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Good morning, and welcome to the D-Wave first quarter 2026 earnings call. I would now like to turn the conference over to Kevin Hunt, Investor Relations. Please go ahead.

Thank you, good morning. With me today are Dr. Alan Baratz, our Chief Executive Officer, and John Markovich, our Chief Financial Officer. Before we begin, I would like to remind everyone that this call will contain forward-looking statements, which are subject to risks and uncertainties and should be considered in conjunction with cautionary statements contained in our earnings release and the company's most recent periodic SEC reports. Both an on-demand webcast and a transcript of the conference call will be available on the investor relations section of the website within 48 hours after the call. During today's call, management will provide certain information that will constitute non-GAAP financial measures under SEC rules, such as adjusted EBITDA loss and non-GAAP adjusted operating expenses and operating metrics such as bookings.

Reconciliations to GAAP financial measures and certain additional information are also included in today's earnings release, which is available in our investor relations section of our company website at ir.dwavequantum.com. This morning, we will be limited to taking 1 question from each analyst during the first round of questions and then, time permitting, proceed to a second round of questions where again, we will have to limit each analyst to 2 just to 1 question. I'll now hand over the call to Alan.

Good morning, everyone, and thank you for joining us. I want to begin by sharing a few perspectives on the quantum computing landscape. As Linus Torvalds, the creator of Linux, once said, "Talk is cheap. Show me the code." That idea feels especially relevant in quantum computing today as excitement rises, competition increases, and investors are looking for proof, not just promise. As quantum computing attracts increasing investor attention, the sector is generating significant excitement but also significant noise. New entrants, new public listings, and ambitious, and some might argue, very overstated technology and product claims are drawing attention. In this environment, it is more important than ever to distinguish hype from execution. As the field grows more crowded, the conversation is shifting from who is participating to who is positioned to deliver. Customers are looking for technology that can give them a competitive edge today.

Researchers want cutting-edge tools that can accelerate discoveries now. Investors are working diligently to separate signal from noise in a sector that can sometimes generate more headlines than evidence or results. As the CEO of one of the world's first and leading quantum computing companies, I believe that it is important to help educate the market on the realities of quantum computing's true near-term capabilities and commercial traction, as well as the strengths and trade-offs of the different quantum computing modalities as this market continues to take shape. Let me be direct. Many still view D-Wave through an outdated lens, but I think it's time for a vision check. We believe we are the clear leader in quantum computing today, a market that Boston Consulting Group, BCG, projects to be in excess of $800 billion.

A full one-quarter of that market is optimization, which is uniquely addressed by annealing quantum computing, where we are the only player. This is not a niche technology or market, as some like to characterize it. It is estimated by BCG to be a whopping $100 billion-$220 billion opportunity. For comparison, that's as big as either the global semiconductor equipment market or the global cybersecurity market. For those who say that D-Wave is addressing a niche market, stop spreading competitive misinformation and start doing your homework. Do you think that the global semiconductor equipment and cybersecurity markets are niche? I don't. What's more, D-Wave is now also a leading player in gate model quantum computing through our acquisition of Quantum Circuits in January of this year.

This means that we are the only company in the world that can participate in the full addressable market for quantum computing with both annealing and gate model quantum computers. We are building a highly differentiated pure-play quantum computing company with proven commercial traction today. For those valuing us on only our annealing technology and products, I would say you're off by a factor of 2. Our unique market position reflects our rapidly advancing gate model progress, which has greatly accelerated given Quantum Circuits Inc. industry-first dual-rail qubit technology. It is imperative that you all understand the profound potential that this has on our business and ensure that the models you're using to evaluate the company take into account this newly acquired technology.

With dual-rail qubits built-in error detection, we believe that our gate model quantum computing systems will set a new standard on quantum performance, efficiency, and scalability. Our dual-rail gate model technology is a meaningful differentiator for D-Wave and, in our view, one of the most important developments in quantum computing today. It brings together superconducting speed, the fidelity associated with ion traps and neutral atoms, and a clear path to scale with our proprietary on-chip cryogenic control technology, a combination that the market should be paying much closer attention to. This combination is a revolutionary approach to the development of a gate model quantum computer. Trapped ions or neutral atoms are like a bicycle. They're simple, reliable, and efficient, but very slow. Superconducting is like a piston propeller airplane, much more complicated and far less reliable, but much faster.

