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Operator: Good morning, everyone and welcome to D-Wave’s First Quarter Fiscal Year 2025 Earnings Conference Call. Today’s call is being recorded. At this time, I would like to turn the floor over to Kevin Hunt of Investor Relations. Please go ahead.

Kevin Hunt: Thank you and good morning. With me today are Dr. Alan Baratz, our Chief Executive Officer; and John Markovich, our Chief Financial Officer. Before we begin, I’d like to remind everyone that this call may contain forward-looking statements and should be considered in conjunction with cautionary statements contained in our earnings release and the company’s most recent periodic SEC report. During today’s call, management will provide certain information that will constitute non-GAAP financial and operational measures under SEC rules, such as non-GAAP gross profit, non-GAAP operating expenses, adjusted EBITDA, and bookings. Reconciliations to GAAP financial measures and certain additional information are also included in today’s earnings release, which is available in the Investor Relations section of our company website at www.dwavequantum.com. I’ll now hand over the call to Alan.

Alan Baratz: Good morning, everyone and thank you for joining us today. I’m really excited to share our results for the first quarter of fiscal 2025. 2025 is shaping up as one of the most significant years in D-Wave’s history, especially when you consider our technical achievements, our product development milestones, our go-to-market momentum and our financial position. Highlights of the first quarter include record quarterly revenue driven by the completion of the first Advantage system sale, additional customer applications moving into production, publication of our quantum supremacy result in science, and ongoing achievements against our aggressive product roadmap. The health of our business remains strong. In terms of some specifics on the financials, our Q1 revenue came in at a record $15 million, and we closed the quarter with a record $304 million in cash, giving us a very solid cash position that we believe is sufficient for us to reach profitability.

Let me now walk you through some key business highlights, starting with technical achievements. On our last call, we proudly shared that we are the first company in the world to demonstrate quantum supremacy on a useful real-world problem. As discussed, D-Wave’s 1200 qubit prototype Advantage2 quantum computer performed a complex magnetic material simulation in minutes and with a level of accuracy that would take nearly 1 million years to complete using one of the world’s most powerful supercomputers. That supercomputer being the frontier massively parallel GPU-based exascale supercomputer at the Oak Ridge National Laboratory. In addition, it will require more than the world’s annual electricity consumption to solve this problem using that supercomputer.

We don’t believe any other researchers or companies have come close to achieving this demonstration. This work should be celebrated as a significant milestone for the quantum industry and a clear demonstration of quantum outperforming classical computing. Building on that demonstration, we recently published a new research paper titled Blockchain with Proof of Quantum Work that used quantum computation to generate and validate blockchain hashes. We believe this research, which leveraged techniques from our quantum supremacy demonstration, indicates that using quantum computation for hashing and proof of work could potentially require a fraction of the electricity used by classical resources alone and reduce electricity costs by up to a factor of 1000.

By adding quantum to traditional blockchain computation, the new architecture could enhance blockchain security and efficiency. Also, as part of this research, D-Wave scientists deployed the blockchain architecture across four of its cloud-based annealing quantum computers in Canada and the United States, performing distributed quantum computing for the first time. This is a very exciting area with potential for broad usage. In fact, we’ve already been contacted by several blockchain focused organizations interested in potential partnerships and we are open to discussions with any other interested parties. With respect to product development progress, our Advantage2 annealing quantum computer, our 6th generation system, has achieved important milestones on the path to general availability, which is expected by the end of this quarter.

These milestones include first, calibration of 4,400+qubit processor chips. We have completed calibration and benchmarking of several 4,400+qubit Advantage2 quantum processors. The Advantage2 QPUs have demonstrated impressive performance gains over the existing Advantage system, including doubled coherence time for faster time to solution, a 40% increase in energy scale for higher quality solutions, and increased qubit connectivity from 15 to 20 way to enable solutions to larger problems. With these substantial performance enhancements, we believe that Advantage2 will be able to solve our customers increasingly complex computational problems, especially in areas such as optimization, AI and material science. The second milestone is Fast Anneal.

