InQuanto Integrates NVIDIA cuQuantum for Native GPU Support and Prepares for the Era of Quantum Supercomputing
With quantum progress accelerating, we introduce InQuanto v4.0 and explain how it supports customers and researchers exploring the application of AI, HPC and quantum computing – A.K.A. Quantum Supercomputing – to problems in chemistry and related fields
Chemistry plays a central role in the modern global economy, as it has for centuries. From Antoine Lavoisier to Alessandro Volta, Marie Curie to Venkatraman Ramakrishnan, pioneering chemists drove progress in fields such as combustion, electrochemistry, and biochemistry. They contributed to our mastery of critical 21st century materials such as biodegradable plastics, semiconductors, and life-saving pharmaceuticals.
Advances in high-performance computing (HPC) and AI have brought fundamental and industrial science ever more within the scope of methods like data science and predictive analysis. In modern chemistry, it has become routine for research to be aided by computational models run in silico. Yet, due to their intrinsically quantum mechanical nature, “strongly correlated” chemical systems – those involving strongly interacting electrons or highly interdependent molecular behaviors – prove extremely hard to accurately simulate using classical computers alone. Quantum computers running quantum algorithms are designed to meet this need. Strongly correlated systems turn up in potential applications such as smart materials, high-temperature superconductors, next-generation electronic devices, batteries and fuel cells, revealing the economic potential of extending our understanding of these systems, and the motivation to apply quantum computing to computational chemistry.
For senior business and research leaders driving value creation and scientific discovery, a critical question is how will the introduction of quantum computers affect the trajectory of computational approaches to fundamental and industrial science?
Introducing InQuanto v4.0
This is the exciting context for our announcement of InQuanto v4.0, the latest iteration of our computational chemistry platform for quantum computers. Developed over many years in close partnership with computational chemists and materials scientists, InQuanto has become an essential tool for teams using the most advanced methods for simulating molecular and material systems. InQuanto v4.0 is packed with powerful updates, including the capability to incorporate NVIDIA’s tensor network methods for large-scale classical simulations supported by graphical processing units (GPUs).
When researching chemistry on quantum computers, we use classical HPC to perform tasks such as benchmarking, and for classical pre- and post-processing with computational chemistry methods such as density functional theory. This powerful hybrid quantum-classical combination with InQuanto accelerated our work with partners such as , and . Global businesses and national governments alike are gearing up for the use of such hybrid “quantum supercomputers” to become standard practice.
In a recent technical blog post, we explored the rapid development and deployment of InQuanto for research and enterprise users, offering insights for combining quantum and high-performance classical methods with only a few lines of code. Here, we provide a higher-level overview of the value InQuanto brings to fundamental and industrial research teams.
InQuanto v4.0 – under the hood
InQuanto v4.0 is the most powerful version to date of our advanced quantum computational chemistry platform. It supports our users in applying quantum and classical computing methods to problems in chemistry and, increasingly, adjacent fields such as condensed matter physics.
Like previous versions of InQuanto, this one offers state-of-the-art algorithms, methods, and error handling techniques out of the box. Quantum error correction and detection have enabled rapid progress in quantum computing, such as groundbreaking demonstrations in partnership with Microsoft, in April and September 2024, of highly reliable “logical qubits”. Qubits are the core information-carrying components of a quantum computer and by forming them into an ensemble, they are more resistant to errors, allowing more complex problems to be tackled while producing accurate results. InQuanto continues to offer leading-edge quantum error detection protocols as standard and supports users to explore the potential of algorithms for fault-tolerant machines.
InQuanto v4.0 also marks the significant step of introducing native support for tensor networks using GPUs to accelerate simulations. In 2022, ҹɫֱ and NVIDIA teamed up on one of the quantum computing industry’s earliest quantum-classical collaborations. InQuanto v4.0 introduces classical tensor network methods via an interface with NVIDIA's cuQuantum SDK. Interfacing with cuQuantum enables the simulation of many quantum circuits via the use of GPUs for applications in chemistry that were previously inaccessible, particularly those with larger numbers of qubits.
