Quantinuum H-Series quantum computer accelerates through 3 more performance records for quantum volume
217, 218, and 219
In the last 6 months, Quantinuum H-Series hardware has demonstrated explosive performance improvement. Quantinuum’s System Model H1-1, Powered by Honeywell, has demonstrated going from 214 = 16,384 quantum volume (QV) announced in February 2023 to now 219 = 524,288, with all the details and data released on our GitHub repository for full transparency. At a quantum volume of 524,288, H1-1 is 1000x higher than the next best reported quantum volume.
We set a big goal back in 2020 when we launched our first quantum computer, HØ. HØ was launched with six qubits and a quantum volume of 26 = 64, and at that time we made the bold and audacious commitment to increasing the quantum volume of our commercial machines 10x per year for 5 years, equating to a quantum volume of 8,388,608 or 223 by the end of 2025. In an industry that is often accused of being over-hyped, a commitment like this was easy to forget. But we did not forget. Diligently, our scientists and engineers continued to achieve world-record after world-record in a tireless and determined pursuit to systematically improve the overall performance of our quantum computers. As seen in Figure 1, from 2020 to early 2023, we have steadily been increasing the quantum volume to demonstrate that increased qubit count while reducing errors directly translates to more computational power. Just within 2023 we’ve had multiple announcements of quantum volume improvements. In February we announced that H1-1 had leapfrogged 214 and achieved a quantum volume of 215. In May 2023, we launched H2-1 with 32 qubits at a quantum volume of 216. Now we are thrilled to announce the sequential improvements of 217, 218, and 219, all on H1-1.
Importantly, none of these results were “hero results”, meaning there are no special calibrations made just to try to make the system look better. Our quantum volume data is taken on our commercial systems interwoven with customer jobs. What we experience is what our customers experience. Instead of improving at 10x per year as we committed back in 2020, the pace of improvement over the past 6 months has been 30x, accelerating at least one year from our 5-year commitment. While these demonstrations were made using H1-1, the similarities in the designs of H1-2 (now upgraded with 20 qubits) and H2-1, our recently released second generation system, make it straightforward to share the improvements from one machine to another and achieve the same results.
In this young and rapidly evolving industry, there are and will be disagreements about which benchmarks are best to use. Quantum volume, developed by IBM, is undeniably rigorous. Quantum volume can be measured on any gate-based machine. Quantum volume has been peer-reviewed and has well defined assumptions and processes for making the measurements. Improvements in QV require consistent reductions in errors, making it likely that no matter the application, QV improvements translate to better performance. In fact, to realize the exponential increase in power that quantum computers promise, it is required to continue to reduce these error rates. The average two-qubit gate error with these three new QV demonstrations was 0.13%, the best in the industry. We measure many benchmarks, but it is for these reasons that we have adopted quantum volume as our primary system-wide benchmark to report our performance.
Putting aside the argument of which benchmark is better, year-over-year improvements in a rigorous benchmark do not happen accidentally. It can only happen because the dedicated, talented scientists and engineers that work on H-Series hardware have a deep understanding of its error model and a deep understanding of how to reduce the errors to make overall performance improvements. Equally important the talented scientists and engineers have mastery of their domain expertise and can dream-up and then implement the improvements. These validated error models become the bedrock of future systems’ design, instilling confidence that those systems will have well understood error models, and the performance of those systems can also be systematically improved and ultimate performance goals achieved. Taking nothing away from those talented scientists and engineers, but having perfect, identical qubits and employing our quantum charge coupled device (QCCD) architecture does give us an advantage that all the other architectures and other modalities do not have.
What should potential users of H-Series quantum computers take away from this write-up (and what do current users already know)?
- Quantinuum is committed to systematically improving the core performance of our quantum computing hardware. The better the fundamental performance, the lower the overhead will be when doing error mitigation, error detection, and ultimately error correction. This provides confidence in our ability to deliver fault-tolerant compute capabilities.
