Quantinuum Q3 2026 Earnings Call Transcript

Quantinuum (NASDAQ:QNT) reported third-quarter financial results on Thursday. The transcript from the company’s third-quarter earnings call has been provided below.

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Summary

Quantinuum reported third-quarter 2026 revenue of $9.1 million, marking a 233% increase year-over-year, driven by cloud platform strength and diversified customer base.

The company achieved world-record logical fidelity on its Helios system and progressed its roadmap with SOL on track for 2027 and Apollo for 2029, aiming for fully fault-tolerant quantum computing.

Quantinuum secured its largest cloud agreement with a leading financial institution and expanded partnerships with Oracle and other hyperscalers, highlighting increased commercial traction and ecosystem expansion.

Nexus platform saw a 20% increase in user organizations and significant job submission growth, with a roadmap to align with future hardware advancements.

Management expressed strong confidence in delivering 100% revenue growth in 2027, with a raised 2026 revenue outlook to $31-$34 million, fueled by robust bookings and a solid financial position with $1.9 billion in cash and no debt.

Full Transcript

OPERATOR

You will then hear an automated message advising your hand is raised to withdraw your question. Please press star 11 again. In the interest of time, we respectfully ask that each analyst limit themselves to one question. Please be advised that today’s conference is being recorded. I would now like to hand the conference over to your first speaker today, Shubh Mukherjee, Head of Investor Relations. Please go ahead.

Shubh Mukherjee (Head of Investor Relations)

Good afternoon and welcome to Quantinuum third quarter 2026 earnings call. With me today are Rajeeb Hazra, President and Chief Executive Officer, and Nitesh Sharan, Chief Financial Officer. Before we begin, I’ll cover the Safe Harbor Statement. Today’s remarks contain forward-looking statements within the meaning of the Private Securities Litigation Reform Act. These include statements about our technology roadmap, commercial expectations, and 2026 and 2027 outlook.

Actual results may differ materially. Please refer to the risk factors in our earnings release issued earlier today and our most recent Form 10-Q filed with the SEC. Statements speak only as of today and we undertake no obligation to update them. In addition, during today’s call we will be discussing certain non-GAAP financial measures. Please refer to our earnings release for additional information regarding these non-GAAP financial measures and reconciliations to the most directly comparable GAAP measures.

With that, Raj, over to you.

Rajeeb Hazra (President & Chief Executive Officer)

Thank you, Shubh, and good afternoon, everyone. Quantum computing, the largest market opportunity across all quantum technologies, is moving more rapidly from promise towards practical impact than it has ever in the past. And what we’re moving to, that opportunity is enormous and growing: discovering new medicines and materials, improving financial modeling, optimizing complex logistics networks, and, in general, finding solutions to many other problems that remain well beyond the reach of classical computers.

And so governments are making quantum a strategic priority and, most interestingly, enterprises are investing now in the expertise, partnerships, and applications needed to put quantum to work. As I said last quarter, the central question is who will lead the creation of this new era of computing. Our view of what it takes to lead, and a leader, is very clear. Leadership starts with building quantum hardware that can deliver accurate results at the speed customers need. Customers need to solve business problems, which means having answers that they can trust in a timely manner. Efficient, fault-tolerant quantum computing at scale is the foundation of that trust.

But having the best fault-tolerant quantum hardware alone is not enough. Leadership also means integrating quantum with classical computing and AI and giving developers the tools to build applications that solve real business problems. And that is what Quantinuum is building: a full-stack platform designed to deliver useful quantum computing at scale. Our third quarter marked significant progress across all three parts of that strategy. First, in product technologies, we achieved world-record logical fidelity on Helios, our commercial system, and significantly de-risked the hardware and error-correction capability that will be required to deliver universal, fully fault-tolerant quantum computing with our Apollo system in 2029. In the area of software, we announced a multi-generational Nexus roadmap designed to accelerate application development on today’s systems and enable those applications to scale well into the fault-tolerant era.

And perhaps most importantly in commercialization, we added new customers, deepened customer engagements, secured the largest cloud agreement in our history, and expanded access through major cloud and enterprise ecosystems. These are not three separate initiatives. Together these efforts position Quantinuum to accelerate commercial value creation before the end of this decade, delivering universal, fully fault-tolerant quantum computing by 2029 while building the software applications and the ecosystem customers need to use it today and in the future.

Let me take a few minutes to walk through the details of our progress this quarter. I’ll first focus on product technology and supply chain. The path to fault tolerance requires two things advancing together: accurate hardware, including an architecture that can scale qubits efficiently, and scalable error correction. We significantly advanced both in the third quarter. While not just advanced, we demonstrated results that illustrate our significant lead in fault-tolerant hardware over the rest of the industry.

More of this in a minute, but first let me do a quick update on our systems roadmap. SOL remains well on track for delivery in the second half of 2027, and given our step-by-step de-risking approach for these systems, we have greater confidence in its timeline today than we had for Helios at the same stage of development. For SOL, following the first traps returned from fabrication that I spoke about in the second quarter, in the third quarter we validated SOL’s entire control system for moving qubits in the two-dimensional trap at full product scale.

That demonstrated the control and movement of ions required to validate our QCCD architecture in SOL and machines beyond. Like Apollo, we are now in full system integration and assembly on SOL and on track to complete that in the first quarter of 2027. Next will come system validation and verification, including running real jobs before commercial availability in the second half of 2027 as planned. As promised, SOL is expected to be the world’s first commercial quantum system with hundred logical qubits, targeting a logical error rate of 10 to the power minus 5—that is approximately one error in 100,000 operations.

Apollo, our universal, fully fault-tolerant quantum computer, is progressing to plan through its design phases and remains solidly on track for 2029. Our teams are progressing through key subsystem designs, including validating our cryogenic cooling system, which is critical for a machine at Apollo scale. We are also building the supply chain we will need to scale production for Apollo and future machines with deep, long-standing partnerships with GlobalFoundries, Infineon, Honeywell Aerospace, Monarch Quantum, and others.

