Quantum Computing Inc. has scaled its Dirac-3 quantum optimization machine to handle nearly 10,000 variables with the new Dirac-3S, a ten-fold increase over its previous 1,000-variable system, QCi says. The company reports the advance delivers faster performance and improved solution quality for increasingly complex optimization problems, with initial customer shipments expected in November 2026.
“Dirac-3S takes our quantum optimization platform from demonstrating what is possible to delivering a system built for practical commercial use,” said Yong Meng Sua, Chief Technology Officer of QCi. The Dirac-3S features a modular architecture designed to scale with customer requirements and address optimization challenges across industries like finance, logistics and aerospace.
Dirac-3S Achieves 9,980 Variable Quantum Optimization Scale
The Dirac-3S quantum optimization machine now solves problems involving up to 9,980 variables, a tenfold increase over Quantum Computing Inc.’s previous 1,000-variable system and a step toward tackling significantly more complex optimization challenges. This expanded capacity, demonstrated on synthetic problems with known global optima, allows the Dirac-3S to consistently find the optimal solution while other evaluated solvers struggled to achieve the same result across all tested instances.
QCi validated the performance increase through benchmarking against Projected Gradient Descent and the commercial solver Hexaly, publishing the detailed methodology and results in a new Technical Reference available to the public. The company’s approach to scaling focuses on modularity, with a base 5U system expandable via modules to accommodate growing computational demands. The Dirac-3S’s architecture is designed to support additional Expansion Modules, offering customers a scalable path to increase system capacity as their optimization needs evolve.
Beyond simply increasing the number of variables, QCi has also focused on advancements in hardware architecture, manufacturing processes and supply chain management to ensure consistent product quality and support broader commercial deployment, according to the company. These improvements include enhanced error correction techniques, designed to improve solution quality across applications ranging from financial services and logistics to manufacturing and aerospace.
The platform’s versatility extends to its deployment options, functioning both on-premises and within cloud environments, and integrating into existing artificial intelligence and machine learning workflows, the company says. QCi has increased performance and computing capacity, expanded the size and complexity of problems the system can address through a modular architecture, and advanced the hardware and manufacturing architecture needed to support broader deployment.
The company anticipates the first customer shipments of the Dirac-3S upgrade will begin in November 2026, signaling a near-term timeline for commercial availability of the increased capacity. QCi’s development of the Dirac-3S builds upon the foundation of its first-generation Dirac-3 machine, which served as a platform for academic researchers exploring quantum optimization algorithms.
Professor Paul Griffin, Associate Professor at Singapore Management University, highlighted the value of the initial Dirac-3, stating, “Our experience with the first-generation Dirac-3 quantum optimization machine validated its potential as a powerful tool for solving meaningful optimization problems.” QCi’s continued innovation with the Dirac-3S, including its expanded computational capabilities, enables us to pursue significantly larger and more complex optimization challenges. He added that they look forward to exploring new research directions and accelerating the development of practical, high-impact applications.
The company also published a survey paper detailing how NP-hard problems can be mapped to simplex formulations native to the Dirac-3S, broadening the range of potential applications to encompass continuous, discrete and combinatorial optimization. This expansion of applicability is central to QCi’s strategy, aiming to provide a single platform capable of addressing a diverse array of real-world optimization problems, the company states.
QCi frames the advancements of the Dirac-3S around three core benefits: Speed, Scale and Solutions, reflecting a focused marketing strategy centered on delivering faster performance, increased computing capacity and a flexible, scalable architecture for its customers.
Dirac-3S takes our quantum optimization platform from demonstrating what is possible to delivering a system built for practical commercial use.
Yong Meng Sua, Chief Technology Officer of QCi
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