# Nvidia expands open source CUDA-Q for fault-tolerant quantum computing > Source: > Published: 2026-09-14 13:00:00+00:00 *Become a member of GB MAX to gain exclusive access to the industry and to the most influential global B2B leadership community in the business of gaming, entertainment, and tech.* [Join now](https://go.gamesbeat.com/gb-max/)and also get a VIP ticket to GamesBeat Next (Nov 2-3, SF). [Nvidia](https://www.nvidia.com) today announced an expansion of the Nvidia CUDA-Q open source platform for fault-tolerant quantum computing. Nvidia launched CUDA-Q Logical, an orchestration layer that provides a programmable, verifiable approach to developing useful applications for fault-tolerant quantum computers. Fault-tolerant quantum processors with logical qubits are essential for useful quantum computing, allowing systems to overcome the errors inherent in physical qubits so they can execute the larger computations needed for practical applications such as drug discovery, financial modeling and materials development. However, developing applications for such systems is a tedious, time-consuming codesign challenge: A change to an algorithm, error-correction code, hardware architecture or other QPU component can significantly change the resources needed to run any given application. With CUDA-Q Logical, researchers can now design and orchestrate the many components required for fault-tolerant quantum computing applications, easily switching between options to identify optimal system configurations for performance with logical qubits. “Quantum computing is maturing into an era of logical qubits, and researchers need an open, customizable platform capable of representing all aspects of a fault-tolerant system,” said Timothy Costa, vice president and general manager of quantum at Nvidia, in a statement. “The addition of CUDA-Q Logical provides power and flexibility to explore fully integrated, co-optimized systems regardless of qubit type and architecture — drastically shortening the timeline to useful quantum-GPU supercomputing.” CUDA-Q Logical is already being used by QPU makers and labs including Fermi National Accelerator Laboratory, Infleqtion, IQM Quantum Computers, QCDesign Quantum Motion and Sandia National Laboratories. Using CUDA-Q Logical, Iceberg Quantum modeled its fault-tolerant architecture for Diraq’s qubits, showing how 1,000 logical qubits can be created with just 150,000 physical qubits, roughly 10x fewer than Diraq’s previous estimates. CUDA-Q Logical gave an unprecedented way to rapidly assess potential implementations of Iceberg’s architecture, helping dramatically reduce the hardware needed for useful, fault-tolerant quantum computing. ## Fermilab uses CUDA-Q Logical to explore fault-tolerant applications In early work, Fermilab researchers used CUDA-Q Logical to validate prior results and evaluate physical qubits, runtimes and other resource requirements across different error-correction approaches and quantum hardware. Fermilab transformed complicated fault-tolerant system designs into a repeatable and verifiable computational workflow, accelerating fault-tolerant algorithm development from five months to three weeks, a 7x speedup. “Fault-tolerant quantum computing is the path to unlocking new scientific discovery, but getting there will require researchers to codesign algorithm, error correction, architectures and hardware together,” said Anna Grassellino, chief technology officer at Fermilab and director of the Superconducting Quantum Materials and Systems Center, in a statement. “Using CUDA-Q Logical, our team explored combinations of these resources in just three weeks, compared with what would have typically taken about five months of building specialized infrastructure.” ## Sandia creates benchmark for future of quantum computing QUOPS is a new, independent cross-platform benchmark developed by Sandia National Laboratories that measures the progress quantum computing systems are making toward utility-scale applications. With Sandia’s QUOPS, the industry now has access to a hardware-agnostic, open system to benchmark progress toward shared goals for fault-tolerant quantum computers. Historically, progress in quantum computing has been measured primarily through advances in physical qubits — increasing qubit counts, improving fidelity and extending coherence. “At Sandia, we can’t wait to see fault-tolerant quantum computers helping to solve problems of national importance for the Department of Energy and the United States,” said Timothy Proctor, co-director of Sandia National Laboratories’ Quantum Performance Laboratory, in a statement. “Our mission right now is to bring that about sooner, by accelerating our industry partners’ progress. To do that, we, and other quantum computing stakeholders, have to be able to track and forecast the growth of quantum computer abilities. We created QUOPS to do exactly that, and we’re excited to see it used by quantum computing vendors and customers.” ## Expanding the quantum-GPU supercomputing platform The ecosystem is also adopting Nvidia’s larger lineup of quantum computing technologies for turning qubits into useful quantum-GPU supercomputers. Diraq used Nvidia Ising, the world’s first family of open models for building and deploying AI for useful quantum computing, to calibrate its silicon-based qubit processor. Companies are integrating their quantum processors with GPU supercomputing using Nvidia NVQLink, the open system architecture for tightly coupling quantum processors with GPU supercomputers. With NVQLink: ● Anyon Computing developed a new quantum control system. ● Quandela developed a QPU-GPU architecture. ● Quantum Machines ran a demo of integrating state-of-the-art supercomputing resources with qubits at the Israeli Quantum Computing Center. The Nvidia CUDA-Q open development platform continues to be adopted across the quantum computing ecosystem: ● BlueQubit launched the Quantum Flywheel grant program for researchers, to give them access to Nvidia accelerated computing through CUDA-Q. ● Qedma Quantum Computing and QCentroid each integrated their technology with CUDA-Q to support quantum error correction and mitigation, as well as the deployment of quantum applications. The quantum ecosystem is also working with Nvidia to develop new and improved quantum applications: ● IonQ announced progress on DQAOA-GPT, a quantum generative AI framework, using Nvidia accelerated computing. ● MITRE published work on building GPU-accelerated digital twins of quantum sensors. ● Phasecraft is using Nvidia cuQuantum to generate the largest-known variational quantum eigensolver emulated molecular database. ● UCLA and Caltech are advancing the design of control sequences needed to run quantum applications.