These partners bring deep expertise early into the design of critical components, helping us reduce complexity, improve reliability, and make production more repeatable. In September, we finalized our CHIPS R&D award following the previously announced letter of intent, which will help accelerate our supply chain efforts. Quantinuum was the only trapped-ion company selected for that award. Beyond the roadmap, as I had promised, I’ll get back to our industry-leading results in fault tolerance, which is very, very exciting not just for us but for the industry at large. In Q3 we introduced a scalable end-to-end logical architecture that brings together tailored AI decoders, all-to-all qubit connectivity, high-fidelity physical operations, and hardware-level error correction. These capabilities working together improve computational accuracy, providing the foundation for universal, fully fault-tolerant quantum computing.

Scale is essential for leadership. The end-to-end logical architecture flexibility also allows us to test, refine, and combine different error-correcting codes, balancing accuracy, efficiency, and speed for an increasingly larger set of diverse, demanding business applications. We have already implemented this logical architecture in Helios. In September and October, two different error-correction codes running on that architecture on Helios delivered back-to-back world records for logical fidelity.

October’s result reached 99.99995%, equivalent to five errors in a million operations. That error rate, just to put it in perspective, was 10 times lower than our own September record and 100 times lower than Google’s, which had published the previous best results amongst the various hardware modalities. Critically, these results point to significantly lower error rates with lower error-correction overhead. Each 2-step increase in the error-correction code distance reduced logical memory errors by a factor of approximately 12, compared with roughly 2 in Google’s published superconducting result.

This stronger error suppression means that we will need 30 times fewer physical qubits—yes, 30 times fewer physical qubits—to reach target logical error rates, reinforcing another significant scalability advantage of our trapped-ion modality and our QCCD architecture. Today we are very clearly leading in scaling accurate, high-fidelity computational power, and that underpins our confidence in delivering the world’s first universal, fully fault-tolerant quantum computer in 2029.

Next, let me move to software. Our Nexus platform had a very significant quarter of progress as well. Nexus is a platform-as-a-service that brings quantum application development and deployment into one environment and converts these hardware advances into capabilities customers can use to build meaningful applications and deploy them on hybrid quantum-classical infrastructure. Today, 215 organizations are building on Nexus, up nearly 20% from the 180 I had quoted last quarter.

More than just the number, total job submissions increased tenfold in the 12 months through August 2026 compared with the preceding 12-month period. Today we announced a significant advance for Nexus: a multi-generational roadmap to develop this platform into what we believe will be the industry’s first platform-as-a-service designed for the fault-tolerant era. It aligns software capabilities with each generation of hardware through Apollo and beyond, giving customers predictability for application development and deployment.

This is a fundamental aspect of accelerating the adoption of useful quantum computing. We are already delivering the foundations of that roadmap. Our September release of Nexus extended our Guppy programming language with tools for programming logical qubits and applying supported error-correction codes, including our own optimized codes and third-party codes, thereby reducing the need to rewrite application logic for each type of error-correction code. Developers can now test programs in emulation, execute supported programs on Helios, and customize their approach while benefiting from advances in error correction.

The upcoming December release will expand capability to deal with hybrid workflows, allowing applications that have both classical and quantum code to respond to quantum results as soon as they become available, thereby making the performance of the systems more efficient and more effective. It will also add supported error-correction codes and execution analytics to help developers optimize further the performance they get on our leading hardware.

As our hardware and software advance together, the applications, the workflows, the expertise customers build on Nexus will become invaluable. That gives them a compelling reason to build with Quantinuum today and carry that investment forward with Quantinuum into the fault-tolerant era. And last but not the least, let me talk about our progress with commercialization. We are adding new customers, developing applications around valuable customer problems, securing commitments across hardware generations, and expanding access through established cloud ecosystems. Let me give you just a few examples of new developments this quarter. Our work with Johnson & Johnson applies quantum computing and AI to the creation of new cancer therapy materials, with the potential to accelerate drug development and enable more effective treatments sooner.

With GE Vernova, we are advancing research into superconducting materials in order to build smaller, lighter, and more efficient electrical infrastructure. A new collaboration brings together Abu Dhabi Maritime Academy, part of the AD Ports Group, AI-powered logistics company Quincus, and Quantinuum to explore quantum, AI, and high-performance computing for complex maritime and logistics applications. We also signed our largest ever cloud agreement, a multi-year, multi-generational commitment from a leading global financial institution for access to our systems through Apollo using Nexus, supporting fault-tolerant applications development and deployment across multiple core business functions.

In addition to this, we are also expanding access to our infrastructure through cloud and enterprise environments that already serve millions of developers. Building on our announced partnership with Oracle last quarter, we are advancing commercialization of the hybrid quantum-plus-classical capabilities in the Oracle Cloud Infrastructure. We jointly launched a beta program for select customers to explore hybrid quantum and AI applications in the areas of defense, financial services, automotive, manufacturing, and general research.

We demonstrated our joint offering at Oracle AI World, and Helios’ deployment into the Oracle Cloud Infrastructure’s AI data center remains well on track for full deployment later next year. In addition, we also signed a new agreement with a leading hyperscaler serving millions of developers and enterprises worldwide. Bringing our hardware and software into that ecosystem significantly broadens our reach and is expected to accelerate the integration of quantum into existing AI, high-performance computing, and enterprise workflows.

Alongside this enterprise and cloud momentum, we are seeing continued government investment and strategic focus in the United States and internationally, benefiting Quantinuum. In the United States, we continue to progress through the DARPA Quantum Benchmarking Initiative, or the QBI Initiative. We are actively discussing a QBI Stage C scope of work with DARPA as we continue to execute on our Stage B contract. Separately, with the USG, we are participating in four winning university proposals in Phase One of the Department of Energy’s GENESIS mission.

