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Welcome to Nebius Group's Q2 2026 earnings conference call. The presentation will be followed by a Q&A session. If you would like to ask a question, you can click on the Ask a Question tab in the top right of the livestream player, then just type in your question and click submit. You can submit questions at any time during the presentation, and the Nebius management team will try and answer them during the Q&A portion of the call. I will now hand over to Gillian Aftolovich, Head of Investor Relations, to start the call.

Hi everyone, and welcome to Nebius's 2nd quarter 2026 earnings conference call. Joining us on the call today, we have our CEO Arkadiy, our CFO Dado, and the broader Nebius management team. Before we get started, I'll quickly cover the safe harbor. Some of the statements that we make today regarding our business operations and financial performance may be considered forward-looking. Such statements are based on current expectations and assumptions that are subject to a number of risks and uncertainties. Actual results could differ materially. Please refer to our Form 20-F for a list of our risk factors. We undertake no obligation to update any forward-looking statements. During this call, we will present both GAAP and non-GAAP financial measures. A reconciliation of non-GAAP to GAAP measures is included in today's earnings press release. All earnings-related documents are distributed and available to the public through our investor relations website, which can be found at Nebius.com. And now I'd like to turn the call over to Arkady.

Thanks, Gillian, and welcome everyone to our call today. I would like to provide our investors with a better understanding of our business model. We had an excellent quarter. The demand for what we're building continues to be enormous, and we have the right business model to capture it. We build capacity ahead of contract and use our multi-tenant cloud and our software stack to support our customers— AI natives, agentic AI leaders, new labs, and some of the most sophisticated enterprises. Our strategy is working. We choose when to sell, to whom we sell, and on what terms, and how we finance everything. This flexibility allows us to meet the needs of independent AI builders and to support an open, diverse, and competitive market. We address customer needs with 3 types of deals. Each has a different duration, pricing, and role in our business. First, for our core AI cloud business, we have midterm contracts of 1 to 3 years with the world's most ambitious AI companies. This quarter alone, we closed four landmark deals with Reflection, Cohere, as well as with a scale U.S. Newlab and a large U.S.-based quant trading firm. These deals were for an average of more than a billion dollars each. They represent a yield of twenty to twenty-five million dollars per megawatt, with upfront payments that cover fifty-sixty percent of the associated cap. But most importantly, we could sell today our entire 2027 capacity on these terms if we wanted to. But we are not doing this. We see that we can achieve higher value by retaining some capacity to serve shorter-term and immediate client needs. And here we come to the second type of deal. This is shorter-duration capacity. Typically for up to six months, for customers with an immediate time-bound need with high-value requirements. For this, they are ready to pay a significant premium. We're negotiating deals for forty to fifty million dollars per megawatt range, and sometimes above under this model. One of such deals has been signed just recently by the way.

Way.

Both deal terms, uh, I just described are all coming online later this year, so they will not have a material effect on our 2026 revenue guidance. However, they will be— they will definitely affect our 2027 revenue and beyond. The third deal type, as we noted many times in the past, is our long-term contracts with investment-grade customers. They serve an important purpose They help us to finance our build-out faster and more efficiently. The secured debt facility we raised in July was on the back of one of these deals. And with $40 billion in contracted backlog, we will do more of this. We are constantly building, innovating, and developing our software stack, token and agentic offerings and services. But today, I would like to focus on different types of innovations from this quarter. We launched our first capacity auction. It was very successful and cleared at the highest price we have seen for the Blackwell generation of chips, 15% above the highest price we ever charged before. This gives us a strong signal on the value of this capacity in the market in real time. This was an innovation of sorts on the go-to-market side.

Side.