In fact, there was recent research from Google and then separately from John Preskill at Caltech and Scott Aaronson that brings this to light. The Google team showed a way to break the Bitcoin protocol with 500,000 superconducting qubits. The Preskill team showed how you could do it with only 10,000 neutral atom qubits, much more efficient. What wasn't highlighted was that the Google computation would take about 9 minutes on a superconducting quantum computer. This computation would take many months on a neutral atom quantum computer. At that speed, they really aren't breaking the Bitcoin protocol. This demonstrates the point that superconducting is much faster, actually 1,000 times faster, but less efficient, requiring more physical qubits to error correct. Well, D-Wave's dual-rail qubits provide the best of both worlds. Again, the best of both worlds. Think a jet airplane.

Still much faster than trapped ions or neutral atoms, much more reliable and efficient than that old piston airplane. You get the speed of superconducting with the efficiency of ions or atoms. This is truly revolutionary, the implications are significant. More reliable computation, more efficient error correction, and a potentially faster, lower overhead path to building useful quantum systems. With built-in erasure detection, these qubits can identify roughly 90% of errors as they occur, with an observed erasure rate of just 0.5%. We have also demonstrated greater than 99.9% fidelities while reducing the number of physical qubits needed for a logical qubit by up to an order of magnitude. Our Advantage becomes even stronger when dual-rail is combined with D-Wave's proprietary on-chip cryogenic control.

This gives us a path to significantly reduce the wiring required to control large numbers of qubits, and ultimately enables full qubit control at scale with multiple orders of magnitude fewer control lines than competing superconducting gate model systems. Any technology that doesn't solve this issue will not achieve utility because they can't feasibly control without requiring football field-sized installations. The combination of speed, fidelity, and scalability is what makes this such an important development. It is not just better qubit design. It is a more scalable system architecture, which is why you should see dual-rail technology as a clear competitive advantage for D-Wave. I'm excited to share with you today more visibility into our gate model roadmap. We are targeting our dual-rail gate model roadmap to extend to 100 logical qubits by the end of 2032.

By the end of 2028, we plan to have approximately 175 physical qubits, which will allow us to demonstrate our quantum error correction technology as well as logical operations. Beyond this, the integration with D-Wave's scalable control is expected to take us to 10 logical qubits by 2030, followed by 100 logical qubits two years later. This acceleration in our roadmap is based upon the unique opportunity provided by the recent merging of Quantum Circuits' expertise in engineering high coherence superconducting quantum devices with D-Wave's extensive toolbox for scaling superconducting quantum processors. With 100 logical qubits, we expect D-Wave to capture as much of the gate model market as any other gate model quantum computing company. There's something else that investors need to see more clearly about roadmaps in this industry.

You've seen companies revise timelines, change milestone frameworks, and move the goalposts as the technical realities and complexities of scaling become clearer. We couldn't be more different. The roadmap we're sharing is built on demonstrated technology, known engineering pathways, and milestones that we believe are achievable with a high degree of confidence. We are not publishing dates for effect. We'll provide more detail on our product roadmap and how it compares to other gate model quantum computing modalities like neutral atoms, trapped ions, and photonics at our upcoming Investor Day on June 1st at the NYSE and online. We encourage you to attend. Our category leadership position is further solidified by our dominance in annealing quantum computing, clearly a foundational strength for the company. This is grounded in a long track record of innovation and product delivery across 6 generations of systems.

Our annealing quantum computers are being deployed today in real customer problems. They're trusted by some of the world's largest companies across manufacturing, aerospace, healthcare, telecommunications, and other sectors, as well as by leading scientific researchers using our systems to accelerate discovery. This is real work driving real value right now. Beyond optimization, we're very excited by what we're seeing in the area of blockchain. We recently collaborated with PostQuant Labs on the development and launch of its quantum classical blockchain test net, which is now live. The test net is designed to support the development of a global quantum blockchain standard and to assess how quantum computing could contribute to a more secure and energy-efficient blockchain in a distributed network. More than 18,500 people have signed up to participate in the test net.

It currently includes more than 1,600 nodes, one of which is D-Wave's Advantage2 annealing quantum computer, with the rest made up of CPUs and GPUs. Our Advantage2 QPU is currently outperforming the classical nodes and winning the majority of the blocks. Together with Postquant Labs, we are launching a detailed benchmarking study to further quantify the advantage. We're also seeing promising work in the area of quantum AI and machine learning. Shionogi, a Japan-based pharmaceutical company, is working on a multi-stage progress project that applies AI to drug discovery, where identifying drug-like molecules with the right activity, chemical properties, and synthetic accessibility is extremely challenging, particularly for classical machine learning methods.

