Nvidia launches open models for AI-based quantum computing

Nvidia launched new open models designed for AI-based quantum computing.

The Nvidia Ising open model family is designed for AI-based quantum processor calibration and quantum error correction decoding that's 2.5 times faster and 3 times more accurate than traditional approaches.

Nvidia's move to meld AI, high-performance computing and quantum computing aligns with its approach to open AI models overall. Nvidia is priming the open-source model pump to create developer momentum.

According to Nvidia, the company has lined up a series of quantum computing companies, research labs and academic institutions to support Ising. Academia Sinica, Fermi National Accelerator Laboratory, Harvard John A. Paulson School of Engineering and Applied Sciences, Infleqtion, IQM Quantum Computers, Lawrence Berkeley National Laboratory’s Advanced Quantum Testbed and the UK National Physical Laboratory (NPL) are all supporting the new Nvidia Ising models.

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Of the quantum computing pure play companies, Infleqtion, a neutral atom player, is the most notable. The company recently launched an IPO, installed a 100-qubit quantum computer in the UK and said 2026 revenue will be about $40 million.

Constellation Research analyst Holger Mueller said:

"AI changes everything, and that includes quantum. With new open-source libraries, Nvidia tackles key quantum problems like calibration. Naturally, these advances run on the Nvidia platform. For CxOs, it is clear that quantum will be deployed in a hybrid fashion of on premises and in the cloud and quantum systems and AI systems be tied together along with HPC systems."

Key points about the Ising launch:

• Nvidia CEO Jensen Huang said, "AI is essential to making quantum computing practical" and "AI will become the control plane of quantum machines."
• Ising Calibration is a vision language model that can interpret and react to measurements from quantum processors. AI agents can continually calibrate.
• Ising Decoding has two variants of neural networks optimized for speed or accuracy for real time decoding for quantum error correction.
• Nvidia will provide a cookbook of quantum computing workflows and training data and Nvidia NIM microservices.
• Ising rides along with Nvidia CUDA-Q as well as Nvidia NVQLink to bridge GPU and quantum systems.