On the capacity side, we're also innovating in how we build. For example, our asset-light partnership model, which we introduced this quarter, provides an additional way for us to scale. This model addresses the 2 constraints of our industry, which is capital and capacity. Partners finance, build, and operate the facilities Whereas Nebius brings the full-stack platform and the demand. We provide value-added services that sit on top of our partners' infrastructure, which delivers us with high-margin revenue and requires minimum balance sheet capital. This model has the potential to unlock new capacity for us in 2027 and beyond. We continue to build our future capacity pipeline through our own and co-located sites, And today raise our year-end contracted power target to 5 gigawatts. Our future capacity pipeline effectively makes NEBIUS one of just a few companies in the world able to build more than 1 gigawatt of new capacity a year, and we plan to do so in 2027. So to close, Everything we set out to do this quarter, we have done, and in most cases, we have done more. Landmark deals in our core market on better terms than we expected, capacity rising to meet demand, and a platform meeting the needs of the industry. We are not just reporting a strong quarter behind us. It's much more than that. We see the demand, we see the supply, we see deal terms for 2027 and beyond. Even our future capacity plans, including for '27, we cannot be more excited about the future. And on this optimistic note, let me hand it over to Dado.

Thank you, Arkadiy. We entered the second half of the year with strong momentum as we successfully executed our strategy in the first half. We again delivered triple-digit revenue and ARR growth growth in Q2, even before most of our 2026 capacity comes online in the second half of the year. This was coupled with a significant expansion in adjusted EBITDA margin while strengthening our funding position, which was supported by substantial customer prepayment terms and expanded sources of our capital. This start is strong and keeps us on track to achieve both our strategic and financial objectives for the I will touch on the progress we achieved in Q2, share details on our financial results, and conclude with our annual guidance, which we are reaffirming today. Please note that all comparisons are year over year unless noted otherwise. Let's start with revenue and ARR. In Q2, we grew group revenue by 454% to $582 million, up 46% from last quarter. Our Nebius AI ARR business grew even faster, increasing 514% from last year to $575 million and generating 98% of group revenue. Annualized run rate revenue reached $3 billion at the end of June, up 598% and increased 56% from $1.9 billion at the end of March. Revenue was driven by capacity added in Q1, higher utilization, and high-margin revenue from our new asset-light business model, Token Factory, and our recent acquisitions. Higher utilization was driven by improvements in our underlying infrastructure efficiency. And once again, we sold out of capacity because as fast as we bring capacity online, we can sell it. Turning to profitability, group adjusted EBITDA was $236 million compared to a loss of $21 million a year ago and $129.5 million last quarter. Group adjusted EBITDA margin was 41%, up from 32% in Q1. Our Nebius AI business generated adjusted EBITDA of $286 million at a margin of 50%. The delta between group and the Nebius AI business margin reflects our investments in Avride and TripleTen. Both are still early-stage companies, and we expect the Nebius AI business to continue to represent the significant majority of group adjusted EBITDA. The increase in profitability is a result of higher revenue and the early contribution of our asset-light model, as well as Token Factory and our recent acquisitions. Even as we continue to invest in growth, we see a clear path to capturing more margin, not just this year, but in 2027 and well beyond. We have visibility into pricing and expect capacity coming online from our own data center to begin improving margins in the second half of next year. Now, turning to our balance sheet, prepayments from our customers reached an all-time high in the quarter. Roughly 70% of the deals we closed in Q2 included an upfront prepayment. In total, customers' prepayments will bring in more than $9 billion of upfront funding this year, directly reducing the capital we need from debt and equity. Operating cash flow was $2.3 billion in the quarter, and we ended the period with $8 billion in cash and cash equivalents. In Q2, we also tapped our at-the-market equity program. We issued 12.7 million Class A shares at a weighted average price of $224 per share, generating gross proceeds of approximately $2.8 billion. As of June 30th, 12.3 million shares remained available under the program. We view the ATM as a flexible funding tool, and it remains an option in our arsenal rather than a commitment. In July, we announced our first asset-backed debt facility for $775 million. This facility is secured against contracted cash flows and priced at a modest spread over benchmark rates. Its rate today is equivalent to a mid-single-digit percentage. And we have more than $40 billion of additional customer commitments at similar terms based on the strategic deals we have entered into with investment-grade companies. We will continue to diversify our funding sources while maintaining a balanced mix of debt and equity. We are progressing on additional asset-backed financing and continue to evaluate corporate-level debt and additional financing instruments. Turning next to CapEx. In Q2, capital expenditures were approximately $5.7 billion, driven primarily by purchases of GPUs, GPU-related hardware, and by our data center expansion. Our capital investments to date position us to achieve our capacity plans for the year. Let me turn to outlook. The solid progress we have achieved in the first half of the year bolsters our confidence in our outlook for 2026. As such, we are reaffirming our full-year 2026 guidance across all metrics. We continue to expect annualized run rate revenue of $7 to $9 billion, group revenue of between $3 and $3.4 billion, group adjusted EBITDA margin of approximately 40%, and capital expenditures of $20 to $25 billion. And we remain confident in our ability to accelerate capacity deployment in the second half of the year, year and expect capacity deployed late in Q2 to begin contributing to revenue in Q3. As Arkadiy said, we are now building capacity for 2027 demand, supported by customer commitments already in place and providing near-term visibility into the revenue associated with this investment. And finally, we are actively pursuing opportunities to generate incremental high-margin revenue from our new models, our auction, our short-term capacity deals, as well as, as our asset-light business. In summary, our strong Q2 performance reflects a rigorous execution to scale the business profitably. We deliver solid revenue growth, we increase profitability, we opened a new capital-efficient path to capacity, and we expanded our funding alternatives. As we look ahead, we will continue to scale rapidly to capture the opportunity in front of us while remaining balanced, disciplined, and focused on delivering long-term value for our shareholders. And with that, I will turn the call over to Gillian for Q&A.

