By Tom Lubowe
Publication Date: 2026-04-14 14:15:00
NVIDIA Ising is the world’s first family of open AI models for building quantum processors, launching with two model domains: Ising Calibration and Ising Decoding.
Both target the fundamental challenge in quantum computing—qubits are inherently noisy. The best quantum processors make an error roughly once in every thousand operations. To become useful accelerators for scientific and enterprise problems, error rates must drop to one in a trillion or better. AI is the most promising path to closing that gap at scale.
Calibration is the process of understanding the noise in each quantum processor and tuning it to achieve the best possible performance. Calibration minimizes error, but because of noise in quantum systems, errors must be corrected in real time by a classical computer, faster than they accumulate. This process is called quantum error correction decoding. Both calibration and decoding are computationally intensive and need improved methods to drive progress. Ising delivers advanced performance on calibration and error correction decoding, using techniques for scaling to millions of qubits.
NVIDIA Ising provides open base models, a training framework, and workflows for fine-tuning, quantization, and deployment. The pre-trained models deliver top performance out of the box, and because everything is open, users can also specialize for their own hardware and noise characteristics while keeping proprietary QPU data on-site.
In this post, we dive…