This feature offers extended control for notably faster annealing times than previously available, which greatly reduces the impact of external disturbances such as thermal fluctuations in noise that can hinder quantum calculations. The Fast Anneal feature paves the way for customers to reproduce and build on D-Wave’s landmark quantum supremacy results using full scale coherent annealing quantum computing available on the Advantage2 system. And the third milestone is error mitigation. We demonstrated successful quantum error mitigation in the 1,200 qubit Advantage2 annealing quantum computing prototype. The technique reduces errors in quantum simulations, producing results consistent with the quantum system, maintaining its quantum state coherence for an order of magnitude longer than an unmitigated system.

This technique is expected to drive performance advancements in the forthcoming full Advantage2 system and future processors. Once we announce GA, the system will become part of the Leap Quantum Cloud service for use by all of our quantum compute as a service customers. In addition, just a couple weeks ago, we shared that the physical assembly of a D-Wave Advantage2 annealing quantum system is complete at Davidson Technologies headquarters in Huntsville, Alabama. Installation is now nearing completion as that system undergoes calibration and readiness testing. We expect that the Advantage2 system will enable Davidson to explore and develop real-world quantum applications, particularly in optimization, for some of the US Government’s most complex problems and then ultimately deploy those applications in a secure environment.

Turning to software. We recently introduced new hybrid quantum solver capabilities and additional use cases designed to drive usage of our quantum optimization offering. Our hybrid solvers, which are capable of handling problems with up to 2 million variables, now support both integer and continuous variables, which opens up the range of use cases that can be addressed with this technology. Recent enhancements to the nonlinear hybrid quantum solver include the ability to support continuous variables with linear interactions, thus enabling new kinds of use cases such as budget allocation and resource distribution. We’ve also expanded our collection of optimization use cases, which now includes offer allocation, portfolio optimization and maintenance repair operations optimization to apply hybrid quantum technology to a growing set of customer problems.

We also launched an open-source toolkit designed to accelerate quantum AI and machine learning innovation. Available in D-Wave’s Ocean software development kit, the package enables developers to seamlessly integrate D-Wave’s quantum computers with PyTorch, a production grade ML framework widely used to build and train deep learning models. The toolkit includes a neural network module for using a quantum computer to build and train an AI system known as a Restricted Boltzmann Machine, or an RBM. Used to learn patterns and connections from data, RBMs are an AI tool used for tasks such as making predictions, recommendations, and identifying trends or anomalies. Looking ahead, we’re making progress on all aspects of our previously communicated product roadmap, which is designed to unlock new customer production application use cases in the Advantage2 and forthcoming Advantage3 quantum computers and beyond.

It focuses on rapid innovation and scaling, including increased connectivity and coherence, next-generation digital addressing and multi-chip processor fabrics to accelerate a path to reaching 100,000 qubits. We’re also developing techniques in analog digital quantum computing to advance quantum optimization, quantum AI and quantum research by adding digital controls to annealing quantum computing processors. Lastly, we’re continuing our efforts to build scalable error corrected gate model processors, including leveraging our proprietary cryogenic control capabilities that will likely be required in all superconducting gate model quantum computers. Now I’ll turn to commercial progress. As a key metric for assessing a quantum computing vendor’s maturity is whether its technology is used in production to fuel daily operations for customers.

We’re excited to have recently announced that Ford Otosan has developed a hybrid quantum application in production streamlining manufacturing processes for its Ford Transit line of vehicles. Using D-Wave technology, Ford Otosan reduced the scheduling time of 1,000 vehicles from 30 minutes to less than five minutes, a six times improvement. Ford Otosan plans to activate quantum scheduling in additional body shops and extend to other processes, including paint shops, assembly lines and buffer zones. Ford Otosan joins NTT DOCOMO and Pattison Food Group customers that are also using our systems currently running production applications. We expect additional customer applications to enter production deployments over the course of 2025. In another powerful customer use case example, we announced the successful completion of a proof-of-concept with the pharmaceutical division of Japan Tobacco, which used the Advantage quantum computer with artificial intelligence in the drug discovery process.

This new approach resulted in molecular structures that are better candidates for subsequent drug development than structures created by purely classical methods. Japan Tobacco expects that this could lead to improvements in both the quality and speed of drug development. Customer success stories like these and others were on full display at Qubits 2025, our annual user conference, which took place on March 31 and April 1 and saw record attendance. In person attendance was up 23% year-over-year and virtual attendees up nearly 100% year-over-year. A number of D-Wave customers presented use cases based on D-Wave’s technology, including Davidson Technologies, Japan Tobacco, the Julich Supercomputing Center, NTT DOCOMO, Pusan National University, Quantum Research Sciences, SAS, the University of Southern California and more.