These draw on our systems and expertise across algorithms and nuclear reaction design, quantum chemistry and new material creation, and AI-driven design of next-generation quantum processors. Beyond the United States, internationally, our second Helios system is on site in Singapore and is being assembled, with commissioning on track for next spring. Next week we are commissioning an upgraded computer at RIKEN in Japan as part of the world’s most advanced hybrid quantum supercomputing system of its kind.

We are also discussing potential deployments with several other governments at this stage. Together, these developments show how our commercial strategy is successfully accelerating the industry’s adoption of quantum computing—in particular, developing applications around customer needs, securing long-term commitments to our products and services, and building the distribution and deployment pathways that are needed for broader adoption and scaling. Lastly, on the ecosystem front, supporting our technological and commercial progress, we are growing the broader ecosystem around our full-stack platform.

First, we worked with Sandia National Laboratories and NVIDIA to introduce QOps, a new performance benchmark that gives customers a capability that they were lacking. That capability is a credible, repeatable way to assess the size of a useful computation a system can execute and how quickly it can execute it. We are building alignment amongst partners in the ecosystem and government stakeholders towards an industry standard around QOps that will help customers compare systems and make informed purchasing decisions.

Expediently, we are also growing the community that develops applications and brings new capabilities to our platform. We’ve now grown QNet, our community providing developers and researchers with resources to do more with our platform, to over 800 participants and added eight new startups to our Quantinuum Startup Partner Program. Finally, we are working closely with our government and commercial customers to grow the quantum ecosystem. A case in point is a Quantum Challenge we designed and ran in Singapore, supported by Singapore’s National Quantum Office.

Over 200 teams submitted proposals, and the winner will be announced later this month. These initiatives help build practical expertise and applications around our technology stack. These efforts reinforce one another. Clear benchmarks help customers evaluate systems, developer programs build expertise and applications, and public–private programs create pathways to adoption. Our third quarter execution increased our technology lead, with deeper customer commitments and expanding routes to market. We believe we are positioned to turn that leadership into momentum—into accelerated commercial growth—and further extend our industry leadership. Our momentum across technology and commercialization has been accelerating through the year, and as I look at 2027, I’m more confident of our opportunity and our ability to capitalize on it than I was when we spoke last quarter.

With that, over to Nitesh to take you through our financial results and outlook.

Nitesh Sharan, CFA (Chief Financial Officer)

Thank you, Raj, and good afternoon, everyone. Let me start by building off of Raj’s thoughts. Our goals were clear this year through the IPO. We shared an aggressive and credible plan grounded in reality. We are running ahead of that pace and our momentum is accelerating. We believe we have a multi-year technological lead versus the competition, and each new deal we close makes it harder for others to catch up. We don’t take that for granted. We are constantly on the offense while being measured about the risks.

Our investments are thoughtfully calibrated, designed to maintain and extend our lead through the engineering required to be the first fault tolerant to scale manufacturing with the diverse and proven supply chain, and to execute the go-to-market strategies that we expect will unlock the greatest value for customers. We are fueling this from a position of capital strength that sets the foundation for disruptive growth and outsized return, and that continues to translate into near-term financials that outpace even our own expectations.

Let me illustrate that in the Q3 results. Revenue for the third quarter was $9.1 million, up 233% from the prior year. Growth was driven primarily by strength in our cloud platform along with research and services. Revenue remained well diversified across customer types and geographies, with government representing the majority and enterprise also a significant contributor. Customer concentration also continued to improve in the quarter. Let me emphasize a point that is important to understand when contrasting our results with others in the quantum sector: every dollar of revenue we report is directly related to quantum computing.

As Raj noted, that is the grand prize we are focused on as the largest part of the quantum ecosystem, and it is what will catalyze the world-changing breakthroughs that we see on the horizon. Bookings are a forward indicator of future revenue. In the quarter, we recorded bookings of $98 million, including the Oracle deal we announced during the last earnings call. These deals were across government and enterprise and served several of our core industry verticals, notably financial services, chemicals, and pharma. Our 2026 year-to-date bookings now stand at approximately $104 million, and we expect to achieve more than $120 million in bookings over the full year, setting us up well entering 2027.

More on that when I get to the outlook. Moving to the cost structure, cost of sales were $3.2 million in the third quarter, including roughly $0.7 million of stock-based compensation. Non-GAAP gross margin, which excludes stock-based compensation and other non-cash charges, was 74.6%. The year-over-year improvement in gross margin this quarter was largely driven by revenue growth. This line will move with revenue from quarter to quarter and be heavily influenced by product mix. The gross margins this quarter reflect the heavy mix of cloud business.

Over time, we will increasingly emphasize design for cost and manufacturing for scale, and we have a great set of supply chain partners working closely with us on these objectives. Research and development expenses were $97.5 million, including $27 million of stock-based compensation, up from $42.4 million a year ago. We are investing in every level of the technology stack: our leading quantum hardware, the Nexis, developer platforms, and in end-user applications. These capabilities amplify one another and are increasingly fueled by direct customer engagement, providing direct clarity towards unlocking end-user value. Sales and marketing expenses were $14.9 million, compared with $4 million in the prior-year period, and included roughly $4 million of stock-based compensation.

We are building our government, commercial, and consulting direct sales engines. Our indirect channel partners will enable us to further leverage this line item to capture more of the market, and we are enabling all of that through targeted, high-ROI marketing spend across brand development, demand generation, and lead execution. General and administrative expenses were $22.1 million, compared with $5.3 million in the prior-year period, and included $5.5 million of stock-based compensation.

The increase reflects the investments required to operate as a public company, including finance, legal, compliance, and operations. We continue to invest in our controls infrastructure from the foundational IT to modern applications that improve overall process and administration. In total, stock-based compensation was $37.2 million in the quarter. Adjusted EBITDA, which excludes stock-based compensation, depreciation and amortization, and other one-time and non-cash items, was a loss of $80.5 million, compared with the loss of $45.3 million in the prior-year period. As a reminder, at the GAAP net income level, we separate the economics attributable to legacy shareholders who have not yet exchanged their shares into the post-IPO public entity as non-controlling interest. Our total GAAP net loss for the third quarter was $117.9 million.

