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NVIDIA’s CUDA-Q platform joins SUSE’s AI Factory

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October 21, 2026 by Ivy Delaney

SUSE and Fujitsu are delivering an enterprise-grade hybrid quantum computing platform as a unified stack, integrating SUSE AI Factory with NVIDIA’s CUDA-Q software on Fujitsu servers. This collaboration aims to move quantum intelligence from research labs into enterprise data centers by treating quantum circuits as manageable workload extensions. “As quantum computing shifts from theoretical physics into practical business assets, AI-driven orchestration is essential,” said Thomas Di Giacomo, chief technology and product officer at SUSE. Fujitsu reports this platform will allow customers to improve their existing hardware investments by connecting quantum simulation directly to production applications.

SUSE AI Factory Integrates NVIDIA CUDA-Q for Hybrid Quantum Workloads

SUSE AI Factory now manages quantum circuits as standard workloads, extending the reach of artificial intelligence into hybrid quantum computing environments. This integration, achieved through the incorporation of NVIDIA’s CUDA-Q platform on Fujitsu servers, allows standard IT teams to deploy and oversee complex quantum tasks using existing tools and workflows, the company says.

The platform’s embedded lifecycle management natively packages and deploys CUDA-Q, eliminating the need for manual patching and version control. Fujitsu is positioning this unified stack to allow organizations to connect quantum simulation directly to production applications, avoiding a complete overhaul of existing infrastructure.

Udo Wuertz, CTO FSAS Technologies EMEA at FSAS, stated, “As Fujitsu expands its technology portfolio with our new quantum computer and Digital Annealer, this partnership delivers the secure infrastructure foundation enterprises need.” The platform’s open source AI building-block kit delivers a modular abstraction layer, including Retrieval-Augmented Generation and LLM Serving, standardizing AI deployment on both Fujitsu and Supermicro hardware. A unified hybrid quantum runtime integrates the CUDA-Q platform into the compute broker, enabling automated submission and execution of quantum workloads.

This approach simplifies management through pre-validated reference architectures and a single support contract covering all hardware and software components. The solution prioritizes operational sovereignty, keeping proprietary data and algorithms strictly on-premises or within private infrastructure to maintain complete data residency and local security control. The joint hybrid quantum solution is scheduled for release in late 2026, representing one of the first instances of enterprise-grade hybrid quantum computing delivered as a production-ready stack.

As Fujitsu expands its technology portfolio with our new quantum computer and Digital Annealer, this partnership delivers the secure infrastructure foundation enterprises need.

Udo Wuertz, CTO Fsas Technologies EMEA at FSAS
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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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