly coupled AI supercomputing clusters and NVLink-domain server configurations such as the GB300 NVL72 rack-scale system. The accelerator also incorporates dedicated transformer engine hardware and FP4/FP8 precision support, enabling inference throughput optimizations for generative AI models including large language models and multimodal architectures.

Designed for enterprise data center deployment, the B300 is available in SXM form factor configurations and is supported within NVIDIA's broader ecosystem including CUDA, cuDNN, TensorRT, and the NVIDIA AI Enterprise software platform. Organizations in demanding sectors — including cloud service providers, financial services, healthcare AI, and scientific research institutions — can leverage the B300's combination of memory capacity, memory bandwidth, and compute density to accelerate the most data-intensive workloads while maintaining operational efficiency within standard data center power and thermal envelopes.

Ideal for

• Training and fine-tuning frontier large language models (LLMs) with hundreds of billions to trillions of parameters within reduced GPU counts due to the 288GB HBM3e memory capacity
• High-throughput generative AI inference for enterprise-scale deployments of multimodal and conversational AI models requiring low latency and high concurrency
• Scientific simulation and high-performance computing (HPC) workloads in genomics, climate modeling, and computational fluid dynamics that require large in-memory datasets
• Retrieval-augmented generation (RAG) and vector database acceleration for enterprise AI applications requiring real-time context retrieval at scale
• AI-driven drug discovery and molecular dynamics simulations benefiting from large memory footprints and high FP64/FP32 double-precision throughput
• Sovereign AI and national AI infrastructure deployments where data residency and on-premises GPU compute density are critical enterprise requirements

Technical specifications

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