We’re also seeing strong interest in the Leap Quantum Launchpad program, which is a three-month trial that provides access to D-Wave’s quantum computing systems, our Leap real-time quantum cloud service and our team of quantum experts for project support. Market demand has been strong with the first customer intending to convert from free trial to paid engagement in less than two months. We continue to believe that this program will expand the universe of organizations using quantum to solve their complex problems today. So, to summarize, we are executing against our technology roadmaps and our go-to-market plans, and this is beginning to show up in our financial results. We are seeing growing interest in D-Wave’s quantum computing solutions as evidenced by a myriad of factors including increased website traffic which is up 153% from October of 2024 to March of 2025, as well as media coverage with strong news stories mentioning D-Wave up 803% from February to March of 2025.

It is evident to us that the D-Wave message is resonating, customers are eager to start exploring and adopting the technology and the world is beginning to recognize the leadership role we’re playing in ushering in the area of quantum computing. We could not be more excited about the future of D-Wave. With that, I’ll hand it over to John to provide a review of our first quarter fiscal 2025 results.

John Markovich: Thank you, Alan and thank you to everyone taking the time to participate in today’s call. In my review of the fiscal 2025 first quarter results, I will be providing non-GAAP operating metrics including bookings as well as non-GAAP financial metrics that include non-GAAP gross profit, non-GAAP gross margins and adjusted EBITDA loss as we believe these metrics improve investors’ ability to evaluate our underlying operating performance. These measures are defined in the tables at the bottom of today’s earnings press release with the non-GAAP financial metrics for the most part adjusting for non-cash and non-recurring expenses. With respect to revenue, revenue in the first quarter fiscal 2025 totaled a record $15 million, which represented an increase of $12.5 million or 509% from the first quarter of fiscal 2024 revenue of $2.5 million, with the magnitude of the increase highly influenced by the sale of an Advantage2 annealing quantum computing system to the Julich Supercomputer Center.

They constituted approximately $12.6 million of the quarterly revenue with QCAAS and professional services comprising the balance. Bookings for the first quarter were $1.6 million, a decrease of $2.9 million or 64% when compared to the fiscal 2024 first quarter bookings of $4.5 million, with professional services bookings comprising more than 50% of the first quarter bookings. With respect to our customers, we continue to broaden and diversify our customer base across commercial research and government organizations. In comparing the most recent trailing four quarters with the immediately preceding trailing four quarters, D-Wave had a total of 133 customers compared to a total of 128 customers with 133 customers, including 69 commercial customers, 25% or 36% of which are Forbes Global 2000 customers, where we are seeing some significant pickup in sales pipeline activity, 52 research customers and 12 government customers.

With respect to gross profit, our GAAP gross profit for the fiscal ’25 first quarter was a record $13.9 million, an increase of $12.2 million or 736% from the fiscal 2024 first quarter GAAP gross profit of $1.7 million. Non-GAAP gross profit for the first quarter was a record $14 million, an increase of $12.2 million or 644% from the fiscal 2024 first quarter non-GAAP gross profit of $1.9 million, with the magnitude of the year-over-year end increase in both GAAP and non-GAAP gross profit due primarily to the higher margin Advantage to system sale. With respect to gross margins, the GAAP gross margin for the first quarter was 92.5%, an increase of 25.2% from the fiscal 2024 first quarter GAAP gross margin of 67.3%. The non-GAAP gross margin for the first quarter was 93.6%, an increase of 17% from the fiscal 2024 first quarter non-GAAP gross margin of 76.6%.

The net loss for the first quarter fiscal 2025 was $5.4 million or $0.02 per share, compared with a net loss of $17.3 million or $0.11 per share in the first quarter of fiscal 2024, with the lower net loss driven primarily by the $12.2 million increase in gross profit that was heavily influenced by the sale of the Advantage to annealing quantum computing system. This represents the company’s lowest quarterly loss since becoming a public company in August of 2022. Adjusted EBITDA loss for the first quarter was $6.1 million, a decrease of $6.8 million or 53% from the fiscal 2024 first quarter adjusted EBITDA loss of $12.9 million, with the decrease due primarily to the year-over-year increase in revenue and the associated gross profit, partially offset by higher operating expenses that are related to the increased investment in our go-to-market, and research and development organizations.

