Google Cloud A5X on NVIDIA Vera Rubin Set for November Availability

NVIDIA (NVDA ) announced on October 21, 2026, that general availability of Google Cloud A5X instances powered by NVIDIA Vera Rubin infrastructure is coming in November 2026, with planned expansion of availability to Europe. The platform is built for training, inference and large-scale reinforcement learning for cloud customers, and Google Cloud plans to scale its Vera Rubin-based infrastructure to as many as 960,000 Rubin GPUs across multiple sites, according to the NVIDIA announcement.

A5X instances bring together NVIDIA Vera Rubin NVL72, NVIDIA ConnectX-9 SuperNICs, the Google Cloud Virgo Network and Google Cloud’s fourth-generation advanced liquid-cooling technology for demanding agentic inference and reinforcement learning workloads at scale. A5X brings Vera Rubin into Google Cloud’s AI Hypercomputer as an integrated system combining compute, networking and storage to support experience-driven learning, which requires a continuous cycle of generating experience, evaluating outcomes and updating models.

Road to General Availability

Google Cloud said on March 16, 2026, that it planned to be among the first cloud providers to offer NVIDIA Vera Rubin NVL72 rack-scale systems in the second half of 2026, integrating them into its AI Hypercomputer architecture.

Google then announced A5X at Google Cloud Next in April 2026. NVIDIA states that Vera Rubin NVL72 rack-scale systems, through codesign across chips, systems and software, deliver up to 10x lower inference cost per token and 10x higher token throughput per megawatt than the prior generation. In its April 2026 post, NVIDIA said A5X would use ConnectX-9 SuperNICs combined with next-generation Google Virgo networking, scaling to up to 80,000 Rubin GPUs within a single-site cluster and up to 960,000 Rubin GPUs in a multisite cluster.

At the April event, Mark Lohmeyer, vice president and general manager of AI and computing infrastructure at Google Cloud, said combining Google Cloud’s scalable infrastructure and managed AI services with NVIDIA’s platforms, systems and software gives customers flexibility to train, tune and serve everything from frontier and open models to agentic and physical AI workloads.

Google Cloud’s broader NVIDIA portfolio ranges from A4 VMs with NVIDIA HGX B200 systems to rack-scale A4X VMs with NVIDIA GB200 NVL72 and A4X Max systems with NVIDIA GB300 NVL72, down to fractional G4 VMs with NVIDIA RTX PRO 6000 Blackwell Server Edition GPUs. NVIDIA’s April post noted that OpenAI is running large-scale inference on A4X Max and A4X systems on Google Cloud for some of its most demanding inference workloads, including for ChatGPT.

First Customers and Demonstrations

Ineffable Intelligence, a London-based technology company founded by AlphaGo creator David Silver, was the first customer to access A5X. The company is using the platform to advance large-scale reinforcement learning and to shape “superlearner” systems that learn continuously from experience.

“We’re building superlearners that continually improve through their own experience,” said David Silver, founder and CEO of Ineffable Intelligence. “That demands both substantial compute and a tight connection between generating experience and training on it, so each improvement in the agent can quickly shape its next experience. Vera Rubin’s combination of compute performance and high-bandwidth connectivity, between the Vera CPU and Rubin GPUs and between the Rubin GPUs within the rack, allow us to push the scale and ambition of our reinforcement learning research further.”

On June 16, 2026, Google Cloud and Ineffable Intelligence announced a strategic partnership under which Ineffable selected Google Cloud as its preferred cloud partner. The agreement followed Ineffable’s $1.1 billion seed round, which the companies described as the largest of its kind in European history. The partnership provides for Ineffable to deploy one of the largest clusters of A5X powered by NVIDIA Vera Rubin NVL72 on Google Cloud. Thomas Kurian, CEO of Google Cloud, said at the time that Ineffable is leveraging the full-stack AI Hypercomputer, from Jupiter networking to optimized storage.

WPP, a London-based marketing and communications company, has also demonstrated its creative agent reference architecture on A5X instances using NVIDIA Nemotron models and NVIDIA OpenShell. The agents turn conversational requests into multistep creative workflows, such as video generation, upscaling and restyling, with human approval before execution, while OpenShell provides governed sandboxes for agent execution to help control access to sensitive brand assets and creative tools. In WPP’s initial tests, workloads that typically required a multi-node cluster ran on a single A5X instance, NVIDIA reported.

NVIDIA separately launched the OpenShell Reference Architecture on October 21, 2026. The architecture combines NVIDIA Vera Rubin infrastructure for model inference, NVIDIA Vera CPUs for operating agent harnesses, and NVIDIA BlueField-4 DPUs running NVIDIA Sentry for continuous monitoring and in-silicon policy enforcement. NVIDIA states that Vera Rubin NVL72 systems deliver 30x higher throughput per megawatt for agentic workloads. The OpenShell Reference Architecture is available now.

On the security side, Google Cloud will be among the first cloud providers to offer NVIDIA Confidential Computing at rack scale on bare metal instances such as A4X Max instances powered by NVIDIA GB300 NVL72. Google Cloud is also making Confidential Computing generally available on G4 VMs powered by NVIDIA RTX PRO 6000 Blackwell Server Edition GPUs, and NVIDIA names Vertebrae, Polaris Cloud and Confidential Core AI (CHAI ) as customers using Confidential G4 for conversational privacy, verifiable agent execution and policy-governed enterprise intelligence.

To support energy-efficient deployment at scale, Google Cloud and NVIDIA are exploring NVIDIA DSX MaxLPS capabilities for Vera Rubin-based infrastructure to help optimize performance per watt and expand capacity within available data-center power budgets.