The work is focused on using D-Wave's annealing quantum computers as part of the large language model training process, with the second phase of the project delivering a 10-fold increase in the number of desirable molecules compared with the results generated using a classical machine learning algorithm. Shionogi is now moving into the next phase of the project with the ultimate goal of real-world adoption. We believe that these early results, along with emerging work by other customers exploring quantum computing to improve AI performance, position D-Wave as an important first mover at the intersection of quantum and AI. Together, these examples show that annealing quantum computing is expanding commercially, opening new application areas, and continuing to demonstrate real-world value today. Not only can our annealing quantum computers uniquely address the significant and important optimization market, we are close to being able to demonstrate their value in AI and blockchain.

We continue to expand the capabilities of our annealing quantum computers. We recently published research outlining powerful new multicolor annealing protocols that enable some gate model operations within our commercial Advantage2 systems. We also launched these features with key customers to enable them to perform fundamental research in quantum simulation. These protocols enable researchers to use D-Wave's annealing QPU to model quantum systems and explore fundamentally new behavior that can be extremely difficult, if not impossible, to study with classical techniques. On our last quarterly earnings call, I said that 2025 was an inflection point for D-Wave. Our results continue to support that view. Last year marked a period of clear technical progress and accelerating commercial momentum, including a triple-digit increase in our sales pipeline that continued to expand through the 1st quarter. Today, that momentum is translating into measurable business outcomes.

As discussed, in January alone, we signed two landmark agreements, a $20 million system sale to Florida Atlantic University and the industry's first $10 million enterprise license quantum computing as a service deal. We have previously covered those transactions, so I won't repeat the details here, but I will emphasize their impact as they help to drive record first quarter bookings. During the first quarter, we closed bookings of $33.4 million, a nearly 2,000% increase over Q1 bookings a year ago and up 149% from the very strong bookings in the fourth quarter of 2025. With regard to system sales, I also want to point out that while I originally shared with you that we expect to sell 1 system per year, the pipeline is much stronger.

We're now expecting 2 or 3 system deals per year with expected delivery of at least 2 systems this year in 2026. Before I hand the call over to John to provide deeper details on our first quarter results, there are 5 key points that I want you to keep in mind about what makes D-Wave different. First, D-Wave is the only dual platform quantum computing company. We are developing both annealing and gate model quantum computing systems, which we believe uniquely positions us to participate in the full addressable quantum computing market over time. Second, annealing quantum computing is better suited for optimization than gate model quantum computing. By its nature, it is uniquely built to solve optimization problems, an area that represents a significant share of the overall quantum computing opportunity and one where D-Wave is exceptionally well-positioned to lead.

Third, our customers are using our annealing quantum computing systems in production right now. They're solving hard computational problems that directly affect operations. This is not experimentation. It is commercial deployment by several Forbes Global 2000 companies. Fourth, D-Wave is the first company to solve a hard computational problem beyond classical computing's reach on a real-world useful problem, evidenced by our quantum supremacy results published in Science last March. Fifth, our dual-rail gate model technology changes the game. It combines superconducting speed, high performance fidelity, and a clear path to scale in a way we believe is highly differentiated.

It is increasingly clear that the winners in quantum will be the companies that combine technical differentiation, commercial proof, and the ability to execute at scale. We believe D-Wave is one of those companies, and our first quarter results, along with our momentum in the second quarter, reinforce that position. With that, I'll turn it over to John.

Thank you, Alan, and thank you to everyone taking the time to participate in today's call. Revenue in the first quarter of 2026 was $2.9 million, a decrease of $12.1 million or 81% from the first quarter of 2025 revenue of $15 million that included $12.6 million in revenue from the first sale of a D-Wave annealing quantum computer system. For the first quarter of 2026, D-Wave recognized revenue from over 100 individual customers, over 50% of which were commercial enterprises, with commercial revenue constituting over 73% of the $2.9 million in quarterly revenue.

From a product perspective, Q1 revenue was comprised of $1.8 million in QCAS subscription revenue that increased by nearly 15% on a year-over-year basis and $1 million in professional services revenue that increased by over 26% on a year-over-year basis. For the first quarter, 100% of D-Wave's revenue was derived from selling, providing access to, or providing services for quantum computing systems, not other revenue that has the word quantum attached to it, such as quantum sensing or quantum networking.

