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Florida International University to get IonQ’s 256-qubit computer by late 2027

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September 24, 2026 by Ivy Delaney
Photo credit: Taimy Alvarez/Florida International University · prnewswire.com

Florida International University will gain access to a 256-qubit quantum computer from IonQ (NYSE: IONQ) by late 2027, establishing it as the first university in Florida with this level of quantum computing hardware. The IonQ Superion system will place FIU researchers alongside those at the University of Chicago and University of Cambridge, providing a powerful tool to address problems beyond the reach of conventional computers.

“Bringing this extraordinary research tool to Miami is an investment in discovery, in our students, and in our country’s ability to compete in a rapidly developing field,” said FIU President Jeanette M. Nuñez. This partnership designates FIU as IonQ’s flagship academic partner in Florida, aiming to create a central hub for quantum research within a growing tech ecosystem.

IonQ’s Superion 256 System Expands FIU’s Quantum Computing Access

Florida International University will be the first in the state to house a 256-qubit quantum computer, the IonQ Superion 256, scheduled for installation in late 2027. The system’s arrival is expected to significantly bolster Florida’s growing quantum computing infrastructure and provide direct access for researchers and students to a full-stack, trapped-ion quantum computer. The Superion 256 is not simply a more powerful conventional computer; it utilizes a fundamentally different method of processing information, opening avenues for tackling problems beyond the reach of classical systems.

FIU researchers plan to focus initial efforts on three key areas: environmental and energy sustainability, national security and cybersecurity, and health and drug development. Specifically, they will explore new materials, battery technologies, and grid management strategies, alongside advancements in encryption and protection of critical infrastructure. The potential for studying molecular interactions and accelerating drug discovery also forms a core component of the planned research.

Niccolo de Masi, Chairman and CEO of IonQ, emphasized the significance of this collaboration, stating, “By housing our Superion 256 system directly on campus, FIU will lead the region in quantum research and training.” The university intends to use the new hardware to attract research funding, forge industry partnerships, and solidify South Florida’s position as a center for applied quantum discovery. FIU President Jeanette M. Nuñez views the acquisition as a critical investment in the nation’s future competitiveness.

The university’s research showcase and briefing center in Washington, D.C. will facilitate engagement with federal agencies and potential partners involved in quantum initiatives focused on sensing, cryptography, commercialization, and workforce development. Plans are already underway to develop new curricula, degree programs, and professional certifications in quantum computing, further expanding educational opportunities in the field. The university anticipates supporting its more than 1,800 faculty members and 55,000 students with access to this advanced computing architecture, alongside collaborations with numerous industry partners.

This key partnership with Florida International University represents a milestone in expanding direct physical access to IonQ’s industry-leading, high-performance quantum hardware.

Niccolo de Masi, Chairman and CEO of IonQ
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Ivy Delaney

Ivy Delaney has been working with neural networks and machine learning since the mid-nineties, back when a couple of hidden layers and a long afternoon of training counted as ambitious. She has watched the field go from academic curiosity to the thing quietly running underneath everything, and she brings that long view to quantum computing. For Quantum Zeitgeist she covers the ground where the two fields meet. That means quantum machine learning and the variational algorithms it leans on, and it also means the less glamorous but more interesting story of classical machine learning already doing real work inside quantum machines, decoding error-correcting codes, calibrating noisy hardware and learning the error models that simulators depend on. She writes about the hardware those algorithms have to run on too, and about the post-quantum cryptography scramble that the same hardware has set off. Her stories typically start with the paper, whether that is peer-reviewed work, conference proceedings or an arXiv preprint, with the source linked so you can hold a claim up against the research it came from. She is unimpressed by benchmarks that will not say what they beat, and by demonstrations that only work in the press release.

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