If you would like to ask a question, please click the Ask a Question tab in the top right of the livestream player. Then just type in your question and click submit. I'll now hand back to the Nebius management team for the Q&A session.

Thank you, operator, and thank you, Dado. Our first question comes in from Ryan Lomtes from Morgan Stanley. With Vineland— with the Vineland, New Jersey data center site hearing adjourning without a vote, can we just get an update on the site? How is capacity tracking? And with no vote taking place yet, how could this impact plans to ramp this site? Tom, can you help us answer that?

Yeah, sure. Happy to. I'll start by touching on the public hearing side of things. And I guess maybe just one quick sort of general comment. Obviously, this is a broader set of issues and debate around data centers in the US. These are things that we track very closely, and we've generally found that we have an effective approach to moving into new regions, which is based on coming in early, being very open, transparent about what we're doing, engaging with the community, and actually answering the questions that come up. And we find that this is an effective approach, and the same approach that we've been applying in New Jersey around Vineland. So specifically around Vineland, so what— overall, we're on track with our delivery, and I'll let Andre speak a little bit more in a bit more detail about that from the kind of the construction and build-out side. But with respect to the public hearing, so what's happening right now? DataOne is seeking final approval for the amendment to their originally approved site layout plan. And the amendment to the site layout plan was a result of the decision to switch from the project's power source to Bloom. I'd say generally that the switch to Bloom, we think, significantly enhances the project, including from a community perspective. It's an onsite power solution delivering reliable power quietly and ultra-low emissions. I'd also say these types of hearings, these are all part of the normal process, and we very much build them into our schedule with these steps in mind. And so with respects to this hearing on the layout plan, so we're confident that the layout complies with all the applicable local, state, and federal laws and regulations, and we're optimistic that once the public has been heard, this will move quickly to approval, and we'll definitely keep you updated as we have more news. But with that, maybe I can ask Andrey to add a couple of points just from the build-out side.

Yeah, sure, Tom. Hello, everyone. Well, we deliver all the trenches that we were required to deliver under the contract up to date, and we have all the reasons to believe that we will continue to deliver the remaining trenches as required by the contract. And probably to add color, construction of the building itself finished earlier this summer, and engineering fit-out is progressing fairly well. And Bloom fuel cells deployment should be fast, and overall the switch to Bloom has been a valuable and a good pivot for the project, we believe, and with no significant impact expected on the project timeline.

Okay, thank you. Our next question is— we're getting a lot of questions actually on this from the portal Well, Mark, maybe you can help us talk through our landmark deal announcements. Can you characterize how those processes ran and why these customers chose Nebius?

