Nvidia has formally launched the Vera Rubin platform, a combination CPU and GPU platform announced at the ISC High Performance 2026 conference in Hamburg. The platform combines Nvidia's Vera CPUs, Rubin GPUs, networking technologies, and software stack into what the company describes as a rack-scale supercomputer, targeting scientific workloads including climate modeling, computational fluid dynamics, quantum chemistry, energy exploration, and large data center operators.

At the heart of the platform is a tightly integrated architecture combining Nvidia Rubin GPUs and Vera CPUs linked through NVLink-C2C interconnects, ConnectX-9 SuperNICs, and BlueField-4 DPUs. The systems are built around direct liquid cooling and support up to 144 GPUs in a single rack. Nvidia claims a fully configured Vera Rubin system can deliver more than seven exaflops of AI performance for scientific workloads alongside five petaflops of native double-precision (FP64) computing performance, placing it well ahead of the top supercomputers in the TOP500 ranking.

The Vera Rubin architecture increases memory bandwidth by 2.8 times compared to Blackwell, the previous generation GPU. According to Dion Harris, senior director of HPC and AI factory solutions at Nvidia, the company is "projecting up to four times performance boosts for memory-bound fluid dynamic applications," adding that "with Rubin, we are ensuring that the fundamental mathematical workloads driving scientific discovery run faster, more efficiently, and with greater precision than ever before."

"Nvidia's roots are firmly planted in scientific computing, and native FP64 precision remains absolutely vital for accurate fluid dynamics, climate modeling, and geoscience," Harris said on a conference call. "We are committed to maintaining that support moving forward."

The new platform is designed to support both traditional HPC simulations and emerging AI-driven scientific applications, enabling researchers to train foundation models, deploy surrogate models, run simulations, and perform real-time data analysis on a single infrastructure. Harris noted that "AI is shifting from a tool that simply answers questions to an autonomous system that executes complex tasks," observing that "early data shows agentic AI increases simulation demand by up to ten times."

Several leading research institutions have announced plans to build next-generation systems based on the new architecture. The Leibniz Supercomputing Centre (LRZ) in Germany will deploy Vera Rubin in its upcoming Blue Lion supercomputer, a second-generation exascale-class HPE Cray system scheduled to enter service in 2027. Blue Lion is expected to deliver approximately 30 times the computing power of LRZ's current system, supporting research in astrophysics, environmental science, and life sciences.

In the United States, the National Energy Research Scientific Computing Center (NERSC) will use Vera Rubin technology in Doudna, the next flagship supercomputer for the Department of Energy at Lawrence Berkeley National Laboratory. This system is being built by Dell Technologies and will support large-scale HPC simulations, AI training, and data-intensive research.

Los Alamos National Laboratory has selected Vera Rubin technology for three new supercomputers: Mission, Vision, and Veritas. Mission will focus on national security workloads, while Vision will support open scientific research and AI-driven discovery. Veritas is specifically designed to enable agentic AI applications in scientific research, combining Rubin GPUs with standalone Vera CPU partitions.

Vera Rubin NVL4-based systems from Dell and Super Micro were also announced at the event.