- Progress on your research, use-case, or application can be accelerated by getting access to H-series technology because our quantum computers can do circuits that other technologies cannot. “It actually works!” exclaim excited first-time users.
- Quantinuum intends to continue to be the quantum computing company that quietly over-delivers, even on big goals.
1. https://github.com/CQCL/quantinuum-hardware-quantum-volume
About Quantinuum
Quantinuum, the world’s largest integrated quantum company, pioneers powerful quantum computers and advanced software solutions. Quantinuum’s technology drives breakthroughs in materials discovery, cybersecurity, and next-gen quantum AI. With over 500 employees, including 370+ scientists and engineers, Quantinuum leads the quantum computing revolution across continents.
Progressing your organization along the five levels of quantum maturity
Quantum computing has moved from a bet on the future to a race already underway. Early adopters are locking in strategic partnerships, building proprietary IP, and positioning themselves years ahead of competitors who are still watching from the sidelines. For executives, the question isn't whether to engage with quantum computing. It's how far along that journey your organization actually is, and what it takes to move forward.
That's a harder question to answer than it sounds. Quantum maturity isn't a single milestone you either hit or miss. It's a progression, built across talent, technology access, workflow integration, partnerships, and value realization, and most organizations aren't entirely sure where they currently stand and what to do next.
Our new paper, A Roadmap for Quantum Maturity, is built to answer exactly that.
A Framework for Where You Stand, and Where to Go Next
Drawing on extensive client experience, the paper lays out five distinct levels of quantum maturity, from early awareness through full transformation, along with the leadership actions that move an organization from one level to the next.
- Awareness — early conversations, but no clear ownership or use cases yet
- Exploration — exploring partnerships and prioritizing use cases with limited budget
- Experimentation — quantum roadmap established and guiding dedicated teams, funding, and partners to execute pilot use case projects
- Integration — quantum computing applications are being embedded into business unit workflows, and the quantum roadmap is integrated with broader digital technology strategy, including AI, HPC, and data
- Transformation — quantum capabilities are embedded in core products and decision-making, with differentiated, proprietary advantage
Most industry leaders today sit at the exploration or experimentation stages, with clear ambitions to reach transformation within the next several years. The paper breaks down what separates organizations that progress from those that stall out at proof-of-concept.
The Advantage Is Built, Not Bought
One of the paper's central takeaways is one many executives underestimate: investing in quantum technology alone isn't enough. Organizations that advance fastest pair that investment with a deliberate strategy, building quantum literacy across leadership and technical teams, honestly assessing capability gaps, focusing on a small number of high-impact use cases tied to real business metrics, and defining a clear roadmap that connects research to business advantage.
How Quantinuum Can Help
Achieving quantum maturity is a journey, not a single step, and most organizations don't need to make that journey alone. Quantinuum's consulting services are built to support every stage of it, from advisory and use-case identification, to capability building, technology access, and the co-development of scalable quantum solutions.
Whether your organization is just starting to build awareness or already scaling toward transformation, our team can help you identify exactly where you stand today, and what it takes to move to the next level.
- SoftBank Corp. and Quantinuum articulated a roadmap connecting quantum algorithms, hardware evolution, and commercial applications, helping organizations understand when quantum computing can address real-world challenges.
- The analysis demonstrates that quantum value will emerge in stages, with early opportunities in data analysis and longer-term breakthroughs in scientific computing as fault-tolerant systems mature.
- The work provides a practical planning framework for enterprises preparing to integrate quantum computing alongside AI and classical high-performance computing infrastructure in quantum-AI data centers.
Quantum computing is increasingly moving from exploratory discussion to structured enterprise planning. As organizations begin to assess where and when quantum technologies may deliver real business impact, a new class of work is emerging: integrated roadmaps that connect algorithmic feasibility, hardware development, and commercial opportunity.