Certainly. Thank you for the question. And we are very excited about these wins. Closing billion-dollar deals in our core AI cloud business is an important milestone in our go-to-market journey. It confirms our fundamental belief that we can build a diversified customer base at scale. All 4 were competitive wins following a similar pattern. Our scale, performance, and reliability were the differentiators. Also, each customer sees us as a long-term partner that they can grow with. In all cases, the customer already had an existing supplier, in some cases hyperscaler, and they were looking to partner and expand with with next-generation capacity and a platform. As a matter of fact, let me tell you about one of these wins. They were introduced to us by a key strategic partner late in Q1. The customer was looking for a large-scale contiguous GB300 cluster, also flexibility for future expansion, as well as strong technical support support and a long-term strategic partnership. When we closed with them in May, they cited our responsiveness, our transparency, the white glove support they received, and our ability to provide their current U.S. deployment needs as well as future sovereign expansion as key differentiators. We are now in discussions with them for more capacity And they're exploring our inference solution, Token Factory. All of these wins were earned wins, not inbound walk-ins. We had multiple engagement cycles before closing. The customers validated our technology through hands-on POCs. One of them told us it was quite literally the best POC they had ever had. We are already in discussions with several of them on post-training and inference to support their revenue plans and growth, and with all of them on significant additional capacity and next-generation chips, including Vera Rubin. And yes, we have more deals just like them. Our pipeline generation stepped up again in Q2 and includes multiple opportunities over $1 billion spanning AI natives, new labs, and enterprises.

Thank you, Mark. The next question we have comes from Alex Duvall at Goldman Sachs. Andrey, a large share of our deals we signed are tied to capacity arriving in late 2026 and through 2027. Given the sentiment around gigawatt-scale data center buildout, what gives you the confidence in our capacity ramp, and can you provide an update on our development timing?

Thank you, Gillian. Well, we made very good progress this year with our contracted power, and we exceeded our end-of-the-year projections much earlier for 2026. And we will be raising— or we are raising, actually, the contracted power to 5 gigawatts now by the end of 2026. Almost all of that power will come online over the next 3, maybe 2, 3.5 years out of the contracted power, that number that we mentioned. And we are not stopping, actually. This is being achieved by different region expansion and the mix of grid power and behind-the-meter power. We also working on security to have the access to the hundreds of megawatts of the generation behind the meter power already as of today. We're also excited about our partnership with Bloom, which allows us to unlock and expedite a lot of our sites. And also, I wanted to mention that the vast majority of our contracts is the cloud contracts where we have the flexibility where within the region we can deliver it, reducing the dependency on any one location. So over-provisioning the sites, over-provisioning the capacity is our highest priority for today, and I believe will be in the future. the case for tomorrow as well. And general approach is we deploy as much capacity as we can, and we try to build in advance as much as we can as well.

Thank you, Andrey. Arkady, we've had a number of questions come in on our strategy. The market is moving quickly. You mentioned prices are increasing, and you plan to expand capacity by more than 1 gigawatt You also announced a lot of new initiatives this quarter. Help us make sense of how these fit into our broader long-term strategy.

Yes, you're right. The market is evolving rapidly, actually even more rapidly than everybody expected. And the good thing about our business model and our platform as well is that they both allow us to evolve rapidly with the market. I will give you a couple of examples from just this quarter. First, as we all see, prices are changing, changing fast, they're growing. And our model was built to build capacity in advance, but not to pre-sell it in advance. And that is why we have this available capacity now that can allow us to allocate it to shorter-term and much higher margin contracts. The second example would be, as I mentioned, we also launched our first auction this quarter. This is the auction for the midterm contract. Why we were able to do so? Because again, we had free unallocated capacity and we had our multi-tenant platform. And We're just realizing the benefits from it. And we have similar flexibility on the capacity front. And again, it's a strategic advantage of the platform we have. The fact that our platform is universal and able to work on any third-party capacity gives us an opportunity to grow even faster. And this is what our asset-light model is all about. So we see there are multiple ways to monetize the universality of our full-stack platform on both software and hardware part of it. And the way we think about all of this is simple. This market is going to continue to move quickly and to grow quickly, and we will be sure that our business model and platform will stay flexible to allow us to capitalize, to use all this growth.

