All MARA transcripts

MARA Holdings, Inc. (MARA) Q1 2026 Earnings Call Transcript

30 segments

Prepared remarks

OperatorOperator

Greetings, and welcome to the MARA First Quarter 2026 Earnings Conference Call. As a reminder, this conference is being recorded. It is now my pleasure to introduce Robert Samuels, Vice President of Investor Relations. Thank you. You may begin.

Robert SamuelsVice President, Investor Relations

Thank you, operator. Good afternoon, everyone, and welcome to MARA's First Quarter Fiscal Year 2026 Earnings Call. Thanks for joining us today. With me on today's call are our Chairman and Chief Executive Officer, Fred Thiel; and our Chief Financial Officer, Salman Khan. Today's call includes forward-looking statements, including those about our growth plans, liquidity and financial performance. These involve risks and uncertainties, and actual results may differ materially. We disclaim any obligation to update these statements, except as required by law. For more details, see the Risk Factors section of our latest 10-K and other SEC filings. We'll also reference non-GAAP financial measures like adjusted EBITDA, which we believe are important indicators of MARA's operating performance because they exclude certain items that we do not believe directly reflect our core operations. Please see our earnings release for reconciliations to the most comparable GAAP measures. We hope you've had the chance to read our shareholder letter and look forward to your feedback. We'll begin with some prepared remarks from Fred and Salman. After their comments, we will open the call to Q&A. I'm going to turn the call over to Fred to kick things off. Fred?

Frederick ThielChairman and Chief Executive Officer

Good afternoon, everyone, and thank you for joining us. Q1 2026 was a redefining quarter for MARA, not an incremental one. This was a quarter where we executed deliberately across multiple fronts at once and moved the company decisively forward. During the quarter, we moved the Starwood joint venture from announcement to execution, closed our acquisition of a majority interest in Exaion and retired about 30% of our outstanding convertible debt, all while realigning the organization to fit the business strategy. Shortly after quarter end, we announced a definitive agreement to acquire Long Ridge Energy & Power from FTAI Infrastructure. These were not isolated events. They are connected pieces of a strategy that is now fully in motion. That strategy starts with a single conviction: the next phase of digital infrastructure value creation will be shaped by the control of power, where it is located, when it's available and how it can best be monetized.

AI adoption is accelerating faster than power can be brought online to meet demand. That is not an opinion. It's the defining constraint of this market. Available connected energy is the bottleneck on AI compute growth. The ability to source, control and dynamically allocate that power is a structural advantage. And the lack of available power will negatively impact semiconductors related to AI if there's not sufficient capacity to absorb chip supply. Some semiconductor vendors are investing directly and locking up demand as evidenced by NVIDIA's recent investments. MARA has positioned itself squarely in the bull's eye with already energized power to enable hyperscalers to, in the near term, energize compute with our previously 1.9 gigawatts of power capacity and now with the addition of Long Ridge, we're having advanced conversations with multiple prospective tenants across multiple sites.

Let me start with Long Ridge. We view Long Ridge as a land and power acquisition to develop a premier compute campus. It is a strategic enabler for our existing Hannibal operations, adding to the site 1,600 acres with a path to grow the existing 200 megawatts of power to over 1 gigawatt. It will establish a leading AI HPC data center campus in the PJM interconnection, one of the most active data center and power markets in North America. In a market where power and infrastructure constraints take years to solve, Long Ridge gives us exactly what is needed to deliver value to shareholders upon closing. This is not a greenfield site. It is a site that is already operational, already generating cash and that gives us immediate access to the infrastructure, interconnection and physical footprint required to scale to over 1 gigawatt. The power is there, the land is there, the water is there, the fuel supply is there and the interconnection is there.

The centerpiece of the campus is an approximately 505-megawatt nameplate combined cycle gas turbine, one of the most efficient in the entire PJM Interconnection. It generated $144 million of annualized adjusted EBITDA in the second half of 2025 with 76% contracted capacity. This is stable, visible cash flow from the moment we closed the transaction. Beyond the power plant, the campus consists of over 1,600 contiguous acres and includes the 200 megawatts of MARA's existing capacity at Hannibal. As of signing, we have already submitted plans to augment the Hannibal interconnect, and we will move quickly post close to further expand power capacity at the power plant. At close, we plan to retain Long Ridge's skilled team consisting of about 25 full-time employees that have deep operational knowledge of the facility. They will supplement our existing energy asset operating expertise. Here's what matters most about the scarcity of this asset.

If you try to build this from scratch today — the land, the power, the permitting, the water, the interconnection — you're looking at $2 billion to $3 billion of capital and 7 to 10 more years of development time. We're stepping into a platform that is already built, already operational and already generating cash flow. Assets like this are very hard to come by. Some might even call it a unicorn. So when they do, you move. In total, Long Ridge gives us over 1 gigawatt of total potential capacity and a path to scale to 600 gross megawatts of AI and critical IT load over time. This transaction increases our owned and operated capacity by approximately 65%, taking us from about 1.3 gigawatts of energized capacity today to roughly 2.2 gigawatts by closing and including expansion capacity to 2.4 gigawatts. We've been actively engaged with multiple top-tier potential tenants around this asset.

