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QuEra to Bring Fault-Tolerant Quantum Computing to AWS in 2028

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June 15, 2026 by Ivy Delaney

QuEra Computing will deliver Libra, its first fault-tolerant quantum computer, to Amazon Web Services in 2028, a significant step toward practical quantum applications. The Libra system is designed to perform on the order of one million reliable logical quantum operations, a key metric for overcoming the limitations of current noisy quantum systems. Projected specifications include over 256 error-corrected logical qubits and a targeted logical error rate of 10⁻⁶, promising a substantial leap in computational reliability for research and commercial workflows. “Fault-tolerant quantum computing is moving from a scientific milestone to an engineering and deployment roadmap,” said Andy Ory, CEO of QuEra Computing. This expanded multi-year collaboration builds on QuEra’s existing relationship with AWS, bringing a new era of scalable, cloud-accessible fault-tolerance to quantum computing.

Libra System: QuEra’s 2028 Fault-Tolerant Quantum Computer Specs

This focus on operational capacity, rather than solely qubit count, signals a shift toward engineering viable quantum computation, as the number of error-free operations dictates the complexity of solvable problems. The Libra architecture is not simply a theoretical design; QuEra emphasizes a foundation built on validated research. Teams at QuEra, Harvard, and MIT have published eight peer-reviewed papers in journals like Nature and Physical Review Letters demonstrating key capabilities, including the creation of logical qubits, the building blocks of error-corrected computing, and below-threshold error correction, where errors diminish as system size increases. This commitment to open science and validation is central to QuEra’s strategy. The system also features transversal logical operations, fast decoding for real-time error correction, and resource-efficient error-correcting codes designed to minimize the physical-qubit cost per logical qubit.

A key specification for Libra is its targeted logical error rate of 10⁻⁶, representing a significant improvement over existing systems and a crucial factor in enabling early commercial and research workflows. This level of reliability is intended to support complex tasks like molecular simulation and materials discovery, areas where classical computers struggle with scaling. QuEra is already preparing for this future, standing up successive generations of fault-tolerant systems internally to refine the design and provide hands-on access to strategic partners. Bob Sorensen, Chief Analyst for Quantum Computing at Hyperion Research, agrees, stating that QuEra’s plan to deliver fault-tolerant systems in 2028 represents a significant inflection point for the quantum computing industry.

We believe fault-tolerant quantum computing will become a foundational part of how customers solve their hardest computational problems on AWS.

Eric Kessler, General Manager, Amazon Braket, at AWS
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AWS fault tolerance logical qubits QuEra Computing
Avatar of Ivy Delaney

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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