NVIDIA and Google Cloud is expanding its collaboration to advance agentic and physical AI infrastructure products, specialised Tensor Processing Units (TPU) chips and extending its cloud and AI infra partnerships to prominent companies, according to a blog post from Nvidia.
The most prominent of these partnerships is Google's multi-billion dollar deal with 'Thinking Machine Labs' - an AI startup which will use Google's cloud AI infrastructure, that uses Nvidia's GB300 chips. The deal is in single digits billions according to a source familiar with the matter, as cited by Tech Crunch.
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The startup will be using the A4 Max VM cloud-based supercomputers powered by Nvidia's aforementioned GB300 chips.
"Thinking Machines Lab is scaling its Tinker application programming interface (API) on A4X Max VMs with GB300 NVL72 systems to accelerate training," Nvidia's blog post said.
Google announced its A5X cloud supercomputer which will be powered by NVIDIA Vera Rubin NVL72 rack-scale systems (consisting of AI chips clubbed together on racks).
These deliver up to 10x lower inference cost per token which means that it will cost ten times less in money and electricity. It also has 10x higher token throughput per megawatt generation, which means it has 10 times more output.
"By combining Google Cloud's scalable infrastructure and managed AI services with NVIDIA's industry‑leading platforms, systems and software, we're giving customers flexibility to train, tune and serve everything from frontier and open models to agentic and physical AI workloads — while optimizing for performance, cost and sustainability,” Mark Lohmeyer, vice president and general manager of AI and computing infrastructure at Google Cloud said, as cited by the blog post.
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The company also unveiled its TPU 8t and TPU 8i, tensor processing chips to power its custom built supercomputers.
Google is also partnering with firms like McKinsey & Company, Boston Consulting Group (BCG), Deloitte, Merck and Accenture over various projects to further the use of Agentic AI.
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