Of that, the net loss attributable to Quantinuum Inc. was $17 million, or a $0.46 net loss per share. On an adjusted basis, non-GAAP net loss was $75.2 million, and non-GAAP EPS was a loss of $0.29 per share. These measures are calculated across our full shareholder base, and they exclude stock-based compensation, depreciation and amortization, and other one-time and non-cash items. Turning to the balance sheet, we ended the quarter with over $1.9 billion in cash and equivalents, with no debt. We have a strong balance sheet with what we believe is more than sufficient cash to fund our technology roadmap and invest in the critical capabilities that we expect to fuel the path to profitability. Maintaining a strong balance sheet is a critical priority for us and a source of strength.

Before turning to guidance, let me describe the accounting related to one of our big wins in the quarter, the CHIPS award. As we noted, we were awarded $100 million from the Department of Commerce to help develop the U.S. quantum ecosystem. As part of the structure of the deal, the U.S. government received roughly 2 million shares and provides cash in milestones, with the majority up front. This deal is characterized as an equity contract and accordingly does not affect the P&L. As of Q3, the cash did not impact the cash and equivalents line on the balance sheet, and its direct effect on the balance sheet will vary quarter to quarter. Overall, just note that this is an incremental investment to fund our pathway to fault tolerance, providing incremental capital protection and diversity of funding sources that may not be fully reflected on the cash line.

Turning now to our outlook, our execution velocity and commercial momentum have picked up through the year, and this gives us higher conviction in our near-term revenue. We are raising our full-year 2026 revenue outlook to $31 to $34 million, from $28 to $32 million previously. It also makes us more bullish on 2027. Based on our current bookings and backlog and our assumptions around contract timing and revenue recognition, we continue to expect revenue growth of more than 100% in 2027.

That growth now builds off of a higher 2026 pace. To put it simply, our expectations for both 2026 and 2027 are higher today than they were just last quarter. In closing, our momentum is clear. Given our early-stage nature, things will not move linearly. Each quarter will have its own unique element, but we expect the longer-term trajectory is exponentially upward. The technology leadership Raj described is converting into commercial traction, and that traction is showing up in our financial results. With accelerating momentum, we believe we are building a diversified business with an attractive long-term financial profile that we expect to deliver sustained growth, profitability, and high returns.

With that, we’ll now open it up for Q&A.

OPERATOR

Thank you. At this time we will conduct the question-and-answer session. As a reminder, to ask a question, you will need to press star-1-1 on your telephone and wait for your name to be announced. To withdraw your question, please press star-1-1 again. We respectfully ask that each analyst limit themselves to one question. Please stand by. Our first question comes from Krish Sankar from TD Cowen. Please go ahead.

Krish Sankar (Analyst)

Thanks for taking my question, and congratulations. Rajeeb, Nitesh, the calendar ’26 outlook improvement from three months ago — just wondering what drove it. Is it cloud, enterprise, government, R&D? Is it within the U.S., overseas? Any specific industries? And just extrapolating it onto the 2027 revenue growth of 100% off a higher base, what kind of specific verticals are driving the growth in 2027? Thank you very much.

Nitesh Sharan, CFA (Chief Financial Officer)

Sure. Thanks for your question, Krish. On the 2026 raise, it really is broad-based. You know, we are seeing great progress on the cloud business. We’re seeing it across governments, not just in the U.S. but across the world, and in enterprises across some of the verticals we highlighted in the prepared remarks. And as you go forward into 2027, certainly we were excited last time to raise that outlook as well. Talked about a significant deal with Oracle that we’re excited about — that has some revenue characteristics that gives us conviction.

But we also this time announced some other deals, another hyperscaler in the mix, some other enterprise deals. So quite frankly, our momentum is broad-based. It’s across governments, it’s across national labs, it’s across universities, it’s across enterprises, it’s in the U.S., it’s in Europe, it’s in Asia. And I think more importantly is that the traction — which over time you’ll see in GAAP revenue — but it’s really the engagement, the levels of, you know, both in developer ecosystem but end-user customers, the algorithms they’re working on, the advancements obviously we talked about on the tech roadmap — that is resonating with customers.

And our sales team and the pipeline that they’re building, we are seeing it across all of the pieces. And so that’s why we had enough conviction, with still in our view a reasonable amount of conservatism and prudence in our planning, that we would be able to raise 2026 and also give you an early view of an increase in 2027.

Krish Sankar (Analyst)

Thanks, Nitesh.

OPERATOR

Thank you. Our next question comes from Vivek Arya from BofA Securities. Your line is open.

William Paul (Analyst)

Hi, thank you. This is William Paul on for Vivek. Thank you for taking our questions. I wanted to start just on the error-correction side. You said the October result, meaning you need about 30 times fewer physical qubits to hit your target logical error rates. Could you discuss how that changes how you design Apollo and Lumos, and particularly how we should think about Lumos in terms of size and that logical qubit count longer term? Thank you.

Rajeeb Hazra (President & Chief Executive Officer)

Thanks for the question, Vivek. So as you stated, you know, there were two really big things we announced in the error correction. One was reaching that absolute five errors in a million operations. But the second big thing was the error correction efficiency where we achieved an exponential reduction in error correction for a reasonably small amount of increase in the number of physical qubits that are used to create a logical qubit. And that comes from the architecture that we have, our modality, and the very strong all-to-all connectivity that we support in our particular implementation of two-dimensional QCCD.

