Ian Buck

NVIDIA has introduced Vera, a CPU designed specifically for agentic AI workloads that prioritizes single-threaded performance at scale rather than core count. Unlike traditional data center CPUs optimized for cost per core, Vera maintains high per-core performance across all cores simultaneously, addressing a critical bottleneck in AI agent systems where each sequential step depends on the previous result. The architecture reflects a fundamental shift in CPU design philosophy driven by the demands of continuous, parallel agent loops rather than intermittent user-driven workloads.

NVIDIA and Google Cloud announced expanded infrastructure for agentic and physical AI workloads at Google Cloud Next, introducing A5X bare-metal instances powered by NVIDIA Vera Rubin GPUs that deliver 10x lower inference cost per token and 10x higher token throughput per megawatt compared to prior generations. The partnership also previewed Google Gemini on Google Distributed Cloud running on NVIDIA Blackwell GPUs, added confidential computing capabilities for sensitive workloads, and integrated NVIDIA Nemotron models with the Gemini Enterprise Agent Platform. The infrastructure scales from single GPUs to 960,000 NVIDIA Rubin GPUs across multisite clusters, enabling enterprises to run frontier models, agentic systems, and physical AI applications in production.