Nvidia's Blackwell Ultra GPU Sets New Efficiency Records
Nvidia's new Blackwell Ultra GB300 GPU is establishing new performance benchmarks in long-context LLM inference, significantly outperforming its GB200 predecessor in speed and efficiency. The hardware is seen as enabling an "efficiency era" of AI, making contexts of over 100,000 tokens more viable and cost-effective for production systems. Australian startup Sharon AI is reportedly building its sovereign AI platform around the new Blackwell architecture, highlighting its strategic importance for new ventures.
- The Blackwell architecture is built on a custom TSMC 4NP process, featuring 208 billion transistors and a dual-die chip connected by a 10 terabytes per second (TB/s) interconnect. The Blackwell Ultra version enhances this with 1.5 times more AI compute FLOPS and double the acceleration for attention layers compared to the standard Blackwell GPU. - In MLPerf benchmarks for inference, the GB300 NVL72 rack-scale system demonstrated a 45% performance increase over the preceding GB200 platform when running the DeepSeek R1 model. It showed up to five times the performance of the older Hopper GPU architecture in some tests. - Compared to the Hopper generation, the GB300 NVL72 delivers up