As we think of that going forward, there are two things. One is obviously these results, even achieved on Helios with a universal gate set, give us very high confidence that as we move to SOL and Apollo and the physical qubits themselves get better, we are in very good de-risked shape to achieve Apollo’s targets that we put forth and achieve them at full fault tolerance across all operations of the universal gate sets. We have not made public yet the logical specs on Lumos, but what we expect is that Lumos will continue the physical qubit improvements to some extent, but most importantly aggressively adopt these error correction techniques that we have now proven are scalable from the scale of Helios to a million-plus qubit machine, that we will effectively continue to run that exponential and therefore deliver essentially the best error rates in the industry for the smallest amount of system size.

And that is very important from a reliability standpoint, cost standpoint, and simply manageability standpoint of these systems.

Vivek Arya (Analyst)

Thank you. And then on your largest ever cloud deal, the multi-generation commitment through Apollo, what’s driving customers to sign multi-year commitments before fault tolerance arrives? How is their spend trending, what kind of conversations you’re having with them? And are they moving from research and exploration projects into production use cases?

Rajeeb Hazra (President & Chief Executive Officer)

Great question. There’s really two drivers. One is being engaged early, actually having a use case roadmap that tells them what can be achieved with what portions of unlock from machines like H2 Helios, SOL, and Apollo. So the first thing is conviction that their business-relevant use cases can grow. The second is the predictability of our roadmap now and the confidence that if they invest in technologies or application building in, say, the SOL timeframe, that that carries forward in a timely manner to a machine called Apollo, which isn’t maybe at some point, but it’s definitely in 2029.

The nature of our conversations: very clearly, as you see these kinds of deals that we are seeing both extend in time, expand in size of dollars, and extend over multiple generations. That came from the early engagement, which was kind of more proof of concept, to now it is almost pre-building of the application that in some cases will unlock at SOL at a full production scale or Apollo. But that path of getting ready, so there is not a delay between when the technology is available and when the applications are deriving business value, that gap is minimized.

So we are very much from the age of kind of discovery to the age of acceleration when it comes to these kinds of commercial customers and their applications.

Nitesh Sharan, CFA (Chief Financial Officer)

And just to add one thing to the tail end of what you asked, in this particular case that you asked about, there is an expansion of what they’re spending with us, and actually we’re seeing that across a number of customers as well because of the value that Raj just articulated.

OPERATOR

Thank you. Thank you. Our next question comes from John McPeek from Rosenblatt Securities. Your line is open.

John McPeek (Analyst)

Hey guys, congratulations on the progress here. Question is the same question I had last call. Actually, I’ll ask it again. Since one quarter has passed, the de-risk since the last call relative to the transition from SOL to what’s likely the first fault tolerant machine, Apollo, maybe you could just give me the key points there. What you’ve accomplished, because you know, you did the crossing with Helios and now you have the chip, I guess, running and you’re crossing ions in the trap.

So just anything there would be great. And then I just have one follow-up.

Rajeeb Hazra (President & Chief Executive Officer)

Sure, maybe I can answer that. And even though you asked the same question, I will give you a different answer and a better answer this time because we have advanced. We have advanced, and what we have done is, last time I told you that SOL is the building block for Apollo. Why? Because it’s the same two-dimensional QCCD. SOL chip came back, and the big thing in SOL, in Helios we had one crossing, so you had to manage only one pair of qubits crossing each other.

Of course, in SOL, with 198 qubits, we have near 100 pairs of qubits to actually move around the chip and pipeline them. And that’s a complex control system, but it is the heart of what makes a 2D trap for SOL and Apollo work, and that we have proved in real silicon at the 198‑qubit scale and then simulated it beyond to give us confidence that the basic heart of SOL’s qubit transport system, which is essential to moving qubits, giving them values, gating them, and reading them and even cooling them, is functional.

So that is one of the things that, while it’s proven on SOL and de-risks SOL, we carry that forward into Apollo. The other two things that we have made advance on Apollo is actually, one is the cryogenic system. Because at the scale that Apollo is, you have to ensure that that system is balanced to the load and the larger chip that Apollo is. The second thing is, of course, advances in what we call the laser optics system because Apollo carries more qubits.

Even though you can move the qubits around, as we’ve proven with SOL and Apollo, the ability to actually show that you can have beam formation, beam delivery, and, working with our partners like Monarch Quantum, prototyping those to us, then being able to say, yes, we can see SOL working in 2027, and by 2027, 2028, we would have de-risked our path significantly through proven subsystems into Apollo, which then we integrate. That has been our strategy: prove out the most critical subsystems first in emulation, then in silicon, test silicon and prototype, and then build them and integrate it and build the whole system together with far less risk than waiting for everything to come together at the end.

John McPeek (Analyst)

Excellent. And then with the recent novel error correction that you’re using, triangular error correction, and the results that you’re getting there, is there potentially upward pressure on the logical error rates, because of the physics, on the logical error rates in SOL, Apollo, and Lumos?

Rajeeb Hazra (President & Chief Executive Officer)

Actually, with the error correction results that we have shown on Helios, which is 5 errors in a million operations, which is 5 times 10 to the power minus 6, we have de-risked the error rate because with Helios and 96 qubits, we have been able to show that all elements of the magic state factory and some of the ancillary and some of what we call coding overhead is easily managed to deliver that error rate. And now in SOL we have two. One is we have more physical qubits and so more resources.

And number two is SOL’s physical qubits themselves are better. That gives us a significant boost in being able to do more error correction per round than we’ve even been able to do on Helios, which is about six times better than the published result on any other modality. Does that make sense, John?

John McPeek (Analyst)

It makes sense. You know, when I say upward pressure, I guess it’s upward pressure on fidelity is really what I meant, not on error rates. And then the final one is, you know, what I think some of other modalities are struggling with is the non-Clifford gates and the distillation, magic states and all that, and the overhead that’s required. So you guys are going to give us at some point soon, I think, some information on non-Cliffords and universal gates, I guess.

Right? With the new error correction codes.