Bookings for the first quarter were $33.4 million, an increase of $31.8 million or 1,994% when compared to the 2025 first quarter bookings of $1.6 million and an increase of $20 million or 149% when compared with the immediately preceding 2025 fourth quarter bookings of $13.4 million. Over 2 dozen commercial customers comprised over 31% of the first quarter bookings, with the balance of the bookings from educational and research organizations, the largest of which was the $20 million system sale to Florida Atlantic University.

During the first quarter of 2026, the dollar value of our sales opportunity pipeline more than doubled over the dollar value of the sales opportunity pipeline as of the end of the immediately preceding fourth quarter of 2025, while the average potential deal size more than doubled over the same period. GAAP gross profit for the first quarter was $1.8 million, a decrease of $12.1 million or 87% from the 2025 first quarter GAAP gross profit of $13.9 million that was heavily influenced by the aforementioned system sale in the first quarter of last year.

GAAP gross margin for the first quarter was 63.6%, a decrease of 29% from the 2025 first quarter GAAP gross margin of 92.5% that again was heavily influenced by the aforementioned system sale in the first quarter of last year.

First quarter GAAP operating expenses totaled $56.5 million, an increase of $31.3 million or 125% from GAAP operating expenses of $25.2 million for the 2025 first quarter, with the increase primarily driven by $9.1 million of non-recurring costs related to the acquisition of Quantum Circuits, an increase of $8.6 million in salaries and related personnel costs, 80% of which relates to increases in sales and marketing and research and development personnel, including Quantum Circuits operating expenses subsequent to the closing of the transaction in January, and $7.4 million in non-cash expenses, including $4 million in stock-based comp and $3.4 million in depreciation and amortization expenses. These increased operating expenses stem from investments to support the company's accelerated product development and go-to-market initiatives, as well as Quantum Circuits.

Non-GAAP adjusted operating expenses were $34.8 million, $21.7 million lower than the GAAP operating expenses, with the non-GAAP adjusted operating expenses increasing by $14.6 million or 73% over the year earlier non-GAAP adjusted operating expenses of $20.2 million, with the difference between GAAP and non-GAAP operating expenses primarily being non-cash stock-based comp, non-cash depreciation and amortization expenses, and non-recurring one-time expenses such as the $9.1 million in non-recurring costs associated with the Quantum Circuits acquisition that are excluded from the non-GAAP adjusted operating expenses.

Net loss for the first quarter was $18.4 million or $0.05 per share, compared with a net loss of $5.4 million or $0.02 per share in the first quarter of 2025, with the increase due to higher operating expenses primarily associated with our increased investment in our R&D and sales and marketing organizations and lower gross profit given the high gross profit associated with last year's sale of an annealing quantum computer. Which was partially offset by the increase in income tax benefit of $28.5 million that was derived from the January 20th acquisition of Quantum Circuits.

Adjusted EBITDA loss for the first quarter was $32.8 million, an increase of $26.7 million from the 2025 first quarter adjusted EBITDA loss of $6.1 million, with the increase due primarily to higher operating expenses and lower gross profit. Now I will address the balance sheet and liquidity. As of March 31, D-Wave's consolidated cash balance in marketable investment securities totaled $588.4 million, an increase of $284.1 million or 93% from the 2025 first quarter consolidated cash balance of $304.3 million. During the first quarter, we invested $250 million in cash in conjunction with the acquisition of Quantum Circuits, and we believe that our remaining liquidity is sufficient to support a fully funded plan to profitability.

Subsequent to the 2025 fourth quarter earnings call that was held on February 26th, I've received a number of questions on revenue recognition that I touched on during our fourth quarter earnings call that I will reiterate here specifically as it relates to system sales. These transactions involve a number of steps before the systems are fully operational, including site preparation, delivery, installation, calibration, and other key steps that are likely to encompass multiple months and possibly quarters, depending upon the unique elements of a particular system transaction. While we will recognize a significant portion of revenue upon the physical delivery of the system, we will recognize a smaller portion over time prior to delivery as installation and calibration progress, since these activities are essential for customers to begin using our systems.

This is the general pattern we expect, but each system sale may have unique characteristics that may cause the revenue recognition pattern to vary somewhat. In addition, we anticipate that most system sales transactions will involve one or two multi-year revenue components, including a service and maintenance contract and access to our Leap cloud service. In conjunction with touching on the topic of revenue recognition, we thought it would be helpful to highlight the recent progression of our remaining performance obligations, or as some would refer to this metric as RPOs or backlog. As of March 31st, the aggregate amount of remaining performance obligations that were unsatisfied or partially unsatisfied related to customer contracts totaled $42.4 million.

