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QBraid OS Available to Early-Access Partners Including Diraq,, MemQ

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October 21, 2026 by Ivy Delaney

qBraid has launched qBraid OS, software designed to operate quantum computing services and connect quantum processors with NVIDIA accelerated computing. The system currently supports 18 quantum hardware providers and manages access, scheduling and billing for quantum processors. qBraid OS uses the NVIDIA CUDA-Q platform for quantum error-correction decoding and classical processing alongside quantum jobs; according to Kanav Setia, CEO of qBraid, “Companies building quantum computers should be able to spend their time on the hardware.” The software is already serving thousands of quantum developers through qBraid’s existing agentic platform.

qBraid OS Integrates 18 Providers with NVIDIA CUDA-Q

qBraid OS is designed to combine scheduling of quantum processors with NVIDIA accelerated computing, including systems connected through NVIDIA NVQLink, a high-bandwidth interconnect. The software’s architecture is built upon infrastructure already serving thousands of quantum developers, indicating a pre-existing user base before its formal release. This established network is now accessible through qBraid OS, offering a platform for both commercial services and internal use.

The system’s capabilities extend to user management, reservations and usage metering, all designed to be operated with AI agents under the supervision of system operators. Access for developers is facilitated through the qBraid SDK, qBraid’s AI agents and NVIDIA CUDA-Q, ensuring code compatibility across different hardware.

Defined integration points for compilers, optimizers and resource-estimation tools further simplify the development process, requiring each integration only once, the company says. “qBraid OS builds on NVIDIA CUDA-Q and NVQLink to help hardware providers offer their systems as services, giving developers and AI agents a consistent way to access quantum hardware and run unified workflows,” said Sam Stanwyck, Director of Quantum Product at NVIDIA. qBraid OS is currently in early access with partners including Diraq, Quobly, IBM, MemQ and Quantum Machines, and can be deployed on premises or in the cloud.

Quantum processors and GPU supercomputers will become as easy to use together as CPUs and GPUs are today.

Sam Stanwyck, Director of Quantum Product at NVIDIA
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CUDA-Q Diraq error correction memQ NVIDIA NVIDIA CUDA-Q Quantum Computing
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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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