Now I’ll transition to the balance sheet and liquidity. As of March 31, D-Wave’s consolidated cash position totaled a record $304.3 million, and as previously reported, we paid off our secured term loan in the fourth quarter of last year. During the fiscal 2025 first quarter, D-Wave raised $146.2 million in equity through its third aftermarket common stock issuance program. And as of the end of the quarter, we had $37.8 million in available issuance capacity under the equity line of credit with Lincoln Park Capital Fund, with the investment commitment running through October of this year. D-Wave’s ability to utilize the ELOC is subject to a number of conditions including having a sufficient number of registered shares and stock price being above $1.00 per share.

In addition, we exited the first quarter with a record $207.4 million in shareholders equity. To conclude, as we have previously stated, we 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, we will now open the call for questions.

Operator: Thank you. We will now be conducting a question-and-answer session. [Operator Instructions] Our first question comes from the line of Harsh Kumar with Piper Sandler. Please proceed with your question.

Harsh Kumar: Thanks. First of all, strong congratulations on a number of fronts, very strong quarter, your quantum supremacy and then also calibration at a product level calibration of your 4,500 Advantage2 system. I had a question — a couple of questions actually, but I’ll keep it at two and get back in line. Alan, maybe you could talk about Davidson Technology. This sounds to me like another system sale that you’ve been working on. Maybe you could clarify possible for us if this is another one of the three that you have been referring to previously. And then sounds like the system is being calibrated or being assembled right now. Maybe you could give us an update on where you are, when you think it might happen, and then I’ve got a follow up.

Alan Baratz: Okay. Sure Harsh, and thanks for the positive comments up front. So, first of all, Davidson is not one of the other handful of potential system sale opportunities that I commented on — during our last earnings call. But I also did say that system sales tend to take time. And so, while we have a handful that we are working on and some maybe sooner than others, these are long lead sales opportunities. So, it will take us some time to get there. But we’re encouraged by the level of interest based on, in part, the supremacy resolve and the demonstration of capabilities that the system has when you’re able to control more of the operating parameters than possible through the quantum cloud service. And so, having your own system makes sense if that’s the direction that you would like to move in, as well as the fact that, we were able to announce that we had completed our first system sale and so, we’re open for business with that type of business model.

With respect to the partnership with Davidson, this really is focused on working together with Davidson to help identify, develop and ultimately deploy applications to support the US government and specifically defense and security hard optimization applications. With the goal being that, initially the system would be a part of the Leap environment while the R&D work is being done in a non-classified fashion, but that ultimately the system would end up in a secured facility to be able to run secure applications. And so that’s the nature of the partnership with Davidson.

Harsh Kumar: Can I ask a follow up on that before I jump to my second? So, the system seems to be based out of Alabama, so can you talk about. So, this seems like a tangential offshoot, set up a business arrangement outside of the sale. How do the economics work? Is it like regular economics? Like it’s just another one of your systems that happens to be on-site of another customer?

Alan Baratz: So, Harsh, we have not disclosed any of the details associated with the economics, associated with that partnership. So that’s just something that you’re going to have to wait for. Sorry.

Harsh Kumar: Yeah. I respect that. That’s fine. I had a totally different question. So, the more I work on quantum computing, the more I realize that error correction, cryogenic control are two big issues in the industry. You guys seem to be ahead of others in that. And I know it’s going to be a mouthful of an answer, because it’s two big technologies that I’m asking you to discuss. But maybe if you could just summarize for us how you stack up in error correction and cryogenic control versus the rest of your peers in quantum.

Alan Baratz: So, first of all, we are world leaders in cryogenic control. In fact, we are the only company in the world that has cryogenic control operational today. And frankly, as I commented previously, at least every superconducting gate model quantum company is going to need this technology. For the most part, they haven’t even started working on it yet. And we have it operational today. The reason why we have it operational today is because we needed it for our annealing quantum computers. That’s why we are able to control 5,000 qubits with just a couple of hundred I/O lines, and why we believe we’ll be able to control even 100,000 qubits with just a couple of hundred I/O lines. So, everybody in the supercomputing quantum computing space will ultimately need this capability in order to be able to scale their processes.