Thanks, Arkady. Our next question comes from Arsenij Matovic from Wolfe Research and was emphasized by many others from our portal. Relates to our new $775 million asset-backed financing. Debt markets have been volatile and all-in costs have generally moved higher. Are you still comfortable leaning on debt from here, or should we expect greater use of equity through the ATM, or perhaps a convertible? Dado?

Thank you, Arsenije. Well, our approach is not about making a call on the markets. Really, our approach is to match the right financing instrument with the right assets, while remaining disciplined about 3 things: our cost of capital, minimizing shareholder dilution, and maintaining a strong and healthy balance sheet. Our first sources of capital remain customer prepayments and operating cash flow. We expect more than $9 billion of upfront customer prepayments in 2026. Clearly, this directly reduces the amount of external financing we need as we continue to scale. Beyond that, asset-backed financing is an important part of our strategy. The $775 million facility we completed in July priced at SOFR plus 250 basis points, was backed by deployed GPUs infrastructure and contracted cash flows from an investment-grade customer. It demonstrated that even in a more volatile market, there is strong demand to finance these contracted cash flows on attractive terms. And look, with more than $40 billion of committed backlog, We believe this is a highly scalable and repeatable financing model. Obviously, we expect to continue accessing this market as we deploy additional capacity. And also beyond asset-backed financing, we have significant flexibility. We currently have almost no corporate-level debt, so that represents an additional source of capital that we can evaluate as the business scales. Equity and equity-linked financing, such as the ATM or potentially convertibles, offer additional sources of funding, and we evaluate those alongside all of our other funding options as a source of capital. We are actively considering further equity-linked and asset-backed financing options and continue to evaluate corporate-level debt and other financing alternatives. So, overall, we remain very comfortable with our funding position. So, we do have multiple sources of capital available to us, and we will continue to optimise across them with a focus on cost of capital, limiting dilution, and maintaining a disciplined balance sheet.

Thank you, Dado. Our next question comes from Tyler Radtke with Citi. And Mark, this one is for you. How do you think about the mix of allocating 2027 capacity between short-dated capacity versus multi-year deals? Is there a threshold of ACV per megawatt you are waiting for on the longer-dated deals to sign into those?

Thank you, Tyler. Before I dive in, let me just make sure and clarify the deals with a little bit more nuance, the type of deals that we're doing with a little bit more nuance. Our long, our medium-term or midterm contract durations are most, for the most part, our AI cloud customer agreements. And that's our core of our business. And that's where we're locking in strong unit economics with some of the world's most ambitious AI companies. And then separately, as you called out, we have the shorter-term opportunities and durations, and these are premium deals. And that includes, as an example, the auction that we described today, as well as the ability to capture sort of the shorter-term scale contracts that we mentioned. In practice, what we strive to do is to optimize across customer type, price, payment structure, duration, and deal size, rather than strictly looking at a single variable or a compiled metric. Our current emphasis is taking care of existing customers, followed by new logos, and then terms— terms in order of priority, including price, then upfront prepayment, then duration. So, a bit wider than purely ACV per megawatt. We have We have also, at the same time, tactically shortened how far in advance we sell capacity. So, in effect, selling closer to deployment, which at the end of the day has improved the pricing that we can derive while preserving our agility. We're deliberately allocating a portion of capacity for short-term and immediate needs, because that is where we currently see the highest potential for combined realized value. To summarize, as we deploy capacity looking towards the latter half of this year and into next year, we will allocate across both medium and short-term deals using this with our customer and terms lens that I mentioned earlier.

Thank you, Mark. This next question comes from James Kisner at Watertower. XAI has begun selling compute at premium prices. What does that say about market pricing for AI capacity, and are you seeing similar strength on new contracts and renewals? What does this mean for Nebius?