Rajeeb Hazra (President & Chief Executive Officer)

Absolutely. In fact, I want to be very clear. We have already, and we were the first, to demonstrate a universal gate set. So our results are universal gate sets and a distribution of non-Clifford gates along with Clifford gates. We define universal full fault tolerance as what we need for the era of full fault tolerance. So it’s not about just doing the Clifford gates and not the non-Clifford gates. So that is already in our results. If you look, then if you’re trying to compare, for instance, where our magic state or some of the components of end-to-end error correction are, we have results—in fact we published it in 2025—where we have slightly better results than what Google published, which was their 40x reduction in magic state errors with a significantly higher acceptance rate. And what I mean by that is the way you do magic state distillation or cultivation is you have to try over and over and over again, and sometimes they work and sometimes they don’t work.

And so the acceptance rate is how accurately you’re doing the magic states versus doing them and throwing them away, and then only keeping the good magic states. And what that practically means is if your acceptance rate is high, then you’re using the physical qubit resources very efficiently, and you’re also cutting down the time required to get these magic states built. So all in all, we enjoy this end-to-end logical error rate advantage due to a number of factors, one of which is best-in-class magic state fidelity and magic state utilization. If you think of it as space-time utilization, which is really how well we can scale as we get to larger qubit counts.

John McPeek (Analyst)

Great. I’m really looking forward to SOL and Apollo. Thanks guys.

Rajeeb Hazra (President & Chief Executive Officer)

Thank you.

OPERATOR

Thank you. Our next question comes from David Vogt from UBS. Your line is open.

David Vogt (Analyst)

Great. Thanks guys for taking my question. Maybe Raj, I just wanted to follow up on John’s question regarding the Apollo roadmap. You know, appreciate all the color on SOL, where we’re going to be from a validation and a commercial availability perspective next year, but can you help us understand, from a simulation, from an emulation to silicon emulation roadmap, what other sort of subsystem designs or what other roadmaps should we be paying attention to as we move forward with Apollo outside of sort of the build-out of the supply chain in terms of tracking the progress?

You know, obviously I know SOL is critical next year, but just want to keep an eye on what else is being focused on from a subsystem perspective for Apollo as you go to a fault tolerance solution. And then I have a follow up.

Rajeeb Hazra (President & Chief Executive Officer)

Absolutely. The first major subsystem, as you see Apollo being a larger version of Sol, is the transport subsystem that we’ve completely now validated at scale. It is important to get that right. Why does scale matter? Because all of the pipelining and therefore the functioning, the time-based performance of the chip, the speed of the chip, depends on very efficiently being able to move these qubits, not just being able to move them. So the first subsystem is the transport subsystem.

The second subsystem, as I mentioned, was essentially the laser, the optic subsystems that then interact with the qubits on the chip that are controlled electrically in their movement. And we made significant progress along with our supply chain partner, Monarch Quantum, that we’ve been engaged with for now over two years, in building out what we call the beam delivery and the beam concentration and the beam localization capabilities so that you can actually have those moving qubits being brought to the computational zones, which are many more in Apollo than in Sol, and being able to accurately use them to give us the kind of fidelity that we enjoy today in Helios and see moving forward in Sol and Apollo.

Third is the cryogenic system. Again, we don’t need cryogenics to actually manufacture qubits like superconducting folks do. We need the cryogenics, which is, I would say, gentler cryogenics, in order to create a good vacuum. But at Sol scale and then at Apollo scale, it’s important that we have a very efficient cryogenic system which is not just a technical matter, but it’s also a closed loop so that it does self-recovery of the cryogenic material, which is helium, and that impacts the practical TCO of the machine.

So a percentage of gain in the actual end-to-end round-trip recovery does impact the TCO and the operating cost of the machine. So we made great progress there as well. We’ve been kind of focused on the hardware, but the next big piece is the infrastructure software stack, Nexus. So in Apollo, the Nexus roadmap is one where developers are not going to have to think of error correction as something that is their responsibility. The Nexus capabilities mapped to Apollo will be able to use Apollo’s hardware and offer developers who bring in just their application a choice of error correction codes that they can link in like a library.

And in some cases, if they don’t know which ones, the machine will actually, using some level of machine intelligence and understanding the application, suggest what may be the best error correction code to use for that application and the resources it needs. So a very sophisticated environment in software that aids developer productivity and effectiveness, enabled by very high-performance, fully fault-tolerant quantum hardware.

Nitesh Sharan, CFA (Chief Financial Officer)

Yeah, maybe I’ll make two points. One is that we’re seeing some of that commercialization happening now. In fact, some of the contracts that we have actually have a graduation of how people will have their journey going forward. And I think to an earlier question Raj talked about, a lot of these customers that we talk about continuing with us, upsizing their contracts, renewing. Oftentimes there’s a long journey of algorithmic development, how these use cases will build and build upon one another.

So it’s actually in our pipeline. It goes further out beyond Sol and to Apollo as well. So I think you’re certainly going to see greater emphasis on that as we go through next year in terms of the opportunity. But I think if, underpinning one of your questions, how does this model play out over several years? We’re very early in this opportunity and we do see the market growing substantially, especially when you get to fault tolerance. And the opportunity in terms of the value of these systems grows step function. And so that’ll be catalyzed in our revenue and our bookings. And ultimately we’re talking getting towards this billions of dollars of opportunity in the not too long horizon, capturing a meaningful part of the market.

Because again, our focus is quantum computing. We are leading, we think we have a multi-year lead against competition. The engagements we’re having with enterprises, governments, universities and so forth is showing that back to us that we’re doing the right thing. We’re trying to make our systems more readily accessible to folks. And that’s happening not only through the hardware side, but also through the Nexus side as Raj has talked about. So we do think all of this leads to, ultimately, we’re in hypergrowth mode and the numbers that we’re laying out for the near term, the next 12 months and so forth, will move to exponential growth as you get into the latter part of this decade and we start to move from Helios to Sol to Apollo and to LUMOS.

OPERATOR

Thank you. As a reminder, we ask that each analyst limit themselves to one question in the interest of time. Thank you. Our next question comes from Joe Moore from Morgan Stanley. Please go ahead.