And we’re the only company in the world that has it today. And we’ve got a significant patent portfolio basically built around that capability. With respect to error correction, I think we’ve mentioned this before, but annealing quantum computers do not need the same type or level of error correction that’s required by gate model quantum computers. And so, while we’ve developed some error mitigation technologies that are very useful for annealing quantum computing, we have not built the kind of error correction that is required for gate models. Now under our gate model program, we are working on that today. But unlike cryogenic control, where we have it in hand, almost commercial grade, we don’t yet have that for gate model system. We don’t yet have error correction for gate model systems.

Operator: Thank you. Our next question comes from the line of Craig Ellis with B. Riley Securities. Please proceed with your question.

Craig Ellis: Yeah. Thanks for taking the question and congratulations guys on the technical and financial accomplishments in the quarter. Alan, I wanted to start with you with the first question. You mentioned that there were numerous blockchain application partnerships that were inbound and it sounds like initially engaged. Can you just provide more color on the opportunity that you see in that area?

Alan Baratz: Yeah. So, Craig, we’re not blockchain experts. And as a result, while we’ve developed an architecture and prototyped it and have it operational today, that we think could be of real value to the blockchain industry, we’re not going to pursue that ourselves. We would pursue that only in partnership with some organization for which that really is their focus and their business. And so, as a result, we were encouraged when a number of companies and investors, frankly, who have expertise and are interested in the space approached us to talk about actual applications and opportunities to leverage this technology. And so, we are working through that to make a determination around what would be the best way, if at all, to commercialize this.

The only thing I will say, though, is for blockchain as well as — we’ve talked about AI as well, and we’re working on how the quantum computers can basically enhance AI and machine learning, both model training and inference. What’s interesting to us and really compelling about both the blockchain and AI opportunities is we actually think they drive the system sale model of our business more than the quantum compute as a service model of our business. And so, while quantum optimization and supporting customers that have applications that they need to run in support of their day-to-day business operations really continues to be a QCAAS, quantum computer as a service, oriented business, we think blockchain and AI will kind of enhance the system sale component of the model.

But I have to caution you, it’s early days.

Craig Ellis: Certainly, and the continuous compute nature of blockchain and AI make it understandable why there might be more of a system sale interest there. John, I’ll switch to you for the second question. And it’s really a clarification and then a follow up. The clarification on the 93.6% gross margin super high level. Is that a proxy for how the model could work when we have a full system sale in the quarter? Or were there some one-time items that might have benefited that? And then you did mention that there’s been an uptick in pipeline activity. If you could just elaborate on that, that would be great. Thank you.

John Markovich: Sure. Generally, it is a proxy, Craig, but as we’ve previously outlined, we have a database of one system sale being this one. So, each deal is going to have unique elements to it. But as it relates to the actual sale of the systems component of these types of arrangements, the gross margins will clearly be higher than what our average consolidated gross margin is, as we just demonstrated in the first quarter. Having said that, there could be some variability relative to what we saw here in the first quarter, but generally they’ll be higher than the QCAAS margins that are typically in the 70% to 80% range. Your second question had to do with pipeline.

Alan Baratz: Yes, John.

John Markovich: Yes. So, we’re seeing a very, very healthy sales pipeline. And what is most interesting about it is we now have a fair number of larger organizations, including a number of Forbes Global 2000 companies. That’s the positive element of what’s happening in the pipeline. But associated with that, these deals typically take longer, because you’re dealing with larger organizations that have in many cases complex procurement processes. I’ll also point out with respect to our customer count numbers that I provided earlier, that over the last two sequential quarters, we’ve seen an increase in the average revenue per commercial customer as well as the average revenue per government customer. So, although, the customer count has not increased dramatically, underlying that is a growth in the average revenue per commercial account and government account over the last two sequential quarters.

Operator: Thank you. Our next question comes from the line of Quinn Bolton with Needham & Company. Please proceed with your question.

Quinn Bolton: Hey, guys. Let me also offer my congratulations on both the financial and technical milestones in the quarter. I’m not sure if it’s for John or Alan, but just a clarification on the system sale. I think last quarter, when you discuss this sale, you mentioned that there’s an option for an upgrade to the Advantage2 processor. In today’s script, you’re saying that you have installed an Advantage2 system. And so, I’m wondering, did the system sale price you recognize, did that include the upgrade option? Or is that upgrade option for the QPU still available to be deployed sometime later this year or next?

