HOBOKEN, NJ – October 1, 2026 -- Quantum Computing Inc. a vertically integrated quantum systems company pioneering photonics and semiconductor manufacturing, today announced Dirac-3S, the next-generation of its Dirac-3 quantum optimization machine, marking a significant step toward commercial deployment of QCi’s quantum optimization technology.

Dirac-3S advances the platform across three areas – Speed, Scale and Solutions – with faster performance, improved solution quality, increased computing capacity and a modular architecture designed to support customers as their requirements grow. The first customer shipment of Dirac-3S is expected in November 2026.

Speed. Scale. Solutions.

Speed: Dirac-3S is engineered to efficiently solve increasingly complex optimization problems, with practical computation times demonstrated on problems involving up to 9,980 variables while consistently finding the optimal solution. This enables customers to tackle larger problems and explore more possibilities in less time.

Scale: Dirac-3S features a modular architecture designed to scale with customer requirements. The compact 5U base system can be extended with Expansion Modules to support larger and more complex optimization problems, with QCi demonstrating configurations supporting up to 9,980 variables with one Expansion Module. The architecture is designed to accommodate additional Expansion Modules, enabling customers to expand their system as their optimization needs grow. QCi has also advanced the Dirac-3S hardware architecture, manufacturing processes and supply chain to support increased production volumes, consistent product quality and broader commercial deployment. These improvements include enhanced error correction, component control and operational reliability.

Solutions: Dirac-3S is designed to address a broad range of real-world optimization problems on a single platform, through multiple optimization approaches including continuous, integer and higher-order optimization. QCi’s latest error-correction techniques are designed to improve solution quality across applications in financial services, logistics and supply chains, manufacturing, energy, telecommunications, scientific research, and aerospace and defense.

The platform can be deployed on-premises or in the cloud and integrated into AI/ML pipelines, enabling organizations to incorporate quantum optimization into existing computational workflows.

“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. “We have 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 tosupport broader deployment. This gives customers a flexible path to adopt quantum optimization and scale their computing capacity as their needs grow.”

Building on the Dirac-3 Foundation

Dirac-3S builds on QCi’s first-generation Dirac-3 quantum optimization machine, which has been used by academic researchers exploring quantum optimization algorithms and applications.

“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. We look forward to exploring new research directions and accelerating the development of practical, high-impact applications,” said Professor Paul Griffin, Associate Professor, Singapore Management University.

QCi has published a new Technical Review evaluating Dirac-3S across synthetic, graph-based and industry-standard optimization benchmarks, including comparisons with Projected Gradient Descent and commercial classical solver Hexaly. On synthetic problems with known global optima ranging from 2,000 to 9,980 variables, Dirac-3S was the only evaluated solver to achieve the optimal solution across all tested instances, while solution times increased only modestly as problem size approached 9,980 variables. On industry-standard DIMACS maximum-clique benchmarks, Dirac-3S more frequently identified the highest-quality solutions than the other evaluated methods.

QCi has also published a survey paper demonstrating how NP-hard problems can be mapped to simplex formulations native to Dirac-3S, expanding its potential applications across continuous, discrete and combinatorial optimization. The Technical Review, along with the detailed benchmarking methodology and results is available in QCi’s Dirac-3S Technical Reference at: https://quantumcomputinginc.com/learn/module/dirac-3s-technical-reference. To learn more about the Dirac-3S, visit QCi’s Dirac-3S webpage.