That represents a $36 million or 563% increase over the first quarter of 2025 RPO balance of $6.4 million and a $29 million or 216% increase over the immediately fourth quarter 2025 RPO balance of $13.4 million. Approximately 54% of the $42.4 million first quarter RPO balance is expected to be recognized as revenue in the next 12 months, and 71% is expected to be recognized as revenue in the next 2 years, with the remainder to be recognized as revenue thereafter. Revenue allocated to remaining performance obligations represents the transaction price of non-cancellable orders for which service has not been performed, which includes deferred revenue and the amounts that will be invoiced and recognized as revenue in future periods from open contracts and excludes unexercised renewals.

The same information is also included in our Form 10-Q. While we are continuing our practice of not providing specific forward financial guidance, given the revenue recognition associated with systems transactions in combination with the remaining performance obligations and the sales pipeline, I want to provide some directional parameters on revenue over the balance of this year. The 2026 second quarter is likely to be up modestly from the first quarter, with a substantial portion of the year's revenue recognized in the second half of the year. In conclusion, as we have previously stated, we continue to believe that D-Wave has the opportunity to be the first independent, publicly held quantum computing company to achieve sustained profitability and to achieve this milestone with substantially less funding than required by any other independent, publicly held quantum computing company. With that, operator, please open the call for questions.

Thank you, Mr. Markovich. We will now proceed to Q&A. To ask a question, you may press star then 1 on your telephone keypad. If you're using a speakerphone, please pick up your handset before pressing the keys. Please limit yourself to 1 question, and if there is time, you may re-queue for a second question. If at any time your question has been addressed and you would like to withdraw your question, please press star then 2. At this time, we will pause momentarily to assemble our roster. The first question comes from Quinn Bolton with Needham. Please go ahead.

Hey, this is Shadi Ghaffari on for Quinn. Thanks for taking our question and congrats on the increased system sales outlook. I guess staying on that topic, what's driving your confidence in being able to secure 2-3 system sales a year? How do you view the split between annealing and gate model going forward? Thank you.

Sure. As both John and I indicated, our pipeline has significantly increased over the course of the last year, and we are, you know, well down the path of negotiating system deals with multiple customers, none of which has been communicated to date. You know, with the Florida Atlantic University sale this year and the progress that we're making on several other system deals, I have a very high degree of confidence that we'll see 2 or 3 sales this year and, as I said, a very high degree of confidence that we will actually deliver 2 of them this year.

The next question comes from John McPeak with Rosenblatt Securities. Please go ahead.

Thank you. Thanks, Alan, John, and Kevin. Congrats on the bookings and RPO number. Pretty impressive. Question on the roadmap here. By the end of 2032, we have 100 logical qubits. Could you give us a sense as to what you're targeting for 2 qubit gate fidelities out there? I have the same question about the 10 logical qubits in 2030.

First of all, you know, we're already at 99.9% fidelity, but that's on, you know, a very small system, admittedly. One of the things that we believe the dual-rail qubits are going to do is put us on a much steeper path to improving fidelities. In particular, the Google Willow work was quite impressive, but we believe that with our dual-rail technology, we'll be able to improve upon that by about five times. We're looking at very high qubit and two qubit gate fidelities.

The next question comes from Antoine Legault with Wedbush Securities. Please go ahead.

Good morning. Thank you for taking my question, and congrats on the momentum so far this year. You know, you've effectively been the sole player in quantum annealing, you know, for over a decade. You know, as the addressable market for optimization grows, Alan, you've cited some pretty significant figures in terms of addressable market. As annealing's commercial viability becomes, you know, more established, do you expect to see more entrants, you know, whether it's from other established gate-based players pivoting towards hybrid approaches, or others moving to the space? Like, how should we think about the competitive landscape going forward?

Yeah. I do wanna point out that the numbers I quoted for optimization are the Boston Consulting Group numbers. This is the data that most people in the quantum industry are using and focused on with respect to the total addressable market. The $100 billion-$220 billion number comes from Boston Consulting Group for optimization. Second, actually, we're already starting to see others working on annealing systems. Very small at this point in time, you know, 2, 3, 4 qubit systems. We're also seeing some gate model companies starting to look at running annealing-type protocols within their gate model systems. Sometimes you'll hear a gate model company say they've done some analog computing within their gate model system.