“Hybrid quantum-classical supercomputing is accelerating quantum computational chemistry research. With ҹɫֱ’s InQuanto v4.0 platform and NVIDIA’s cuQuantum SDK, InQuanto users now have access to unique tensor-network-based methods, enabling large-scale and high-precision quantum chemistry simulations” - Tim Costa, Senior Director of HPC and Quantum Computing at NVIDIA
We are also responding to our users’ needs for more robust, enterprise-grade management of applications and data, by incorporating InQuanto into ҹɫֱ Nexus. This integration makes it far easier and more efficient to build hybrid workflows, decode and store data, and use powerful analytical methods to accelerate scientific and technical progress in critical fields in natural science.
Adding further capabilities, we our integration of InQuanto with Microsoft’s Azure Quantum Elements (AQE), allowing users to seamlessly combine AQE’s state-of-the-art HPC and AI methods with the enhanced quantum capabilities of InQuanto in a single workflow. The first end-to-end workflow using HPC, AI and quantum computing was demonstrated using AQE and ҹɫֱ Systems hardware, achieving chemical accuracy and demonstrating the advantage of logical qubits compared to physical qubits in modeling a catalytic reaction.
Where InQuanto takes us next
In the coming years, we expect to see scientific and economic progress using the powerful combination of quantum computing, HPC, and artificial intelligence. Each of these computing paradigms contributes to our ability to solve important problems. Together, their combined impact is far greater than the sum of their parts, and we recognize that these have the potential to drive valuable computational innovation in industrial use-cases that really matter, such as in energy generation, transmission and storage, and in chemical processes essential to agriculture, transport, and medicine.
Building on our recent hardware roadmap announcement, which supports scientific quantum advantage and a commercial tipping point in 2029, we are demonstrating the value of owning and building out the full quantum computing stack with a unified goal of accelerating quantum computing, integrating with HPC and AI resources where it shows promise, and using the power of the “quantum supercomputer” to make a positive difference in fundamental and industrial chemistry and related domains.
In close collaboration with our customers, we are driving towards systems capable of supporting quantum advantage and unlocking tangible and significant business value.
To access InQuanto today, including ҹɫֱ Systems and third-party hardware and emulators, visit: /products-solutions/inquanto
To get started with ҹɫֱ Nexus, which meets all your quantum computing needs across ҹɫֱ Systems and third-party backends, visit: /products-solutions/nexus
To find out more and access ҹɫֱ Systems, visit: /products-solutions/quantinuum-systems
About ҹɫֱ
ҹɫֱ,the world’s largest integrated quantum company, pioneers powerful quantum computers and advanced software solutions. ҹɫֱ’s technology drives breakthroughs in materials discovery, cybersecurity, and next-gen quantum AI. With over 500 employees, including 370+ scientists and engineers, ҹɫֱ leads the quantum computing revolution across continents.
Quantum computing companies are poised to exceed $1 billion in revenues by the close of 2025, to McKinsey & Company, underscoring how today’s quantum computers are already delivering customer value in their current phase of development.
This figure is projected to reach upwards of $37 billion by 2030, rising in parallel with escalating demand, as well as with the scale of the machines and the complexity of problem sets of which they will be able to address.
Several systems on the market today are fault-tolerant by design, meaning they are capable of suppressing error-causing noise to yield reliable calculations. However, the full potential of quantum computing to tackle problems of true industrial relevance, in areas like medicine, energy, and finance, remains contingent on an architecture that supports a fully fault-tolerant universal gate set with repeatable error correction—a capability that, until now, has eluded the industry.
ҹɫֱ is the first—and only—company to achieve this critical technical breakthrough, universally recognized as the essential precursor to scalable, industrial-scale quantum computing. This milestone provides us with the most de-risked development roadmap in the industry and positions us to fulfill our promise to deliver our universal, fully fault-tolerant quantum computer, Apollo, by 2029.
In this regard, ҹɫֱ is the first company to step from the so-called “NISQ” (noisy intermediate-scale quantum) era towards utility-scale quantum computers.
Unpacking our achievement: first, a ‘full’ primer
A quantum computer uses operations called gates to process information in ways that even today’s fastest supercomputers cannot. The industry typically refers to two types of gates for quantum computers:
- Clifford gates, which can be easily simulated by classical computers, and are relatively easy to implement; and
- Non-Clifford gates, which are usually harder to implement, but are required to enable true quantum computation (when combined with their siblings).