These conversations are now accelerating since announcing this transaction. And the current plan calls for an initial 200 megawatts of AI build-out with construction beginning around the first half of 2027 and initial capacity coming online in mid-2028. The power plant is not the end product, it's the enabler. It provides reliable control over an increasingly scarce input at a cost of approximately $15 per megawatt hour. This is a cost position that very few can match as well as a positive cash flow tomorrow. And to be clear, our existing Bitcoin mining operations at Hannibal will continue without interruption until such time as the data center campus needs the power. MARA does not expect to reduce Long Ridge's current supply of power into the PJM grid. As we develop compute capacity behind the meter, we will pair that demand with incremental generation over time. Our goal is to continue to operate Long Ridge Energy and ensure that consumers continue to benefit from the reliable power they have been accustomed to.

Taken together, Long Ridge gives MARA a scaled power advantage platform, immediate and durable cash flow and a clear path to build one of the leading digital infrastructure campuses in this market. Next, I'd like to talk about our strategic partnership with Starwood, which has made meaningful progress during the quarter. We moved from announcement to execution, advancing permitting and site preparations across our portfolio and entering active tenant discussions with multiple counterparties, including hyperscalers across 90% of our existing owned and operated sites, including the Long Ridge campus. I want to take a moment to explain why the structure of this partnership matters because it's fundamentally different from a traditional lease and that distinction has real economic benefits for MARA and its shareholders. First, Starwood is a trusted institutional counterparty with global investment expertise and a dedicated data center development platform.

Their team has developed, built and put into operations more than 7 gigawatts of data center capacity worldwide for premier tenants. This means Starwood is a trusted counterparty having negotiated multiple leases with premier tenants, which we believe accelerates the timeline for site evaluation and lease signing, something we have already seen. Second, Starwood brings captive development and EPC capabilities. They lead design, development, construction and facility operations, giving MARA an experienced execution partner without having to source and manage third-party contractors. Additionally, their prior experience for constructing sites for premier tenants provides an enhanced certainty regarding their ability to develop on tenant timelines and technical requirements. This trust factor provides prospective tenants more confidence that their timelines and specifications will be met. Our peers who have never done this before still need to build trust with prospective tenants because they lack a proven track record.

Third, the structure is capital efficient. When MARA contributes a site, its value is determined using pre-agreed site-specific economics tied to power, land, interconnection and development attributes. That value gives MARA equity credit in the project before joint venture cash contributions are required. To put this in context, on an illustrative 200-megawatt project, MARA could generate approximately $50 million to $100 million of net annualized stabilized cash flow based on a 9% to 15% yield on cost range with little to no incremental equity required beyond the value of the site we contribute. As projects scale, the structure naturally evolves; MARA's site contribution is fixed. So for larger developments, the incremental growth capital becomes more proportionate between the partners. At that point, the funding model starts to look more like a traditional data center development structure, including the use of construction financing that can support roughly 80% loan-to-value.

The key point is that this model allows MARA to monetize the value of its powered land portfolio, preserve significant upside in long-term cash flows and manage capital exposure in a disciplined way. Most critically, this is not designed to be a one-time transaction. As we continue to aggregate land and power assets, our goal is to contribute sites into the structure repeatedly. Starwood is a capital-efficient engine for turning MARA's powered land portfolio into contracted institutional-grade digital infrastructure at scale. We expect to sign multiple tenant leases by year-end. And as the pipeline converts, we'll disclose contracted megawatts. While the Starwood joint venture addresses the large-scale hyperscale end of the AI infrastructure market, Exaion addresses a different but equally important segment, sovereign, enterprise and private cloud AI compute. Together, they give MARA two distinct pathways into AI, both grounded in the same foundation of energy-backed infrastructure, both serving real and growing demand.

Governments and enterprises, particularly across Europe and Canada, are increasingly unwilling to rely solely on hyperscale platforms for their AI infrastructure due to data sovereignty and cost. They want control over compute, data autonomy, jurisdictional compliance, security and independence. This is not a niche requirement. As AI policy evolves and data sovereignty standards tighten, a meaningful share of AI workloads will require infrastructure that is compliance-ready, jurisdictionally controlled and trusted. Exaion is built to serve exactly that demand. We continue to build on our proven success in UAE, Finland and our recent launch in Oman. We are in active discussions with major energy companies in France, Brazil and Saudi Arabia across energy-rich regions where reliable, scalable power supports long-term digital infrastructure development. We are still early, and we will share a more detailed roadmap as this effort develops.