A recent white paper from SoftBank Corp. and Quantinuum represents one of the most comprehensive examples of this approach to date. Rather than treating quantum computing as a distant, abstract capability, the study constructs a detailed, quantitative framework for understanding how real-world use cases evolve as hardware matures—and what this means for enterprise strategy.
A Comprehensive Roadmap
The SoftBank–Quantinuum white paper is broad in scope. It attempts to answer a fundamental question:
Which real-world problems can benefit from quantum computation, at what scale, with what accuracy requirements, and under what hardware conditions?
To address this, the study adopts a structured methodology that connects:
- Algorithmic resource estimates (logical qubits, circuit depth, gate counts)
- Explicit error correction assumptions and overhead models
- Hardware roadmaps across multiple generations
- Timelines for when specific classes of problems may become feasible
Two representative domains anchor the analysis:
- Quantum chemistry, particularly excited-state dynamics and photochemical processes
- Topological data analysis (TDA), including graph-based structure and anomaly detection
These domains were selected because they combine industrial relevance with computational structures that scale poorly on classical systems but map naturally onto quantum approaches.
Quantum chemistry is closely tied to materials science, energy systems, and the development of sustainable technologies. TDA, by contrast, offers tools for understanding complex data structures in networks, finance, and large-scale systems—where identifying structure and anomalies is increasingly critical.
Together, they illustrate how quantum computing may create value across both deep scientific domains and high-impact data applications.
An important caveat is that the resulting roadmap assumes a widely-studied but inefficient error correcting code. As more error correcting codes come online, the resources required to run algorithms will shrink. That means that the timelines detailed in this work can be thought of as “worst case” scenarios, which adds to the value by setting out a clear limit.
A distinguishing feature of the work is its emphasis on implementation over abstraction. Rather than relying solely on theoretical models, the study explicitly constructs quantum circuits and executes them on Quantinuum’s Helios and H2 system.
Parallel Paths to Value
A notable insight from the study is that quantum value creation will not follow a single linear path.
Instead, two complementary regimes are expected to emerge:
- In quantum chemistry, the focus is on fault-tolerant, logical-qubit-based computation, where error correction is essential for scaling toward meaningful scientific and industrial outcomes.
- In TDA, value can emerge earlier, where partial quantum advantage may already support useful computational tasks without full error correction.
This dual-track structure is important: it shows that quantum computing is not a single “threshold technology,” but a spectrum of capabilities that unlock value at different stages of maturity.
The Vision for Quantum Industrialization
The framework ultimately supports a broader strategic vision: the evolution of Quantum AI Data Centers—hybrid infrastructures where quantum processors operate alongside AI and classical HPC systems.
For enterprises, the implication is clear: quantum computing readiness is no longer about speculation. It is about structured preparation, disciplined modeling, and early engagement with the full stack of capabilities that will define the next generation of computational infrastructure.
Every year, The IEEE International Conference on Quantum Computing and Engineering – or IEEE Quantum Week – brings together engineers, scientists, researchers, students, and others to learn about advancements in quantum computing. This year’s conference, from September 13th - 18th in Toronto, Canada, will focus on translating research into real-world impact through the convergence of generative AI, distributed quantum systems, and quantum software engineering.
Throughout IEEE Quantum Week, our quantum experts will be on-site to share insights on upgrades to our hardware, enhancements to our software stack, our path to error correction, and more.
Meet our team at Booth #501 and join the below sessions to discover how Quantinuum is forging the path to fault-tolerant quantum computing with our integrated full-stack.
Keynote with Quantinuum's CEO, Dr. Rajeeb Hazra
September 14th
5:00 – 6:30pm | 800 Hall G
Quantum computing has passed the point where error correction is theoretical. What comes next depends on systems that hold logical performance steady and do real work at scale. On September 14th, join Quantinuum’s CEO Dr. Rajeeb Hazra for his keynote session on “Logically Speaking: The Next Era of Error Correction” where he will explore what the next era of quantum computing requires: shared definitions of logical performance, and benchmarks built on real workloads.
