Nvidia on Tuesday unveiled NVIDIA Ising, a new family of open source quantum AI models it says can help researchers and enterprises build quantum processors capable of running useful applications. The company said Ionq is already using Ising Calibration, placing the quantum computing company among the first known adopters of the system.
Nvidia said the models are designed to make quantum machines more reliable by improving calibration and quantum error correction, two areas the company described as critical to turning today’s processors into large-scale computers. Jensen Huang said, “AI is essential to making quantum computing practical,” and added that with Ising, “AI becomes the control plane — the operating system of quantum machines — transforming fragile qubits to scalable and reliable quantum-GPU systems.”
The company said Ising models deliver up to 2.5x faster performance and 3x higher accuracy for the decoding process used in quantum error correction. Nvidia also said Ising Calibration is already in use by Atom Computing, Academia Sinica, EeroQ, Conductor Quantum, 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, Q-CTRL and the U.K. National Physical Laboratory. Ising Decoding is being deployed by Cornell University, EdenCode, Infleqtion, IQM Quantum Computers, Quantum Elements, Sandia National Laboratories, SEEQC, the University of California San Diego, UC Santa Barbara, the University of Chicago, the University of Southern California and Yonsei University.
Nvidia said it is also providing a cookbook of quantum computing workflows and training data, along with NVIDIA NIM microservices. The models can run locally on researchers’ systems, which Nvidia said helps protect proprietary data. Ising complements the company’s CUDA-Q software platform for hybrid quantum-classical computing and integrates with NVQLink, the hardware interconnect Nvidia says supports real-time control and quantum error correction.
The announcement lands as Nvidia and its partners push quantum software further toward practical use, with the company saying major gains in calibration and error correction are still needed before useful applications can scale. Nvidia pointed to analyst firm Resonance’s estimate that the quantum computing market will surpass $11 billion in 2030, a forecast that helps explain why companies and labs are moving quickly to test tools that promise higher accuracy and faster decoding today.