Part of the reason for looking at this is that, you know, as we've talked about in the past, annealing is far less sensitive to errors and doesn't require error correction to give good results. The problem with that is, there's a lot of overhead associated with trying to run annealing protocols within gate model systems, and they'll never be as fast, or never be able to solve problems as large as what you can solve on a native annealing quantum computer. Yes, there is increasing interest in the annealing approach to quantum computing. There are some early activities underway with respect to building annealing quantum computers, and there is some work going on with respect to trying to perform annealing within gate model systems.

None of that represents a real threat to the advantage that we have in annealing quantum computing. We continue to believe that, you know, D-Wave is and will always be the leader in that portion of the market.

The next question comes from Joe McCormick with Evercore. Please go ahead.

Yeah. Hi, guys. Congrats on the quarter, and thanks for letting me ask a question. You know, maybe just as you've seen the pipeline progress and, you know, kind of, you know, expectations for the aperture to start widening as it relates to system deliveries, moving forward here, can you kind of, you know, double-click on that and talk through, you know, kind of the appetite for on-prem systems for, you know, kinda governments and, you know, kinda academic research versus commercial? Maybe to the extent that you found there's, you know, kinda greater openness on the commercial side of things as well over the next couple of years to, you know, taking, you know, kind of annealing systems on-site.

Yeah. If I were going to guess at what we're likely gonna see this year, I think, you know, when I talk about 2 or 3 system sales this year, I think that we're likely to see one in the commercial arena, and the others more in the research and academic arena. I think we're still in an environment where the system sales are more oriented toward deeper research investigations, where you need control over more of the operating parameters of the system than what's required if you're just trying to, you know, run a commercial application.

But the reason why I say I think we may see one commercial purchase of an annealing quantum computer is because I think at least in the blockchain and AI arena, you know, we may see commercial organizations with an interest in doing some research into how these systems ultimately will be able to benefit AI and/or blockchain. You know, mostly still research and academically oriented, still purchasing systems to be able to control more of the operating parameters that you can't control when you're running on a cloud-based service. Possibly one commercial sale this year, you know, in a, you know, emerging application area where there's some research to be done that will require more control over the parameters of the system.

Now I think that what is likely the potential to change in a significant way, system sale purchase from research and academic to commercial is if we're successful with the work that we're doing on blockchain and AI. I think that those two areas could potentially be very transformative to D-Wave with respect to significant commercial sales of systems in support of those application areas. We're not there yet. We're making good progress. I've talked about this in the past. I think the launch of the test net with Postquant Labs for a new quantum blockchain, quantum classical blockchain environment is a really good next step.

We're hopeful with respect to what we will see coming out of that work and, you know, potentially validating the application opportunity for our systems in that arena, but we're not quite there yet. I also think that not only the work we're doing with Shionogi on AI, but some other companies where we're now doing very similar work to what we've done with Shionogi could potentially help with that transition in AI as well. In both of those cases, we're not quite there yet, but making good progress.

The next question comes from Craig Ellis with B. Riley Securities. Please go ahead.

Yeah, thanks for taking the question, and congratulations on upping the system shipment outlook, guys. I wanted to ask a question on the nice detail you provided with the QCI roadmap. The question is this: What are you hearing from your 100 commercial customers on where they want to engage with that roadmap system capabilities? Is it at the 2028 level, 2030, 2032 level? And to what extent are you seeing QCI start to be additive to your potential customer base? Thank you.

Sure, Craig. We actually have a handful of customers that have expressed interest in the Gate Model system today. A couple have expressed interest in acquiring a Gate Model system, and a few accessing it over the cloud. We are working on moving the tools into our Leap Cloud service, integrating them with our Ocean SDK, and we are working on moving the actual hardware into the Leap Cloud service as well for cloud-based access to the system. We're also working on hardening the systems so that we could support sales of a gate model system, premise-based installations of a gate model system.

There's an understanding of the fact that the current system that we have operational is only 8 qubits, but as we said in the past, we expect to have 17 qubits operational before the end of this year. And honestly, for both the cloud-based access and premise installation, there's interest in either the 8 or the 17-qubit system. In other words, we're not hearing, "Come back to us when you've got a 49 or, you know, 175 qubit system." We're interested in getting our hands on these things now. You know, I think we may start to see some preliminary sales this year, but more likely into 2027.

The next question comes from Krish Sankar with TD Cowen and Company. Please go ahead.

Yeah, hi. Thanks for taking my question. I've got a 2-part question. John, can you give some color on the composition of the backlog of the RPO, how much is commercial, et cetera? Alan, you know, thanks for the color on the commercial adoption. I'm curious, like, some of these research academic sales that you're doing, are these for niche R&D projects, or can some of those lessons learned be ported over to accelerate commercial adoption? Thank you.