Speaking Sessions
September 13th
11:00 – 11:12am | Location: 601A/B
Workshop: QGenAI: Synergies between Quantum Computing and Generative Artificial Intelligence
Finding Compatible Datasets for Quantum Generative Modeling
Presenting Author: Chen-Yu Liu
September 14th
1:00 – 1:20pm | Location: 701B
Workshop: Q3-Control: Integrated Systems for Quantum Computing, Sensing, and Networking
Cryo-ASICs for Scalable Control
Speaker: Dr. Patty Lee
September 15th
2:30 – 3:30pm | Exhibit Hall (informal event)
Workshop: Q3-Control: Integrated Systems for Quantum Computing, Sensing, and Networking
The Quantum Spectrum
Speaker: Dr. Patty Lee
3:00 – 4:30pm | Location: 801A
Where Quantum-HPC Integration Actually Stands in 2026
Panelist: Neal Erickson
3:00 – 4:30pm | Location: 718A
From Research to Commercialization: Defining the Quantum Workforce for the Next Five Years
Panelist: Kortny Rolston-Duce
September 16th
10:00 – 11:30am | Location: 801B
Who Will Turn Quantum Computing into Value? Specialists, Domain Experts, and the Workforce Gap
Panelist: Enrico Rinaldi
September 17th
10:00 – 11:30am | Location: 701B
International Workshop on Quantum Computing for Power Systems: From Optimization Algorithms to Grid-Scale Applications | Session 1
Organizer: Kortny Rolston-Duce
10:00 – 11:30am | Location: 714A
openQSE: Co-Designing the Quantum-HPC Software Stack from Applications to Control Systems | Session 1
Speaker: Neal Erickson
10:00 – 11:30am
The Impact of Qubit Connectivity on Quantum Advantage in Noisy IQP Circuits
Presenting Author: Leonardo Placidi
10:15 – 11:00 am | Location: 601A/B
Workshop: AI for Circuit Synthesis, Optimization, and Discovery
Automated near-term quantum algorithm discovery
Speaker: Konstantinos Meichanetzidis
11:00 – 11:15am | Location: 601A/B
Workshop: AI for Circuit Synthesis, Optimization, and Discovery
Fast Stabilizer State Preparation via AI-Optimized Graph Decimation
Presenting Author: Jasmine Brewer
1:00 – 1:15pm | Location: 601A/B
Workshop: AI for Circuit Synthesis, Optimization, and Discovery
Reinforcement Learning for Adaptive Composition of Quantum Circuit Optimisation Passes
Speaker: Gabriel Matos
1:00 – 1:20am | 718B
Quantum Software 2.6: current challenges and headways in quantum software | Session 1
Quantum compilation and hybrid compilation
Speaker: Ross Duncan
1:00 – 2:30pm | Location: 714A
openQSE: Co-Designing the Quantum-HPC Software Stack from Applications to Control Systems | Session 2
Speaker: Phillipp Seitz
1:45 – 2:00pm | Location: 601A/B
Workshop: AI for Circuit Synthesis, Optimization, and Discovery
Graph-Theoretic Quantum Circuit Optimization with the ZX-Calculus and Gumbel AlphaZero
Speaker: Alexander Koziell-Pipe
2:00 – 2:15pm | Location: 601A/B
Workshop: AI for Circuit Synthesis, Optimization, and Discovery
Reusable Equivariant Neural Compilers for Matrix-Group Quantum Circuit Synthesis
Speaker: Richie Yeung
3:30 - 4:00pm | Location: 715B
Workshop: 4th Workshop on Quantum Computing for Natural Sciences: Technology and Applications
Quantum Algorithms
Speaker: Setso Metodi
September 18th
10:00 – 11:30am | Location: 801B
Scalable QPU architectures
Panelist: Setso Metodi