Build on infrastructure designed for frontier AI

The NVIDIA B300 addresses the critical industry shift from compute-bound to memory-bound AI workloads, where performance is defined by data movement speed rather than raw FLOPS. Featuring 288 GB of HBM3e memory per GPU and a massive 8,192-bit bus, the architecture ensures large model parameters and activations remain in local memory, minimizing latency from external storage. This high-bandwidth configuration supports data-intensive tasks like longer context windows and Mixture-of-Experts (MoE) routing without stalling GPU cores. Furthermore, the B300’s on-package design places memory stacks on a shared substrate with the GPU, which reduces signal distance to lower power consumption and improve thermal efficiency. Ultimately, this architecture allows enterprises to scale model sizes efficiently, reducing total compute costs by decreasing idle time during training.

The NVIDIA DGX B300 serves as a high-performance foundation for AI factories, exemplified by deployments capable of 9 quintillion calculations per second. It integrates eight Blackwell Ultra GPUs featuring a dual-die design that appears to software as a single logical unit. To accelerate reasoning, the architecture uses NVFP4 precision, reducing memory usage by 1.8×, and doubles SFU throughput for 2× faster attention performance. The system features 2.3 TB of HBM3e memory with 8 TB/s bandwidth per GPU to keep massive models resident. Scaling is enabled by NVLink 5 (1.8 TB/s) and 800 Gb/s networking within a 10 RU chassis. Effective integration requires meticulous planning of power and cooling, supported by deployment guidance from the Uvation Marketplace.

The NVIDIA B300, or Blackwell Ultra, is engineered for massive AI workloads, featuring 288 GB of HBM3e memory and a 50% increase in compute performance over its predecessor. Its architecture addresses data bottlenecks through NVLink 5, which provides 1.8 TB/s of internal bandwidth per GPU.  For multi-node scaling, B300 systems utilise 800 Gb/s InfiniBand or Ethernet connectivity via ConnectX-8 adapters. These capabilities are delivered through the DGX B300 turnkey appliance and the modular HGX B300 platform. Together, they facilitate large-scale model training and high-speed inference by ensuring compute power is not idled by slow data movement.  Think of the B300 as a high-performance racing engine; without a wide, high-speed highway (the network), it cannot reach its top speeds when working as part of a fleet.