Alan Baratz: Sorry, Quinn, I think you confused two different things here. The Julich system installation that has been handed over to Julich is an Advantage system with the option to upgrade to Advantage2. The Davidson system is an Advantage2 system installed from the outset. And so, yes, the upgrade of the system at Julich is still to be done.

Quinn Bolton: Okay. Maybe I misheard. I thought in the script you had referred to the Julich system as Advantage2. So, my apologies, but that option is still available for later this year. Alan, the second question I had is you talked about NTT DOCOMO, Pattison and Ford Otosan moving to production. Can you just discuss the pipeline of additional customers moving applications? How are you feeling about converting additional customers or more applications at the three I mentioned into production over the course of the year? Thank you.

Alan Baratz: Yeah. So, I can’t give you any specifics. We’ve talked in the past about what’s involved in progressing a customer, from proof-of-concept through to benchmarking through to kind of the work that needs to be done on their internal infrastructure environment in order to move the application into production. All on the path to moving into production. And that does take some time. That having been said, maybe the best way to think about this is to think about all the entities read that as companies or partners or institutions that showed up at qubits and were on stage in one way or another, either giving a presentation or as a part of the keynote in panel discussions, what have you. These are all companies that we are working with, and that can give you a sense of what the pipeline might look like on the path to production.

Operator: Thank you. Our next question comes from the line of Suji Desilva with Roth Capital Partners. Please proceed with your question.

Suji Desilva: Good morning, Alan. Good morning, John. Congrats on all the progress here. I think, John or Alan, you talked about the increasing revenue per customer. Can you talk about the shape that’s taking anecdotally? Are you seeing maybe one application going to two, or is it more that you’re seeing one application getting the customer bought into the approach and then kind of looking to spread across multiple applications? What are you seeing more anecdotally?

Alan Baratz: John, do you want to take that?

John Markovich: Sure. I mean, typically, Suji, we’re starting with one application and depending on how that goes, and there’s the opportunity for multiple opportunities or multiple applications. But typically, we start with a focus on successfully executing one initial application, even though there’s interest or maybe interest in multiple applications locations. The objective is to get the first application into production as quickly as possible.

Alan Baratz: Suji, I think the only thing I might add to that is that part of the reason why we’re seeing this growth is that, as John commented, we’re starting to now engage with larger companies who are interested in having us help them to build out the proof-of-concept versus just kind of buy a small amount of quantum compute as a service and do it yourself kind of effort. And that, of course, drives larger deals for us.

Suji Desilva: Okay. Alan, John, thanks for that color. And then, I think you mentioned, John, with the funding level you have now that you’re funded to profitability, can you give us some help here on what your thoughts are on, what a revenue run rate might be when you reach profitability? And within that, what the mix at that point might be on an annual basis, maybe Advantage systems versus service revenue.

John Markovich: Quick answer, Suji, is we’ve not quantified what that revenue run rate is as it relates to achieving profitability, nor have we provided any timing. What we have outlined, and we did this in a January press release based upon the closing of the most recent ATM, that we have sufficient liquidity to get us to that point in time of sustained profitability and positive cash flow.

Operator: Thank you. Our next question comes from the line of Tyler Anderson with Craig-Hallum. Please proceed with your question.

Tyler Anderson: Morning, gentlemen. Congratulations and thank you for taking my question. And specifically, congratulations on the error mitigation. I was just wondering if this is available as a library for customers who purchase systems? And if you could quote the coherence time difference between the 1.2K and the 4.4K processors that you’re seeing.

Alan Baratz: Okay. So, first of all, the coherence times on the 1.2 and 4.4 are the same. So, these are both Advantage2 processors where the chips were fabricated using essentially the same fabrication process and the same materials. The only difference is the number of qubits on the chip. And so, what drives the coherence time is the materials and the fab process and basically the reduction in noise through that fab process. So, since these chips are using the same process, the same materials, they essentially have the same coherence time with one being 1,200 cubits on the chip and the other being 4,400 qubits on the chip. With respect to error mitigation, the error mitigation essentially gives us the effect of a 10x increase incoherence time for certain types of problems over the base coherence time.