Probably I will take it. It's Arkady. Definitely we don't see any change here from Nebius or our plans to change. We are playing on the basically on the same market as the three big hyperscale clouds. The whole AI cloud market is growing. Massively from hundreds of billions of dollars per year to probably a trillion, some people say more. And there is no doubt that the main existing players will continue to grow with the market, right? But there is also definitely, there is an opening for the new entrants, for the independent players, Like us, and yes, we want to build a gigawatt capacity per year. Yes, there is not so many companies doing that. The numbers look great, big, but the market as a whole is growing by tens of gigawatts per year. It's like multiple of order larger, and. The hyperscalers are those who build a lot of this, but even them, they definitely cannot build all of it. And somebody needs to help them to build. And that's not us. Somebody, because somebody needs to build the rest of the market. And that will be us. This is our part. And this is where we see the biggest opportunity for us. So, coming back to the question, new players coming to the market don't change the market for us. They actually just, I think, validate the market.

Thank you, Arkady. Our next question is from Rob Oliver from Baird. Is your strong positioning in open weight driving increased inference among clients? Roman, this one's for you.

Yeah, thank you, Gillian, for the— and thank you for the question. Uh, first of all, we believe that customers, businesses, and even society benefit from competition and diversity. Uh, we were committed to an open AI ecosystem from the beginning of the company and providing open infrastructure without lock- So customers get flexibility, control over their data and models, freedom in how they deploy. And at scale, the economics matter. Companies at the frontier of adoption, of AI adoption, are seeing the cost of token consumption and asking, can AI not only solve the task, but but do so with economics that allow to scale. And another important question is how to extract value from specialized knowledge and data held within enterprises and where there are people and convert it into better performing AI systems. Everybody is saying that data is the mode and maybe the only mode. All of these is driving companies towards more specialized models. Open-source models are valuable not simply because they are available, but because they can be tuned, trained, and eventually optimized for a particular use case of a particular customer, particular business. What has changed is that the quality of open models is improving rapidly. At the same time, the industry is moving toward the flexibility and control that we built from the start. So Token Factory provides day-zero support for frontier open models, and the velocity is just crazy. If you look just in the last 4 weeks, we got Nemotron Ultra, GLM 5.2, Kimi K3, new DeepSeek Flash, MiniMax 3. Today, new Neutron Lightning was released, but availability alone is not enough. We are building the capabilities to serve these models without compromising quality, cost, and performance. Let's take GLM 5.2 as an example. Some people call the moment when this model was released, the DeepSeek Moment 2. Our implementation achieved a 100% quality score and leading performance validated by independent benchmarking and Artificial Analysis. That positioned us in a great spot to grow and drive the demand to open source models that we see at the market now.

Thank you, Roman. A follow-up from Rob. Can you provide any early color on the asset-light offering, early customer engagement, and how the economics look for you versus your core? Arkadiy, do you want to take this one?

Yeah. Yes, first of all, Well, we're growing globally, but we're still a startup and we should be very mindful about where we invest our own capital. We can't go into all markets instantly and simultaneously. That's why we're very open to working with partners and our platform allows us to do so. After we announced our asset-light model, we have had dozens of inquiries from potential partners who have significant capacity and enough capital but don't know how to build and how to sell it. With GPU increasingly becoming an investable asset— look at the recent news— we expect more and more companies who will want to come to the market but will need our help to deliver this capacity to customers. By having the right tech platform and access to the market, we can help them. So this is actually exactly what we can easily offer to them, and that's why this asset-light The model is still in very early stage, but we are very much encouraged by early signs and think that it has a great potential.

Thank you, Arkady. Our next question is from Ryan Lountis from Morgan Stanley. Dado, you've said you could sell your entire 2027 capacity today. How should investors frame 2027 across capacity, pricing, and revenue, and will you When will you formalize an outlook?