John. Sure, to be fair to everybody, you go ahead and answer the first question, and we'll have to defer the second question, 'cause we did say only one question per.

Sure. With respect to the makeup of the backlog, we have $20 million of that is the system sale to FAU. We also have a very significant portion of the commercial enterprise SaaS deal that we did. That backlog is roughly 50/50 between commercial and research.

Krish, feel free to get back in the queue for the second question.

The next question comes from Tyler Anderson with Craig-Hallum. Please go ahead.

Hi, everyone. This is Tyler on for Richard Shannon. Have you gotten your hands on any of your multi-chip processors? If so, what's the initial read and learnings from those? Any comment on coherence time would be helpful. If you haven't, just any timeline you would expect too would be great. Thank you.

Okay. Are you talking about our annealing multi-chip processor?

Either one of them.

Okay.

you have already going on. Thank you.

Yeah. There are two things that we are working on for the multi-chip processors. You know, we've talked about it in the past. We are making good progress. One is obviously the bonding process between the processor chips, and the other is scalable I/O. You know, we are quite unique in the superconducting quantum computing arena in that, you know, we're controlling 4,000 qubits with 200 I/O lines versus everybody else who requires 3 to 5 I/O lines per qubit, and that's due to our on-chip cryogenic control capability. However, as we are scaling from, you know, 4,000 annealing qubits to, you know, ultimately, and for Advantage3, 100,000 annealing qubits, that I/O needs to change.

The architecture needs to be a bit more scalable than it is currently. We now have masks and chips back that represent both the interconnecting of the processors as well as the new scalable I/O architecture. We're about to begin testing of those chips. This is very much an R&D work in process. We're making good progress. We've defined the new scalable I/O architecture. We've created the initial masks to build out that capability. We've got early prototype chips back that we're gonna begin testing. We're in a similar position on the processor, the bonding of the processor chips.

The next question comes from Ruben Roy with Stifel. Please go ahead.

Thank you. John, thanks, I was wondering if you could maybe rough idea on the split on sale between sort of how to think about upfront revenue, installation, calibration, et cetera, versus multi-year service. Just to add onto that is on the RPO, CRPO for 12 months, I assume some of it includes some of the use system installation. Is that correct? Thank you.

Ruben, I caught about half of what you said. You're cutting in and out. Can you repeat?

Yeah. sorry about that. Can you hear me now?

Yes.

I was just asking on the FAU system sale, if you can give us a rough idea on the split between initial installation versus, the sort of multi-year service and, you know, additional components to that sale. Then can you tell us about the CRPO? The 12-month RPO, does that include some of the system sale to FAU? Thank you.

To answer your second question is, yes, the RPO includes FAU, and I cannot provide you detail on the elements of the rev rec on that system yet.

The next question comes from Troy Jensen with Cantor Fitzgerald. A reminder, to ask a question, please press star then one. Please go ahead, Mr. Jensen.

All right. gentlemen, congrats on the great bookings and the momentum here. just for you, Alan, I'd like to hear your thoughts on the NVIDIA announcement. you know, the Ising. Is this less important to D-Wave given the dual-rail technology you guys have and obviously better fidelity, so less need for error correction?

Yeah. First of all, I do wanna comment on their use of the term Ising. You know, annealing quantum computing is basically based on the Ising Hamiltonian. You know, typically, when we talk about programming the annealing quantum computer, for the technical folks, we talk about converting your problem either into a QUBO, quadratic unconstrained binary optimization problem or an Ising model problem. The two are equivalent. One is computer science speak, the other is physicist speak. However, the announcement from NVIDIA with use of the term Ising has absolutely nothing to do with the Ising Hamiltonian or the Ising programming model for annealing-based quantum computers. I'm not entirely sure why they picked that name.

But basically the work that they are focused on with respect to leveraging GPU technology to aid in error correction is important work. I mean, you know, there is a significant classical component to error correction. This is something that a lot of people don't really think much about or focus on. And in fact, it is one of the things that really makes solving optimization problems on gate model systems very inefficient. That classical overhead associated with error correction eats up pretty much all of the benefit of solving the optimization problem on a gate model system, whereas annealing quantum computers don't have that issue. But nonetheless, there is a significant classical component to error correction. GPUs are an important component of the computing landscape for performing that piece of the computation.

