Artificial Intelligence, High Performance Computing

NVIDIA GB300 Powers Anthropic’s Claude in Microsoft Foundry

Avatar of Ivy Delaney
June 30, 2026 by Ivy Delaney

Anthropic’s Claude models are now running on NVIDIA GB300 Blackwell Ultra GPUs within Microsoft Foundry on Azure, providing infrastructure for enterprises seeking to build advanced AI agents. The integration of NVIDIA Quantum-X800 InfiniBand networking alongside the NVIDIA GB300 NVL72 systems is designed to enable more powerful and scalable agentic systems capable of performing complex tasks across business domains. NVIDIA is extending developer capabilities by integrating its tools into the Anthropic stack, allowing enterprises to equip Claude agents with domain-specific abilities. NVIDIA states this allows businesses to “embed AI agents deeply into their business and use them as the operating system for the organization” through NVIDIA verified agent skills, enabled by access to NVIDIA accelerated computing. This launch builds on a strategic partnership between Microsoft, NVIDIA, and Anthropic announced last November to expand enterprise access to Claude.

This development addresses the increasing demand for computational power necessary to deploy specialized agents capable of accelerating critical business functions and reducing total cost of ownership through improved inference performance and efficiency. The NVIDIA Secure Agent Workspace Reference Design provides a blueprint for running these autonomous agents within a controlled environment, governing identity, network access, and runtime policies at the infrastructure level.

With Claude in Foundry running on NVIDIA GB300 NVL72 systems with NVIDIA Quantum-X800 InfiniBand networking, enterprises can now build and run more powerful agentic systems, including autonomous and specialized sub-agents that can work across business domains to perform advanced tasks.

The convergence of large language models and specialized AI agents is rapidly reshaping enterprise computing, with organizations now seeking to imbue these agents with targeted expertise.

Organizations are increasingly seeking to equip these agents with targeted expertise, and this infrastructure supports that goal.

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AI agents Anthropic Microsoft Azure NVIDIA NVIDIA GB300 GPUs
Avatar of Ivy Delaney

Ivy Delaney

Ivy Delaney has been working with neural networks and machine learning since the mid-nineties, back when a couple of hidden layers and a long afternoon of training counted as ambitious. She has watched the field go from academic curiosity to the thing quietly running underneath everything, and she brings that long view to quantum computing. For Quantum Zeitgeist she covers the ground where the two fields meet. That means quantum machine learning and the variational algorithms it leans on, and it also means the less glamorous but more interesting story of classical machine learning already doing real work inside quantum machines, decoding error-correcting codes, calibrating noisy hardware and learning the error models that simulators depend on. She writes about the hardware those algorithms have to run on too, and about the post-quantum cryptography scramble that the same hardware has set off. Her stories typically start with the paper, whether that is peer-reviewed work, conference proceedings or an arXiv preprint, with the source linked so you can hold a claim up against the research it came from. She is unimpressed by benchmarks that will not say what they beat, and by demonstrations that only work in the press release.

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