So, we said that Advantage2 has two times the coherence time over Advantage. And with error mitigation, we get another 10x on Advantage2. So that would put Advantage2 a 20x over Advantage or 10x Advantage2 error mitigated versus Advantage2 not error mitigated. But in my comments, I said for material simulation problems. So, the error mitigation technique works for certain classes of problems. It’s particularly good for simulation problems.

Tyler Anderson: Okay. Great. Thank you. That’s good color. And could you discuss whether the David installation has been garnering system cell attention from primes or the government? Because it seemed like your installation stole some thunder from other events in the area, and they had to change their date. And then how much of that system sales in Q2 as a percent, or any color on that?

Alan Baratz: Okay. So, again, we haven’t disclosed any of the terms of the Davidson relationship, so I can’t go into any detail there. What I will say is that we have an enormous amount of interest in systems from governments and supercomputing centers around the world, but frankly less so in the United States. We’ve talked about this before, but there is a strong gate model bias in the US Government. That is something that we are working hard to address. And we’re making incremental progress, but we are not there yet. We believe it’s a huge mistake on the part of the US Government because frankly, other governments around the world are looking at quantum computing to help solve important hard problems today, recognizing that annealing can do that while gate model can.

And the US, in my view, admittedly somewhat biased, is falling way behind on this and really needs to get that sorted out. So, I would not say that we’re seeing a lot of interest from the US Government in system sales at this point in time.

Operator: And our next question comes from the line of Harsh Kumar, a follow up question. Please proceed with your question.

Harsh Kumar: So, I think, Alan, you might have just answered my question. I was going to ask you about with the change in the US Government, what you’re seeing, but I think you just answered that one, so I’ll let that be. You did talk about blockchain hashing and that you will need a partner, like a strong partner that you will work with. That’s the only way. It seems like you want to go-to-market on that. So, I was curious if you might share, what kind of characteristics would you look for in a partner for something like that? Would it be like a crypto exchange or — I don’t even know that much about blockchain. Maybe you could just educate us a little bit on what kind of partner you will need.

Alan Baratz: Sure. So, let me just make a further comment on the US Government since you started there. Look, the Trump administration is still relatively new. Not even all of his appointments have been installed yet, including in areas that are technology related. And so, we are hopeful that with the change in administration, there will be an increased interest in and focus on quantum computing and in looking at all forms of quantum computing, as well as looking at near-term applications versus long-term research. And we’re starting to see a little bit of turnover in some of the key positions that frankly have been part of the challenge that we’ve been facing. So, we’re hopeful. But we’re not there yet. And so, we just need to see how this will play out over the next several months.

And, of course, we continue to be very focused on helping to educate and engage with the US Government because frankly, we want to be helpful and we think we can be helpful. And we’d like to get that level of engagement and support. With respect to blockchain. So, it’s not only about cryptocurrency, Harsh. It’s about protecting assets, protecting important information. Elon Musk has talked about putting the US Government ledger on a blockchain. The important elements of blockchain are that A, it’s very secure; and B, it’s immutable. I mean, you can’t change it, right? So, it’s a great way to kind of enshrine important information in a way that can’t be modified or subverted in some way. And so, you could put health records in a blockchain, for example; you could put financial ledgers in a blockchain.

These are all interesting and useful applications. And so, the type of partner, we’re kind of open minded on it, but it could go the route of application oriented or it could go the route of kind of a generic service and we’re still trying to work through that.

Harsh Kumar: Very helpful, Alan. Thank you.

Operator: Thank you. Our next question is another follow up question from the line of Tyler Anderson. Please proceed with your question.

Tyler Anderson: Thanks for taking my follow up, guys. Your gate on annealing or your gate alone system, can the gate model be toggled through software, or does this require hardware tweaks? And if it’s hardware, does this take a long time and can non-research customers do this themselves? And does it require like new guts and controls within the dilution fridge?

Alan Baratz: Okay. I’m not sure I understand your question, but let me make some comments and then if I have not addressed it, feel free to kind of refine the question. So, our annealing quantum computer and our gate model development work are two separate quantum computing systems. They are very different architectures. There’s a lot of technology, underlying technology that can be leveraged from the annealing quantum system into the gate model quantum system. But they are different architectures, they are different hardware systems. So, it’s not the case that you can take our annealing quantum computer and somehow toggle it to run as a gate model system. That is not the case. As I said, two different architectures, two different hardware systems, but synergy between them in the sense that important technologies that we developed for annealing like cryogenic control can be applied in development of the gate model system.