In the context of our gate model work, what NVIDIA is talking about is absolutely relevant. That having been said, error correction on a dual-rail processor is quite different from error correction on kind of, you know, standard older technology qubits. The error correction is far more sophisticated and far more efficient. GPUs are still going to be important, but, you know, the computation will be done in a slightly different way. You know, the work that NVIDIA is doing is relevant but not quite as directly applicable to us in our dual-rail technology. There's modification that will be required.

The next question is a follow-up from Joe McCormick with Evercore. Please go ahead.

Yeah. Thanks for letting me ask a follow-up. Quick one for John. Maybe, John, can you explain the, the deferred revenues dynamics? I think you had mentioned it's included in the RPO, and it stepped up a little bit, and I believe that was, you know, kinda related to Quantum Circuits, but maybe just to hear, you know, kind of, you know, kind of the, the step-up there on deferred revs and how it'll impact your backlog moving forward as well.

Well, deferred revenue is one of the components of the RPO number. I can't provide that to you in terms of specific accounts, but it is one of the components of the $43 million in backlog.

We have a follow-up from Krish Sankar with TD Cowen. Please go ahead.

Yeah. Thanks for taking the follow-up. Alan, I had a question for you. You know, your research academic sales, are these for niche R&D projects or do you think lessons learned there can actually be imparted to advancing commercial adoption faster?

Some of the research that's going on is more pure science research. You know, there's been some interesting work recently out of Google that was kind of pure science work and, you know, we've got researchers that are leveraging our systems similarly to do some pure scientific research. Basically, investigating, you know, physics theories that up until now have, you know, not been demonstrated or, you know, analytically validated. This is very important work, very interesting work, but not necessarily commercially application relevant. There's other work that is more commercially relevant. For example, you know, last year we sold a system to the Jülich Supercomputing Centre. You know, that system was delivered and installed last year. It's in their hands now.

They are interconnecting it to their JUPITER exascale supercomputer, 25,000 NVIDIA GPU system, for work on optimization, new optimization and AI workflows. The work coming out of that will absolutely be commercially relevant. I think the work that we will see at Florida Atlantic University is also exploring more commercially relevant application areas. I think it's a mix.

We have a follow-up from Tyler Anderson from Craig-Hallum. Please go ahead.

Hi, guys. Thanks for taking my follow-up. With the blockchain application, is there anything specific about this blockchain that makes it amendable to your system? Are you able to address all proof of work protocols as well as proof of stake or is there a subset? Just like to know what makes this work. Thank you.

Yeah. No, this is a new proof of work protocol that is by construction quantum safe, and if you're doing the mining on the quantum processor, we believe will be much more energy efficient. However, you know, as I said, we are about to enter a benchmarking phase within the test net to, you know, really understand, you know, the accuracy of the statement that I just made. You know, for now, that statement about energy efficiency is a hypothesis, not a fact, and we are beginning the benchmarking work to validate or not that statement. But it is a new proof of work protocol. What makes the quantum computer able to win the majority of the blocks right now is that at its core, the proof of work is drawing samples from a distribution.

The quantum computer is very, very fast and very, very energy efficient at generating samples from a distribution. Whereas CPUs and GPUs have a much heavier lift, and they're much slower. You know, if the proof of work requires you to generate multiple samples, in theory, it gives an edge, and potentially a very significant edge, to the quantum processor. This is not about performing the existing proof of work computations. This is about a brand-new proof of work computation that can be performed either classically or quantum. You can use CPUs, you can use GPUs, you can use the quantum processor, but it absolutely, in theory, gives a significant edge to the quantum processor. If that holds up, then basically we would have an architecture that is quantum safe and much more energy efficient.

This concludes our question and answer session. I would like to turn the conference back over to Dr. Alan Baratz for any closing remarks.

Okay, let me just close with this. The quantum computing shakeout is coming. The industry is moving from promise to proof and from experiments to evidence. We believe that D-Wave is exceptionally well-positioned for that transition because we are already delivering results in the market today while continuing to build differentiated technology for the future. We are not trying to win a corner of quantum. We are building to win across the market. With annealing, we're driving commercial value now. With Gate Model, we believe we have a highly differentiated path to long-term leadership.

Across both, we are making quantum computing easier for customers to adopt, easier to use, and easier to generate value. D-Wave is not waiting for the future of quantum computing. We are helping to define it now. Thanks again for joining us today, and we look forward to continuing the conversation at our Invest Today on June first. We'll see you there. Thank you.

The conference has now concluded. Thank you for attending today's presentation. You may now disconnect.