- Nvidia (NASDAQ:NVDA) announced Ising, an open-source family of quantum AI models designed to improve quantum processor calibration and quantum error correction, key barriers to scaling useful quantum computers
- The models deliver performance gains, with up to 2.5x faster decoding and 3x higher accuracy than existing open-source tools, and include AI systems for automated, real-time calibration
- Adoption is already underway across leading enterprises, universities and national labs, with Ising integrating into NVIDIA’s broader hybrid quantum-classical computing software and hardware ecosystem
- Nvidia stock (NASDAQ:NVDA) opened trading at US$190.84
Nvidia (NASDAQ:NVDA) announced the release of Nvidia Ising, a family of open-source quantum AI models designed to help researchers and enterprises advance the development of scalable, reliable quantum processors capable of running practical applications.
The models address two of the most persistent challenges facing quantum computing: processor calibration and quantum error correction. While quantum hardware continues to improve, error rates and the difficulty of maintaining stable qubits remain key obstacles to large-scale deployment. Nvidia said artificial intelligence will play a central role in overcoming these engineering challenges by automating and accelerating critical workflows.
According to Nvidia, open-source models provide developers with flexibility and control, allowing them to build high-performance AI systems while maintaining ownership of their data and computing infrastructure. The company said this approach is intended to support collaboration across academia, national laboratories and industry.
The Ising family is named after a foundational mathematical model that simplified the understanding of complex physical systems. Nvidia said the models build on that legacy by providing scalable AI tools tailored specifically for hybrid quantum-classical systems, where conventional processors work alongside quantum hardware.
Nvidia reported that Ising models are already being used to run some of the most advanced quantum processor calibration systems. The company said the models can handle larger and more complex quantum workloads while delivering up to 2.5 times faster performance and up to three times higher accuracy in decoding tasks required for quantum error correction, compared with existing open-source methods.
The quantum computing market is projected to exceed $11 billion by 2030, according to analyst firm Resonance. Industry observers note that realizing this growth will depend largely on continued progress in quantum error correction, system stability and scalability.
The Nvidia Ising release includes multiple components. Ising Calibration is a vision-language model designed to interpret measurement data from quantum processors and respond in real time. By enabling AI agents to manage continuous calibration, the system can reduce calibration cycles from days to hours, according to the company.
Ising Decoding includes two variants of a three-dimensional convolutional neural network optimized for either speed or accuracy. These models are designed to perform real-time decoding for quantum error correction and are positioned as an alternative to pyMatching, an open-source decoding tool widely used in the field.
Nvidia said adoption of the Ising models is already underway. Organizations using Ising Calibration include Atom Computing, IonQ, IQM Quantum Computers, Lawrence Berkeley National Laboratory’s Advanced Quantum Testbed, the U.K. National Physical Laboratory, Harvard University, and several national laboratories and research institutions worldwide.
Ising Decoding is being deployed by universities and research centers including Cornell University, the University of California San Diego, the University of Chicago, Sandia National Laboratories, Yonsei University, and others working on fault-tolerant quantum architectures.
In addition to the models, Nvidia is releasing workflow guides and training datasets intended to help developers customize Ising for specific quantum hardware platforms. The company said the models can be run locally, allowing researchers to protect proprietary designs and experimental data.
Nvidia Ising is designed to integrate with the company’s CUDA-Q software platform for hybrid quantum-classical computing and its NVQLink QPU-GPU interconnect. Nvidiasaid the combined tools are intended to support real-time quantum control and error correction, with the long-term goal of enabling accelerated quantum supercomputing systems.
“AI is essential to making quantum computing practical,” Nvidia’s CEO, Jensen Huang said in a news release. “With Ising, AI becomes the control plane — the operating system of quantum machines — transforming fragile qubits to scalable and reliable quantum-GPU systems.”
Nvidia Corp. is a full-stack computing infrastructure company.
Nvidia stock (NASDAQ:NVDA) opened trading at US$190.84 and is up around 73 per cent since this time last year.
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