Joe Moore (Analyst)

Great, thank you. I wanted to ask about the DARPA Stage C. You talked about the progress that you’re making there. I guess to the extent that some others did pass through Stage C, just wanted to give you a chance to address if that means anything, and certainly we’re confident that you’re in a strong position. And I guess, to the extent Stage C is about whether the system can be built and operated as designed, what key pieces of LUMOS do you need to demonstrate to get there?

Thank you.

Rajeeb Hazra (President & Chief Executive Officer)

Hi Joe, thanks for the question. Just the fact, what DARPA has said is Stage C is a phased set of awards depending on which companies were in their Stage C commitments and delivery. We continue to work with finishing up on our Stage B and are in active discussions with DARPA on our Stage C scope of work. We see the DARPA as an important kind of validation confidence builder. But we are also engaged very deeply, as Nitesh talked about and I talked about, with enterprise customers. Our view of what these systems need to be, what error rates they need to reach, what scale they need to reach and how we build them is built partly on the conviction of our own technology view and partly on the conviction that our customers say these are the right kinds of systems, these are the right kinds of system capabilities.

So we’re moving down with Apollo and LUMOS on our roadmap very confidently as we de-risk critical components of that fully fault-tolerant computing stack and, in parallel, continue to work to finalize our Stage C scope of work based on this particular de-risked, highly credible roadmap that we put forward for the industry.

Joe Moore (Analyst)

Thank you.

OPERATOR

Thank you. Our next question comes from Mark Moerdler from Bernstein. Please go ahead.

Mark Moerdler (Analyst)

Thank you very much for taking my question. Congratulations on all the progress you’re making. It’s really quite impressive. I’d like to switch gears a little bit and talk about the hyperscaler partnership you have, and likely maybe you’ll get more of these going forward. I’d like to understand some more on the economics of this. Who’s selling the usage? How is it being monetized? Are they reselling just the compute or the software platform? Is it consumption agreements, or are they paying something up front?

Any color you can give so that we can get a better understanding as this scales of what the opportunity and monetization is, and what the use cases they’re using it for. Thank you.

Nitesh Sharan, CFA (Chief Financial Officer)

Thanks, Mark. I’ll start and then Raj can add on. I mean, so first, yeah, we’re excited to have continued growth, both direct customer activity but also through these channel partners, excited last time to disclose Oracle and then excited now to talk about hyperscaler. And to your point, yeah, there’s a lot of opportunity for us. What’s most important is that the arrangement is a strategic one, that we’re providing customers with differentiated service.

So ultimately for us it’s a go-to-market access play. We are providing the full stack capability. We talked last time about how Oracle were actually the first to put a quantum system in a data center and it’s going to be natively built up, integrated and so forth. Here it’s not exactly that construct, but it is another one where we’re able to have joint go-to-market. The revenue model is, openly, we’re still working through some pieces, but there is ultimately that, if you have an end customer of the hyperscaler that wants access to the best breed of quantum system out there, they can access our systems and then we will obviously accrete the revenue associated with that.

Rajeeb Hazra (President & Chief Executive Officer)

Yeah, the only thing I’d add, Mark, is the hyperscaler models are different depending on how the integration happens, and we provide the flexibility through our software stack and our business model to be able to do that. But in the Oracle case, as we said, Oracle bought the system and our full stack along with it, monetizing it. We may have future opportunities to build on top of that as we bring additional customers in. In other cases, we are a full stack—think of it as a full stack capability within that—and we get paid for the value we unlock for customers that are already on that hyperscaler or come to that. The key point is twofold. One is we are seeing an increasing number of end customers already on the public cloud wanting to integrate AI, HPC, and quantum workloads, which is what’s driving these hyperscalers to look aggressively at incorporating the QPU along with the GPU and the CPU in the data center.

And number two is we are monetizing our full stack: the hardware, our Nexus layer, our value-added libraries and applications in chemistry, and not just commoditizing the hardware in these kinds of partnerships with our hyperscalers. Thanks, Mark.

Mark Moerdler (Analyst)

Extremely helpful. Thank you.

OPERATOR

Thank you. Our next question comes from Vijay Rakesh from Mizuho. Please go ahead.

Rafael (Analyst)

Hi Raj and Nitesh, this is Rafael covering for Vijay. Congratulations on the strong results. And I was wondering, how many of those organizations that you have on Nexus could become on-premises clients over time, and is there something specific that will drive their conversion from cloud to on-prem? Is there some usage level or maybe customer size?

Rajeeb Hazra (President & Chief Executive Officer)

Yeah, it’s a great question. I mean, the first thing is, you know, when customers get on Nexus it’s a highly sticky environment because you’re choosing the programming language, you’re binding your applications to specific libraries, and it’s a very sticky environment that then you want transportable, whether you want it in a private cloud or you want it on a public cloud. And the private cloud is the on‑premise cloud. Right. So we have architected our full stack to be able to do that.

The organizations, we have about 215 organizations today on Nexus, and a large majority of them are using the hardware in the Quantinuum cloud as we move forward, but some of them are already on a private cloud. For instance, we have Singapore as a customer, Japan as a customer, that are actually using a private cloud and Nexus on their private cloud where they have the hardware on their premises. As we move forward, what I see is how the world played out for enterprise workloads. You will see some of the workloads and some portion of the workflows happen in the public cloud, but some stay on the private cloud for data governance, data security, and simple economics of moving large amounts of data back and forth. And we have customers across all of those segments, which is why we have a good set of inputs as to how to create a flexible architecture that essentially says we meet you where you need the service.

Nitesh Sharan, CFA (Chief Financial Officer)

A good amount is covered. I won’t give you too precise an answer, but I’ll just say that we are feeling like we’re in a really good position. Obviously there’s still details that play out of when actually revenue plays through, but the line of sight we have including the existing backlog gives us a fair amount of confidence that we can deliver at least 100% next year. And Oracle is important, but there are definitely other deals. We talked about a few of them in the earnings call this time.

