NVIDIA on Tuesday announced what it said is the world’s first family of open-source artificial intelligence models designed to accelerate the development of practical quantum computers, as the chipmaker pushes deeper into tools for emerging computing systems.
The new model family, called NVIDIA Ising, is aimed at two of the biggest obstacles facing the quantum computing industry: calibrating quantum processors and correcting the errors that arise as fragile quantum systems operate. NVIDIA said the models can help researchers and companies build more scalable and reliable quantum machines capable of eventually running useful applications.
In a statement, CEO Jensen Huang said artificial intelligence is becoming central to making quantum computing practical, describing AI as the “control plane” for future quantum machines.
NVIDIA said the Ising family includes customizable models, tools and data for quantum calibration and quantum error-correction decoding. One model, Ising Calibration, is a vision-language model designed to interpret measurements from quantum processors and automate calibration tasks, which the company said could reduce the process from days to hours. Another, Ising Decoding, includes two variants of a 3D convolutional neural network optimized either for speed or accuracy in real-time quantum error correction. NVIDIA said those models are up to 2.5 times faster and three times more accurate than pyMatching, which it described as the current open-source industry standard.
The company said the models are already being adopted by a range of companies, universities and national laboratories. Users of Ising Calibration include Atom Computing, Academia Sinica, EeroQ, Conductor Quantum, Fermilab, Harvard’s John A. Paulson School of Engineering and Applied Sciences, Infleqtion, IonQ, IQM Quantum Computers, Lawrence Berkeley National Laboratory’s Advanced Quantum Testbed, Q-CTRL and the U.K. National Physical Laboratory. NVIDIA said 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 releasing a cookbook of quantum-computing workflows, training data and NVIDIA NIM microservices to help developers fine-tune the models for specific hardware and use cases while keeping control of their data and infrastructure. The models can also run locally on researchers’ systems, the company said.
The launch adds to NVIDIA’s broader portfolio of open models, which includes systems for agentic AI, physical AI, autonomous vehicles, robotics and biomedical research. The company said Ising is designed to complement its CUDA-Q software platform for hybrid quantum-classical computing and to integrate with NVQLink, its QPU-GPU interconnect aimed at real-time control and error correction in quantum systems.
Quantum computing remains an emerging field in which companies and researchers are trying to make unstable quantum bits, or qubits, reliable enough for large-scale use. NVIDIA cited analyst firm Resonance as projecting that the quantum computing market will surpass $11 billion by 2030, though the industry’s growth is expected to depend heavily on breakthroughs in engineering challenges such as error correction and scalability.