Inference performance is critical, as it directly influences the economics of an AI factory. The higher the throughput of AI factory infrastructure, the more tokens it can produce at a high speed - increasing revenue, driving down total cost of ownership (TCO) and enhancing the system's overall productivity. Less than half a year since its debut at NVIDIA GTC, the NVIDIA GB300 NVL72 rack-scale system - powered by the NVIDIA Blackwell Ultra architecture - set records on the new reasoning inference benchmark in MLPerf Inference v5.1, delivering up to 1.4x more DeepSeek-R1 inference throughput compared with NVIDIA Blackwell-based GB200 NVL72 systems.

Blackwell Ultra builds on the success of the Blackwell architecture, with the Blackwell Ultra architecture featuring 1.5x more NVFP4 AI compute and 2x more attention-layer acceleration than Blackwell, as well as up to 288 GB of HBM3e memory per GPU. The NVIDIA platform also set performance records on all new data center benchmarks added to the MLPerf Inference v5.1 suite - including DeepSeek-R1, Llama 3.1 405B Interactive, Llama 3.1 8B and Whisper - while continuing to hold per-GPU records on every MLPerf data center benchmark.