So it’s broad‑based. I think I answered an earlier question about our revenue is really a nice composite of governments across the world, national labs, universities, and enterprises across industries. And our bookings‑to‑revenue profile for next year reflects that diversity as well.

OPERATOR

Thank you. Our next question comes from Quinn Bolton from Needham and Company. Please go ahead.

Shady Milwaukee (Analyst)

Hey guys, this is Shady Milwaukee for Quinn. Thanks for taking the question. I guess on the agreement with J&J. I know in the past you guys have talked about outcome‑based IP being a potential revenue stream, so was just curious to hear if that’s something that can come out of this agreement. Thank you.

Rajeeb Hazra (President & Chief Executive Officer)

Yeah, we see it certainly monetizing our full stack. So we are working with some chemistry customers. For instance, I’ll give you one example where we have IP around a workflow to deal with metal‑organic frameworks, which can be used for anything from carbon sequestration to creation of drug delivery elements. That’s an IP we own and that we are actually actively monetizing in a couple of the engagements we have with pharma customers. So that is very much still a way these services get delivered for end users into solutions.

And we see that as a value add for us going forward.

Shady Milwaukee (Analyst)

Great, thank you. Congrats on the results.

Rajeeb Hazra (President & Chief Executive Officer)

Thank you.

OPERATOR

Thank you. Our next question comes from Troy Jensen from Cantor Fitzgerald. Your line is open.

Troy Jensen (Analyst)

Hey gentlemen. Congrats on the results. I’m sorry I jumped on a little late here, but I guess a question for Raj. With the balance sheet you have right now, just the thoughts of acquisitions, software, and I guess ultimately I want to know if multimodality is something that Quantinuum would ever pursue or is it always going to be just trapped ions. Thank you.

Rajeeb Hazra (President & Chief Executive Officer)

Great question. It would be kind of getting into speculation at this point and I don’t want to do that. What I will simply state is, number one, we have great confidence in the modality path we’ve chosen and our delivery just demonstrates further confidence. In the way we are acting on the software spaces, we look at a gamut of possibilities from deep partnerships to enabling folks on Nexus, collaborations on standards and benchmarks. And with the balance sheet we have and our position, we are always actively looking at what’s the best way to propel our business and deepen our moats.

And we will continue to be good stewards of that capital and use it for those purposes to drive our business forward and accelerate where necessary.

Troy Jensen (Analyst)

Okay, and just maybe a follow‑up, I guess, on your thoughts on trapped ions. Do you think that’s the time‑to‑solution and time‑to‑cost winner for all applications, or does it cover most of the applications? I’m just kind of curious. I always thought that there could be different modalities that are good for different applications, but I’d just love to hear your thoughts on that.

Rajeeb Hazra (President & Chief Executive Officer)

Yeah, I’m glad you used the word time to solution, because time to solution incorporates not only the speed of the computer, but the accuracy of the computer as well, because there’s no point calculating the wrong answer quickly. As we look at our lead in fault tolerance, for instance, and being able to generate with fewer qubits and fewer rounds of error correction the entire chain of correction, we actually see time to solution being in favor of those modalities, including trapped‑ion modalities and us, that actually have the highest fidelity.

And fidelity being more important in order to deliver an effective, real, usable answer, of course within the time‑to‑solution bounds that that answer needs. And so we actually look at our approach on building fidelity and building the best fidelities and then innovating to cut that down to as fast as we can deliver that fidelity in terms of execution speed as the right way to meet our customers’ workloads and use cases that they want from us.

Troy Jensen (Analyst)

Understood. All right, thank you and congrats going forward. Good luck going forward.

Rajeeb Hazra (President & Chief Executive Officer)

Thanks again.

Shubh Mukherjee (Head of Investor Relations)

Thanks, Troy, and operator. I think it’s sensitive to time. We’ll take one final question.

OPERATOR

Okay, thank you. Please stand by. Our last question comes from Tyler Anderson from Craig‑Hallum Capital Group. Please go ahead.

Tyler Anderson (Analyst)

Hi, this is Tyler Anderson on for Craig‑Hallum. Thank you for taking my question. I was hoping I was going to make the cut. So I was reading your work on the error correction codes, and to me this seems like something that can be used to separate out whether it be a magic state factory or just something to create T gates, such that that area requires much less resources than what would be otherwise, and then have a separate area for, let’s just say, the logical or the logic compute of the system.

And I’m wondering to what degree does that free open logical qubits for you and enable you to calculate with greater depth and a faster time to solution.

Rajeeb Hazra (President & Chief Executive Officer)

So if I understood your question correctly, Tyler, thank you for asking it. What I’ll tell you is, if you want to build a universal fault‑tolerant quantum computer, you’re going to have to have magic state distillation or at least magic state cultivation to a certain extent. What is critical is that the magic state output is high fidelity. But also, because magic states are built, or magic state factories depend on the number of magic states you may have to inject and how effectively you can build them, we actually stand with a very distinct advantage because we can build those magic states using far fewer physical qubit resources than anybody else can, because of the improved physical qubits we have, the all‑to‑all connectivity, and our ability to be more efficient, therefore in a higher acceptance rate.

So when we look at a full logical computation which has a universal gate set, we are already lower in the number of magic state resources that we need, and I just told you why. And so therefore, what we see is not complicating the developer’s life by giving them two completely separate paths, because we are already generating the world’s best leading logical error rates and have a path forward on continuing to do that without running into a wall.

Tyler Anderson (Analyst)

Okay, that makes sense. And I agree with the trying to abstract away for end users. I think that’s very important. That’s all for me. Thank you.

Rajeeb Hazra (President & Chief Executive Officer)

Thanks again, Tyler.

OPERATOR

Thank you. This concludes the question and answer session. Thank you for your participation in today’s conference. This does conclude the program and you may now disconnect.

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