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NVIDIA CEO Jensen Huang and Google Cloud CEO Thomas Kurian shake hands, symbolizing their partnership making Vera Rubin infra

Editorial illustration for Google Cloud, NVIDIA Make Vera Rubin Infrastructure Generally Available

Google Cloud, NVIDIA Launch Vera Rubin AI Infrastructure

• 4 min read

Google Cloud and NVIDIA will make the new A5X instance generally available next month, with plans to expand into Europe shortly after. The instance pairs NVIDIA's Vera Rubin NVL72 system with ConnectX-9 SuperNICs, Google Cloud's Virgo Network and its fourth-generation liquid-cooling setup, built specifically for agentic inference and reinforcement learning at scale. Google Cloud says it intends to grow its Vera Rubin footprint to as many as 960,000 Rubin GPUs spread across multiple sites, folding the new hardware into its AI Hypercomputer as a single integrated system covering compute, networking and storage.

The first company given access to A5X is Ineffable Intelligence, a London startup founded by David Silver, the DeepMind researcher behind AlphaGo. Ineffable is using the infrastructure to train what it calls "superlearner" systems, models designed to improve continuously by generating experience, evaluating results and updating themselves in a tight loop rather than training on fixed datasets. That kind of learning puts unusual demands on infrastructure, since every step in the cycle has to run at scale without creating bottlenecks between generating experience and training on it. Silver described what that requires in his own words below.

Learning through interaction requires a continuous cycle of generating experience, evaluating outcomes and updating models, requiring infrastructure that can support the entire process 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 at scale.

Why this matters

For teams building agentic systems, the bottleneck has never just been raw compute, it's the round trip between an agent acting, learning from that action, and updating fast enough to matter. A5X instances landing on Google Cloud next month, with Europe to follow, gives developers and researchers a concrete option for that loop: Vera Rubin NVL72 paired with ConnectX-9 SuperNICs and Google's Virgo network, all wrapped in fourth-gen liquid cooling. That's a specific, provisioned stack, not a roadmap slide.

Founders running reinforcement learning at scale should pay attention to the bandwidth claims between Vera CPUs and Rubin GPUs specifically, since that's the part that determines whether "the agent can quickly shape its next experience" is marketing language or an actual latency win. We'd want to see independent benchmarks once instances ship before treating this as settled. Still, a major cloud provider committing to general availability, rather than a limited preview, signals NVIDIA and Google think agentic inference workloads are common enough now to justify dedicated infrastructure.

Worth watching how pricing lands once it's live.

Common Questions Answered

What is the A5X instance and when will it be available on Google Cloud?

The A5X instance is a new infrastructure offering that pairs NVIDIA's Vera Rubin NVL72 system with ConnectX-9 SuperNICs and Google Cloud's Virgo Network, featuring fourth-generation liquid cooling. Google Cloud will make the A5X instance generally available next month, with plans to expand into Europe shortly after.

How does the Vera Rubin infrastructure support agentic inference and reinforcement learning?

The Vera Rubin infrastructure is specifically built to support the continuous cycle of generating experience, evaluating outcomes, and updating models required for agentic inference and reinforcement learning at scale. By integrating compute, networking, and storage as a unified system within Google Cloud's AI Hypercomputer, it enables experience-driven learning with minimal latency between an agent acting, learning from that action, and updating its models.

What is Google Cloud's expansion plan for Vera Rubin GPU capacity?

Google Cloud intends to grow its Vera Rubin footprint to as many as 960,000 Rubin GPUs spread across multiple sites globally. This massive expansion demonstrates the company's commitment to scaling infrastructure specifically designed for advanced AI workloads.

Why is the round trip latency between agent action and model update important for agentic systems?

For teams building agentic systems, the bottleneck has never been just raw compute power, but rather the round trip between an agent acting, learning from that action, and updating fast enough to matter. The A5X instance with its integrated compute, networking, and cooling addresses this specific challenge by enabling rapid feedback loops essential for effective agent learning.

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