A system that can run both gates is classified as and has the machinery to tackle the widest range of problems. Without non-Clifford gates, a quantum computer is non-universal and restricted to smaller, easier sets of tasks - and it can always be simulated by classical computers. This is like painting with a full palette of primary colors, versus only having one or two to work with. Simply put, a quantum computer that cannot implement ‘non-Clifford’ gates is not really a quantum computer.
A fault-tolerant, or error-corrected, quantum computer detects and corrects its own errors (or faults) to produce reliable results. ҹɫֱ has the best and brightest scientists dedicated to keeping our systems’ error rates the lowest in the world.
For a quantum computer to be fully fault-tolerant, every operation must be error-resilient, across Clifford gates and non-Clifford gates, and thus, performing “a full gate set” with error correction. While some groups have performed fully fault-tolerant gate sets in academic settings, these demonstrations were done with only a few qubits and —too high for any practical use.
Today, we have published that establishes ҹɫֱ as the first company to develop a complete solution for a universal fully fault-tolerant quantum computer with repeatable error correction, and error rates low enough for real-world applications.
This is where the magic happens
The describes how scientists at ҹɫֱ used our System Model H1-1 to perfect magic state production, a crucial technique for achieving a fully fault-tolerant universal gate set. In doing so, they set a record magic state infidelity (7x10-5), 10x better than any .
Our simulations show that our system could reach a magic state infidelity of 10^-10, or about one error per 10 billion operations, on a larger-scale computer with our current physical error rate. We anticipate reaching 10^-14, or about one error per 100 trillion operations, as we continue to advance our hardware. This means that our roadmap is now derisked.
Setting a record magic state infidelity was just the beginning. The paper also presents the first break-even two-qubit non-Clifford gate, demonstrating a logical error rate below the physical one. In doing so, the team set another record for two-qubit non-Clifford gate infidelity (2x10-4, almost 10x better than our physical error rate). Putting everything together, the team ran the first circuit that used a fully fault-tolerant universal gate set, a critical moment for our industry.
Flipping the switch
In the , co-authored with researchers at the University of California at Davis, we demonstrated an important technique for universal fault-tolerance called “code switching”.
Code switching describes switching between different error correcting codes. The team then used the technique to demonstrate the key ingredients for universal computation, this time using a code where we’ve previously demonstrated full error correction and the other ingredients for universality.
In the process, the team set a new record for magic states in a distance-3 error correcting code, over 10x better than with error correction. Notably, this process only cost 28 qubits . This completes, for the first time, the ingredient list for a universal gate setin a system that also has real-time and repeatable QEC.
Fully equipped for fault-tolerance
Innovations like those described in these two papers can reduce estimates for qubit requirements by an order of magnitude, or more, bringing powerful quantum applications within reach far sooner.
With all of the required pieces now, finally, in place, we are ‘fully’ equipped to become the first company to perform universal fully fault-tolerant computing—just in time for the arrival of Helios, our next generation system launching this year, and what is very likely to remain as the most powerful quantum computer on the market until the launch of its successor, Sol, arriving in 2027.
If we are to create ‘next-gen’ AI that takes full advantage of the power of quantum computers, we need to start with quantum native transformers. Today we announce yet again that ҹɫֱ continues to lead by demonstrating concrete progress — advancing from theoretical models to real quantum deployment.
The future of AI won't be built on yesterday’s tech. If we're serious about creating next-generation AI that unlocks the full promise of quantum computing, then we must build quantum-native models—designed for quantum, from the ground up.
Around this time last year, we introduced Quixer, a state-of-the-art quantum-native transformer. Today, we’re thrilled to announce a major milestone: one year on, Quixer is now running natively on quantum hardware.
Why this matters: Quantum AI, born native
This marks a turning point for the industry: realizing quantum-native AI opens a world of possibilities.
Classical transformers revolutionized AI. They power everything from ChatGPT to real-time translation, computer vision, drug discovery, and algorithmic trading. Now, Quixer sets the stage for a similar leap — but for quantum-native computation. Because quantum computers differ fundamentally from classical computers, we expect a whole new host of valuable applications to emerge.