Thank you, Ryan. This is probably one of the more interesting questions for investors on this call. You should expect the deals we closed in this quarter, with more than $20 million per megawatt yields and less than 2-year payback period, to start coming online from late Q4 and onwards. This can serve as the baseline for pricing early next year, As we could have sold out our planned capacity already today. However, we are choosing not to do so, reflecting our confidence with respect to future pricing dynamics. But also, capacity obviously is a major part of this equation, and we are going to deploy significantly more capacity in 2027 than what we have already done in '26 and what we are going to do still in '26. The dynamics we expect across both capacity and pricing make us extremely excited about 2027, although we will provide formal guidance later this year. And don't forget that in addition, we expect our asset-light model, along with high-value services such as agentic and inference solutions, to contribute an increasing share of revenue while supporting even higher margins.

Thank you, Dado. Our next question is from Brett Knockback at Cantor. Do we still expect to end the year with 800 megawatts to 1 gigawatt? Do you—

I see—

Andrey, do you want to take that for us?

Yeah, absolutely. Yes, we still, well, we still expect to meet this guidance from 800 megawatts to 1 gigawatt of connected power this year. And, but, and also there was a part about the Vineland included in 2027? No, the Vineland is the part of 2026 capacity and connected power. What I wanted to say is that connected power represents the data centers. And there are a few steps coming from the data centers to the revenues. You have to commission the data center, build the network, build the clusters, deploy the platform, then onboarding the customers. and then the revenue generation starts. So that takes a few months and depending also on the generation change of the GPUs probably. And so there's a gap between the connected power and the revenues coming. And in terms of our guidance from 800 to 1 gigawatt, yes, that's more or less, that's true about the connected. it, but I would think that about being active in throughout the first half of 2027.

Thank you, Andrey. We also have a question from BNP Paribas from Stefan Slowinski, specifically around our $40 million per megawatt monetization in Q3. Is this reflective of initial pricing from selling Vera Rubin capacity? Andrey, do you want to talk about the ramp of Vera Rubin capacity?

Yeah, absolutely. So we have Vera Rubin in our labs for quite a while already, and we already are getting the results, the expected results with the Vera Rubin So we, first of all, I wanted to mention that step between the Grace Blackwell and Vera Rubin is somewhat easier from the technical perspective than step from the previous generations to the Grace Blackwell. And we expect to start deploying the Vera Rubin late this year or early next year. And continue throughout the full next year.

Yeah, and to the first part of that question, and we're getting a lot of questions from the portal on our new go-to-market motions. So, Mark, I think that that will be a good topic for you. We piloted both a capacity auction and short-term scaled training deals since quarter end. Walk us through the strategy behind these motions, what they told you about pricing, and are they still take-or-pay?

Thank you, Keeley. By now, I think we can all agree that the market is incredibly dynamic and moving rapidly, and we are constantly looking for ways to discern signal and understanding in order to deliver a better and more complete understanding of our take-or-pay business. Now, we launched these initiatives to first and foremost learn and validate while building our customer relationships in a disciplined way. What we described earlier as short-term scale training capacity deals are specifically customers that are looking for dedicated scale, in this case GB300 clusters, for 3 to 6 month engagements at a premium. These customers have specific requirements. Like time-boxed large-scale training runs ahead of a model release or reinforcement learning post-training sprints. In the model world, we hear over and over again, weeks matter, and so does access to reliable, performant AI compute. These customers are willing to pay for speed and certainty for a controlled span of time. Now, on the other hand, the auction is all about clear price discovery. In today's environment, the price in the market can change literally as we move through a sales cycle. The challenge is to get a solid gauge on the fair value of our offering at any moment in time. The standard reference points— competitor pricing, Analyst opinions and even prediction markets are all over the place. In a market where we have several buyers for every GPU, we let the market tell us directly. The auction result was a price 15% higher than we've ever seen before and 20% higher than our pipeline for Blackwell. Also, the winning bidder is thrilled with the experience. They called out specifically the combination of validated pricing and the certainty of access to the compute they need. Also, they told us they plan to participate in future rounds. So what you should take away is that these are both customer value confirming and independently lucrative. We are using a small portion of our overall capacity to drive price discovery and value-validating initiatives, and will help— these will help us to evaluate our capacity and the market as we move into '27. They will both have a broad impact across our pricing, packaging strategy, deal negotiation, and they inherently have faster close-to-deployment cycles.

