NVIDIA has launched NVIDIA Ising, the world’s first family of open-source AI models designed specifically to accelerate the development of practical, large-scale quantum computers. The new models address two of the most persistent barriers to usable quantum computing: quantum processor calibration and quantum error correction.

As quantum processors scale, they require continuous calibration and real-time error correction to remain reliable. NVIDIA said artificial intelligence is critical to overcoming these challenges and transforming today’s fragile, noise-prone qubits into scalable and dependable systems capable of running real-world applications. Open-source delivery also allows enterprises and researchers to maintain full control over their data, infrastructure, and customization workflows.

Critical in Quantum Computing

Named after the foundational Ising mathematical model, which simplified the study of complex physical systems, the NVIDIA Ising family provides high-performance, scalable AI tools optimized for hybrid quantum–classical architectures. According to the company, the models deliver up to 2.5x faster performance and three times greater accuracy than traditional approaches for quantum error-correction decoding.

“AI is essential to making quantum computing practical,” said Jensen Huang, founder and CEO of NVIDIA. “With Ising, AI becomes the control plane — the operating system of quantum machines — transforming fragile qubits to scalable and reliable quantum‑GPU systems.”

The Ising family includes two primary model types. Ising Calibration is a vision-language model that can rapidly interpret measurements from quantum processors and respond in real time. This approach enables AI agents to automate continuous calibration, reducing tuning cycles from days to hours. Ising Decoding uses 3D convolutional neural networks to perform real-time quantum error-correction decoding, with variants optimized separately for speed and accuracy.

Ecosystem Partners

NVIDIA said the models are already being adopted across the quantum ecosystem. Early users include 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 U.K. National Physical Laboratory. These organizations are using Ising to advance quantum processor development and hybrid quantum‑classical systems.

The announcement comes as the global quantum computing market is projected to exceed $11 billion by 2030, according to analyst firm Resonance. NVIDIA noted that future growth depends heavily on solving foundational engineering challenges such as scalability and error correction—areas where AI-driven approaches are increasingly seen as essential.

By releasing Ising as open-source models, NVIDIA aims to accelerate collaboration across academia, research institutions, and enterprises, positioning AI as a core enabling layer for next-generation quantum computing systems.

15 April 2026