Achieving that future requires models that are efficient, scalable, and actually run on today’s quantum hardware.
That’s what we’ve built.
What makes Quixer different?
Until Quixer, quantum transformers were the result of a brute force “copy-paste” approach: taking the math from a classical model and putting it onto a quantum circuit. However, this approach does not account for the considerable differences between quantum and classical architectures, leading to substantial resource requirements.
Quixer is different: it’s not a translation – it's an innovation.
With Quixer, our team introduced an explicitly quantum transformer, built from the ground up using quantum algorithmic primitives. Because Quixer is tailored for quantum circuits, it's more resource efficient than most competing approaches.
As quantum computing advances toward fault tolerance, Quixer is built to scale with it.
What’s next for Quixer?
We’ve already deployed Quixer on real-world data: genomic sequence analysis, a high-impact classification task in biotech. We're happy to report that its performance is already approaching that of classical models, even in this first implementation.
This is just the beginning.
Looking ahead, we’ll explore using Quixer anywhere classical transformers have proven to be useful; such as language modeling, image classification, quantum chemistry, and beyond. More excitingly, we expect use cases to emerge that are quantum-specific, impossible on classical hardware.
This milestone isn’t just about one model. It’s a signal that the quantum AI era has begun, and that ҹɫֱ is leading the charge with real results, not empty hype.
Stay tuned. The revolution is only getting started.
Our team is participating in (ISC 2025) from June 10-13 in Hamburg, Germany!
As quantum computing accelerates, so does the urgency to integrate its capabilities into today’s high-performance computing (HPC) and AI environments. At ISC 2025, meet the ҹɫֱ team to learn how the highest performing quantum systems on the market, combined with advanced software and powerful collaborations, are helping organizations take the next step in their compute strategy.
ҹɫֱ is leading the industry across every major vector: performance, hybrid integration, scientific innovation, global collaboration and ease of access.
- Our industry-leading quantum computer holds the record for performance with a Quantum Volume of 2²³ = 8,388,608 and the highest fidelity on a commercially available QPU available to our users every time they access our systems.
- Our systems have been validated by a #1 ranking against competitors in a recent benchmarking study by Jülich Research Centre.
- We’ve laid out a clear roadmap to reach universal, fully fault-tolerant quantum computing by the end of the decade and will launch our next-generation system, Helios, later this year.
- We are advancing real-world hybrid compute with partners such as RIKEN, NVIDIA, SoftBank, STFC Hartree Center and are pioneering applications such as our own GenQAI framework.
Exhibit Hall
From June 10–13, in Hamburg, Germany, visit us at Booth B40 in the Exhibition Hall or attend one of our technical talks to explore how our quantum technologies are pushing the boundaries of what’s possible across HPC.
Presentations & Demos
Throughout ISC, our team will present on the most important topics in HPC and quantum computing integration—from near-term hybrid use cases to hardware innovations and future roadmaps.
Multicore World Networking Event
- Monday, June 9 | 7:00pm – 9:00 PM at Hofbräu Wirtshaus Esplanade
In partnership with Multicore World, join us for a ҹɫֱ-sponsored Happy Hour to explore the present and future of quantum computing with ҹɫֱ CCO, Dr. Nash Palaniswamy, and network with our team.
H1 x CUDA-Q Demonstration
- All Week at Booth B40
We’re showcasing a live demonstration of NVIDIA’s CUDA-Q platform running on ҹɫֱ’s industry-leading quantum hardware. This new integration paves the way for hybrid compute solutions in optimization, AI, and chemistry.
Register for a demo
HPC Solutions Forum
- Wednesday, June 11 | 2:20 – 2:40 PM
“Enabling Scientific Discovery with Generative Quantum AI” – Presented by Maud Einhorn, Technical Account Executive at ҹɫֱ, discover how hybrid quantum-classical workflows are powering novel use cases in scientific discovery.
See You There!
Whether you're exploring hybrid solutions today or planning for large-scale quantum deployment tomorrow, ISC 2025 is the place to begin the conversation.
We look forward to seeing you in Hamburg!