Thank you, Mark. We're getting a lot of questions around the deployment of more than 1 gigawatt of new capacity starting in 2027. Dado, can you talk us through how we're planning on funding this CapEx at scale, and how do we prioritize our funding sources?

Absolutely. So, what is important to understand is is actually that we have multiple pools of capital available to fund our growth, and we are very comfortable with our ability to finance the capacity we plan to deploy in 2027 and actually beyond. Clearly, the first source is operating cash flow. We are already generating positive operating cash flow and expect this to increase meaningfully as the business scales. Then, we have our customer prepayments. The terms we secured in Q2 cover approximately 50 to 60% of associated CapEx. But going forward, one of our objectives is to increase this coverage even, even further. Third, our long-term contracts with investment-grade customers give us a very strong base to raise asset-backed financing on attractive terms. We currently have approximately €40 billion of committed backlog that we can borrow against, and we began utilizing this source of financing already in Q2. But beyond that, we have additional flexibility through corporate-level debt and equity-like financing, which we have not yet meaningfully tapped. We will continue to balance these sources in a disciplined way, to maintain a strong balance sheet as we scale. But we also see financing opportunities that are additional to those emerging around GPUs as an asset class. We have seen increasing activity in an interest in financing GPUs as standalone assets, and we are strong believers in the potential of this market. Over time, this could provide us with another attractive source of funding. Overall, we are really very comfortable with our balance sheet today and confident in our ability to finance our growth in '27 and beyond through this diversified funding strategy while maintaining financial discipline.

Thank you, Dado. The next question is from one of our investors on the portal. Roman, what are we seeing in the market around token maxing, and is that having an impact on usage or adoption of Token Factory and Tavily?

Yeah, thank you for the question. First of all, I wanted to start with a reminder about our first Inflection event that we held in June. And probably that was the first time when we publicly described our product strategy where we built layer by layer the AI cloud to meet developers where they need us from scaled bare metal infrastructure to the agentic layers. And the obvious trend is that AI systems are moving into the production. Coding is the most visible example. But this is not limited to coding. We see long horizon agentic workflows in financial services, such as use cases at Revolut and Mastercard, e-commerce applications improving the customer experience and process and Shopify and many more. For example, Sword Health in healthcare or Higgsfield in marketing automation. And other verticals. We also, as always, customer zero for ourselves. EHO, our own infrastructure agent shipped at the last cloud release, runs an open-source model served by Token Factory. The challenge that we see for the customers is scaling complex systems that combine multiple models models, inference engines, and tools. We help solve this with our suite of services, including Token Factory for reliable high-performance inference and post-training, and Havidia for grounding, particularly as companies move from closed ecosystems with built-in search towards more open ecosystems. EigenAI and Clarify teams are fully integrated into Token Factory effort and already shipping inside our roadmap. We see day-zero support for the major open model launches, measurable performance optimization post-launch, and independent benchmarks, as I said earlier, continuing to rank us among the leading inference platforms. Q2 was also Tavily's first full quarter within Nebius. Its developer community grew to more than 2.5 million developers from 1 million in February, and it launched keyless paper search built for autonomous agent consumption, and it achieved, uh, the set of certification for enterprise deployments. We also see more customers post-train their own models, creating additional demand for inference and grounding throughout throughout the development cycle, not only in production. Reinforcement learning rollouts, evaluations, synthetic data generations, and grounded training workflows all require significant inference capacity and reliable access to external information. These trends validate our strategy of building a vertically integrated platform that delivers attractive total cost of ownership and supports diversified workloads. We want to serve customers across the full AI lifecycle, from training and post-training to inference and grounding. This is where our infrastructure and software come together as a strong offering, and we are only getting started. New workloads are bringing new requirements to the physical infrastructures. well. And again, we can address them as we build the full stack. And not only bringing new generations of GPUs that Andrej mentioned, uh, agentic orchestration, tool calling, and data preparations are CPU heavy. So we are aiding ARM and CPU deployments alongside the GPU fleet.

Thank you, and that concludes our earnings call for today.

This concludes today's call. Thank you, everyone, for joining. You may now disconnect.