TL;DR — Key Takeaways
- IonQ will install a Superion 256 quantum computer at Nvidia’s Boston research center in 2027, making it NVAQC’s first on-site QPU.
- The system will connect with Nvidia’s GB200 NVL72 platform through NVQLink, with hybrid quantum and classical workloads orchestrated using CUDA-Q.
- IonQ and Nvidia plan to use the installation to study quantum-GPU integration, error correction, hybrid software and applications in finance, materials science and drug discovery.
IonQ announced it will install a Superion 256 quantum computer at Nvidia’s Accelerated Quantum Research Center (NVAQC) in Boston next year. The company’s trapped-ion system will be the first quantum processing unit deployed on site at NVAQC.
The Superion 256 system will connect to Nvidia’s GB200 NVL72 accelerated computing platform through NVQLink, Nvidia’s architecture for tightly coupling quantum systems with GPU accelerated computing. Hybrid workloads will be orchestrated with CUDA-Q, Nvidia’s open source quantum development platform.
Nvidia announced NVAQC in 2025 as a research center for integrating quantum hardware with AI supercomputers and named several quantum hardware and software companies as collaborators. The companies said their joint research there will focus on hybrid software, large-scale system prototypes and quantum-GPU co-design.
“What we’re looking towards is a future where QPUs join CPUs, GPUs, NICs and Ethernet switches in these very complicated systems to enable solutions for problems that aren’t possible today,” Timothy Costa, Nvidia vice president and general manager for quantum, said during a press briefing. Costa noted there are still a “tremendous number of challenges that have to be addressed to get there.”
Those include system and application challenges, Costa said, and NVAQC gives researchers a lab to work through the problems involved in building, programming and operating quantum-GPU supercomputers. That work includes processor connections, hybrid application software, AI-assisted calibration and quantum error correction, and applications that can make use of the combined systems, he said.
Costa said quantum error correction places demanding requirements on the connection between quantum and classical hardware because measurement data must move out of the quantum system and classical computations must finish within the time available for the results to be fed back. Nvidia designed NVQLink to provide that tight connection between quantum control systems and GPU-accelerated computing with a low-latency, high-throughput architecture to support error correction workloads.
Nvidia and IonQ say their engineers will work closely at NVAQC to identify what needs to change across their respective technology stacks. Costa said the resulting research could influence Nvidia’s future product roadmap as the companies investigate how QPUs, GPUs and CPUs can operate as parts of a single computing system.
IonQ introduced Superion earlier this month as its sixth-generation quantum platform. The first model is a 256-qubit trapped-ion system and uses electronic qubit controls integrated onto the chip, technology IonQ gained through its 2025 acquisition of Oxford Ionics. The company says the design makes the platform easier to manufacture and deploy with conventional data center infrastructure. IonQ also plans a 10,000-qubit Superion generation that it says will be the first hardware built to run its Walking Cat architecture, a blueprint for fault-tolerant quantum computing that covers how applications are compiled, errors are corrected and ions move across the chip. Superion 256 is available to order now, with first customer deliveries planned for 2027.
The NVAQC Superion installation is also scheduled for 2027. IonQ said research at the center is expected to cover use cases like portfolio optimization and risk modeling in financial services, materials science and computational chemistry for drug discovery. During the press briefing, IonQ CEO Niccolo de Masi framed the collaboration as part of the ongoing convergence between AI and quantum computing.
“When I look at where applied science and potential cybersecurity risks are heading, there’s no doubt that the acceleration in what LLMs are doing on NVIDIA hardware, plus what IonQ is doing with QPUs on our own, is changing the world now on a combined basis,” De Masi said. “We think that will be doubly powerful, doubly exponential, and just a lot more practical.”