Nvidia Launches NVQLink Architecture for Hybrid Quantum Computing

Nvidia unveiled NVQLink at the International Conference for High Performance Computing in St. Louis on November 17, 2025, introducing an open system architecture connecting quantum processors with accelerated computing infrastructure.

The platform enables hybrid quantum-classical workflows through high-throughput, low-latency interconnects adopted by more than a dozen global supercomputing centers and quantum hardware manufacturers.

Nvidia CEO Jensen Huang described NVQLink as the Rosetta Stone connecting quantum and classical supercomputers, emphasizing the technology's role in bridging fundamentally different computing paradigms.

Quantinuum announced its newly launched Helios quantum computer, and future systems will integrate with Nvidia GPUs through NVQLink, marking a significant milestone in commercial quantum computing deployment.

What technical specifications enable hybrid quantum workflows?

NVQLink delivers 40 petaflops of AI performance at FP4 precision with a GPU to quantum processing unit throughput of 400 gigabits per second and latency under four microseconds.

The architecture uses RDMA over Converged Ethernet, enabling researchers to scale classical compute resources dynamically as quantum processors expand.

This bidirectional communication allows GPUs to perform real-time error correction, circuit optimization, and result validation while quantum systems execute computations.

The platform supports integration with Nvidia's GH200 Grace Hopper superchips and Grace Blackwell architecture, providing seamless connectivity between quantum hardware and existing high-performance computing infrastructure.

Nine US national laboratories, including Brookhaven, Fermilab, Lawrence Berkeley, Los Alamos, Oak Ridge, and Sandia, have committed to deploying NVQLink, alongside 17 quantum hardware builders and five controller manufacturers.

US Energy Secretary Chris Wright stated the technology provides critical infrastructure to unite world-class GPU supercomputers with emerging quantum processors.

Did you know?
NVQLink's 67 microsecond decoder reaction time represents a 32-fold improvement over the required two millisecond threshold, enabling real time quantum error correction previously considered impossible with existing classical computing interconnects.

How did Quantinuum demonstrate breakthrough error correction?

The collaboration between Nvidia and Quantinuum achieved the world's first real-time decoding of scalable quantum low-density parity check codes using the Helios quantum computer integrated with GH200 Grace Hopper processors.

The teams demonstrated error correction with a decoder reaction time of 67 microseconds, exceeding the required two-millisecond threshold by a factor of 32.

This performance breakthrough enables active error correction during quantum computations rather than post-processing, fundamentally changing how quantum systems can be operated.

According to technical documentation, an Nvidia GPU-based decoder integrated in the Helios control engine improved the logical fidelity of quantum operations by more than 3 percent.

For the Bring's code experiment encoding eight logical qubits into 30 physical qubits, the system achieved a 0.925 percent error rate after three rounds of quantum error correction, representing a 5.4-fold improvement over the 4.95 percent error rate prior to decoding.

These results demonstrate practical pathways toward fault-tolerant quantum computing at commercially relevant scales.

What applications benefit from quantum GPU integration?

The partnership demonstrated substantial speed improvements in quantum chemistry simulations through the ADAPT-GQE framework, a transformer-based Generative Quantum AI approach developed by Quantinuum, Nvidia, and a pharmaceutical industry leader.

The system achieved a 234-fold speed increase in generating training data for complex molecules compared to traditional quantum chemistry methods, dramatically reducing the time required to model drug candidates and materials.

NVQLink enables quantum processors to leverage GPU-accelerated machine learning for circuit synthesis, parameter optimization, and result interpretation.

Classical GPUs can perform extensive precomputation and postprocessing, while quantum systems handle exponentially complex calculations beyond classical capabilities.

This division of labor maximizes the utility of limited quantum resources while applying proven GPU acceleration techniques to expand quantum computing's practical applications across chemistry, cryptography, optimization, and materials science.

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How does NVQLink compare to previous quantum approaches?

Previous quantum computing implementations relied on slow classical feedback loops with latencies measured in milliseconds or seconds, preventing real-time error correction and limiting quantum circuit depths.

Existing quantum control systems typically use field-programmable gate arrays with limited computational capacity, restricting the complexity of error correction codes and adaptive algorithms.

NVQLink's sub-4 microsecond latency and 400 gigabit per second throughput represent orders of magnitude improvements over these legacy architectures.

The open, interoperable design contrasts with proprietary quantum-classical interfaces that locked users into specific hardware ecosystems.

NVQLink supports multiple quantum modalities, including ion traps, superconducting qubits, neutral atoms, and photonic systems, allowing researchers to select optimal hardware for specific applications.

This vendor-neutral approach accelerates innovation by enabling direct performance comparisons and allowing supercomputing centers to deploy multiple quantum technologies through unified infrastructure.

What partnerships are driving NVQLink adoption?

Quantinuum's Helios quantum computer serves as the flagship demonstration platform for NVQLink capabilities, showcasing the architecture's potential with the industry's highest reported gate fidelities.

The system combines Quantinuum's trapped ion technology with Nvidia's GPU acceleration to enable generative quantum AI workflows previously impossible with isolated quantum systems.

Additional quantum hardware manufacturers, including IonQ, Rigetti, IQM, and Pasqal, have announced NVQLink integration plans for upcoming systems.

AWS announced plans to integrate NVQLink with its Braket quantum computing service, potentially providing cloud-based access to hybrid quantum classical workflows for researchers and enterprises worldwide.

National laboratories are deploying NVQLink as part of broader quantum networking initiatives aimed at creating distributed quantum computing resources accessible to the scientific community.

These partnerships position NVQLink as infrastructure for an emerging hybrid computing ecosystem combining quantum processors, classical supercomputers, and AI accelerators into unified problem-solving platforms.

Nvidia's entry into quantum computing infrastructure represents a strategic expansion beyond its traditional GPU markets into next-generation scientific computing.

As quantum processors advance toward practical applications in drug discovery, materials design, and optimization, the ability to seamlessly integrate quantum and classical resources becomes critical for realizing commercial value.

NVQLink's adoption by leading research institutions and quantum hardware manufacturers suggests the technology addresses a fundamental gap in quantum computing infrastructure, potentially accelerating the timeline toward quantum advantage in real-world applications.