Second thing I’ll say is our annealing quantum computers are very far advanced today. Advantage2 will be our sixth-generation annealing quantum computer, and they are commercial systems today. In fact, they’re the only quantum computers in the world that are truly commercial today, supporting customer business applications in production. Our gate model system is still in the early R&D phase. Now the only other thing I’ll say is I did talk about digital analog controls in our annealing quantum computer and that may be where your question came from. So, one of the things that we have been able to demonstrate is the ability to take our annealing quantum computer and perform some digital operations on it. Do not think of this as all the gate model controls and operations.

That’s not the case. But some of them, like being able to directly excite a qubit or being able to take the state of one qubit and move it to another qubit. These are some gate model controls that when applied to an annealing quantum computer can actually deliver some very interesting capabilities for optimization applications. And so, what we’re working on is applying some digital controls, read that as some of the gate model controls to the annealing fabric to improve some of the capabilities of the annealing quantum system. But separate from that, building a full gate model quantum computer.

Tyler Anderson: Okay. So just to reframe quickly and I got one more follow up. So, can somebody swap out the QPU with the existing control hardware that they have that they bought a previous system, or do they need to buy a whole new system or swap out the control from the one they have?

Alan Baratz: If what you want to do is to upgrade from one annealing quantum computer to another, for example, from Advantage to an Advantage2, that’s essentially a chip change and some minor I/O modifications, but not a whole new system. If what you want to do is go from Advantage annealing quantum computer to, say a D-Wave gate model quantum computer, at some point in the future, you would not need a new dilution refrigerator, but you would need to change out both the chip and pretty much all of the I/O and control.

Tyler Anderson: Okay. And then for your Advantage2 the 4,000 qubit one, is this accessible to certain customers? Are you generating revenues on that or are you still waiting to release this broadly?

Alan Baratz: Okay. So, we have the 1,200 qubit prototype Advantage2 in our elite quantum cloud service that any customer can use today. Our 4,400 qubit full scale Advantage2 quantum computer we will make generally available before the end of this quarter, before the end of Q2. At that point, it will be a part of our quantum cloud service for any customers to make use of it as well as kind of being the primary processor that we would use in any remote installations.

Tyler Anderson: Awesome. Thank you. I appreciate you taking my questions.

Operator: Thank you. Our next question is another follow up question from the line of Craig Ellis. Please proceed with your question.

Craig Ellis: Thanks for taking the follow up. Alan, at Qubits ’25 you presented a long-term technology roadmap that included scaling up to, I believe it was 20k and 100k qubit systems. Can you just elaborate a little bit on the reaction you got from customers and partners at the event and since the event on that roadmap?

Alan Baratz: Yeah. I mean, as you’d expect it excitement. I mean, the truth of the matter is, and I think I’ve talked about this before, obviously with more qubits and more connectivity, we are able to solve larger and more complex problems on the quantum computer. Now today, the way we solve larger and more complex problems that can be solved natively on the quantum computer is by using our hybrid solvers. And it’s a very powerful technology. But the more of the problem that we can solve natively on the quantum computer, the greater the advantage over classical. And so, while we have — many customers that today, through the hybrid solvers are seeing improvements over their classical solutions and as a result they’re seeing a good ROI.

And that’s why we’ve got three customers with applications in production and more that are on the path to production. If we were able to solve more or all of the problem on the quantum computer, the improvement would be significantly larger. Right? And an even stronger ROI. So, the excitement is around the ability to on the one hand, enable additional use cases that aren’t yet possible, and on the other hand, see increased benefit over classical for things that where benefit is already today being seen.

Craig Ellis: That’s helpful. Thank you.

Operator: Thank you. This concludes our question-and-answer session. I’d like to turn the floor back over to Dr. Baratz for closing comments.

End of Q&A:

Alan Baratz: Okay. So, thank you all again for taking the time to be here with us today. Frankly, we see only tailwinds as we continue to blaze the trail of quantum computing innovation and adoption. I’ve never been more confident in our business, our technology, our commercial opportunities, and our truly remarkable team. So, thanks again for taking the time to join us today.

Operator: This concludes today’s teleconference. You may disconnect your lines at this time. Thank you for your participation and have a wonderful day.