NVIDIA has introduced its first family of open-source quantum AI models, NVIDIA Ising, aimed at helping researchers and enterprises overcome critical barriers in quantum computing, including processor calibration and error correction. Designed as high-performance, scalable tools, the Ising models leverage AI to improve the reliability and scalability of hybrid quantum-classical systems, delivering up to 2.5x faster performance and 3x higher accuracy in decoding for quantum error correction. The suite includes Ising Calibration, a vision-language model that automates processor calibration, significantly reducing timelines, and Ising Decoding models optimized for real-time error correction.
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“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.” Already adopted by leading enterprises, academic institutions, and research labs, the models are complemented by NVIDIA NIM microservices and workflow resources, enabling developers to customize solutions while maintaining data control, as the quantum computing market accelerates toward projected multi-billion-dollar growth.