The simplest way to think about it is Starwood and Exaion are different expressions of the same thesis. The JV pursues large-scale colocation for hyperscalers. Exaion pursues private cloud, sovereign AI and enterprise deployments in regulated markets where these are critical criteria. Both depend on MARA's core capability of controlling and monetizing energy-backed infrastructure. Together, they expand our addressable market across two large and growing segments of the AI infrastructure opportunity. Finally, Bitcoin mining is the operational foundation we're building from. Our strategy is to co-locate new infrastructure with our existing mining operations. This allows us to monetize power assets immediately while building on the operational discipline and infrastructure expertise that mining demands. Mining generates revenue today. It preserves the option to redirect capacity toward AI and critical IT loads as those opportunities mature on the same sites.

That flexibility is deliberate. It's not incidental to our strategy. It is central to it in that it allows us to best monetize our power and compute. We continue to believe Bitcoin is supported by institutional demand. In our view, that creates a constructive setup over time with a bias to the upside if institutional buying continues and retail demand returns. We continue to believe Bitcoin will appreciate beyond its current levels. We also took deliberate steps to strengthen the balance sheet during the quarter. We retired about 30% of our outstanding convertible debt at a discount, reducing potential dilution and increasing our financial flexibility. This was a decision to reduce the capital structure's drag on equity value and give us greater capacity to pursue the highest return opportunities across the business with discipline and without being forced to dilute shareholders. With that, I will turn the call over to Salman to walk through the financial results.

Salman KhanChief Financial Officer

Thank you, Fred. Good afternoon, everyone. Before I walk through the quarterly results, I want to briefly frame the first quarter of 2026 from a strategic and financial perspective. This was a quarter in which we strengthened the balance sheet, reduced potential dilution from convertible notes by as much as approximately 46 million shares or 9% on a fully diluted basis and continued to align our capital allocation with the strategy. As Fred outlined, we are converting MARA's digital infrastructure with lower cost, large-scale energy capacity into AI and critical IT. Two initiatives are central to that strategy. First, our recent announcement to acquire Long Ridge adds one of the most efficient energy-backed compute campuses with existing cash flows, owned generation, existing interconnection, low-cost vertically integrated power generation complex and a significant development opportunity over time.

This acquisition is next to our existing Bitcoin mining site and is expected to expand our AI expansion in an AI-rich corridor. As we pursue the regulatory approvals and seek consent from Long Ridge debt holders, we believe Long Ridge will provide near-term diversified financial performance while unlocking significant long-term contracted digital infrastructure revenue. Second, the Starwood joint venture gives us a capital-efficient path to monetize the value of our sites by converting them to AI, HPC and critical IT workloads. It is important to note that in our joint venture structure with Starwood, MARA contributes a site into the joint venture once the tenant is signed, for which we receive credit based on the site's power, land, interconnection and development attributes at predetermined value, as Fred mentioned earlier. That is the power of the joint venture model. It allows us to convert the embedded value of our existing infrastructure into meaningful ownership in large-scale digital infrastructure opportunities while significantly limiting the incremental capital required from our balance sheet, giving us a higher return on capital than our peers.

Now let me turn to Bitcoin price in Q1. This was a challenging quarter for the Bitcoin price and reflected broader pressure across risk assets. The decline was driven by a combination of macro uncertainty, tighter risk appetite and continued pressure on mining economics. For MARA, that backdrop reinforces the importance of operating discipline. We remain focused on fleet efficiency, cost control and capital allocation rather than pursuing growth for growth's sake. Since quarter end, Bitcoin has rebounded meaningfully, increasing approximately 20% from its March 31 closing price. While volatility remains inherent to this asset class, the recovery reinforces the value of maintaining Bitcoin as both a reserve asset and a source of strategic financial flexibility. With that context, I'll turn to our Q1 financial performance, capital allocation and balance sheet activity. Revenues in Q1 of 2026 were $174.6 million compared to $213.9 million in the prior year period.

The decline was primarily driven by an 18% decrease in Bitcoin's average price, which reduced revenue by $33.1 million and to a lower extent, impacted lower production, which accounted for approximately $2.5 million. In addition, other revenues declined approximately $3.7 million, primarily reflecting lower revenue from other digital asset hosting services compared to the prior year period. During the quarter, we delivered record energized hashrate of 72.2 exahash per second, increasing 33% from 54.3 exahash per second in Q1 of 2025. This growth reflects continued fleet optimization and the deployment of approximately 2.4 exahash of new generation ASIC miners at favorable pricing during the quarter. Our share of available mining rewards reached 5.5%, up from 4.8% in Q4 of 2025. We mined 2,247 Bitcoin or 25 Bitcoin per day in the first quarter of 2026. That is approximately 39 fewer BTC than prior year period, reflecting a higher network difficulty level, partially offset by our higher hashrate.

We reported a net loss of $1.3 billion or $3.31 loss per diluted share this quarter compared to net loss of $533.4 million or $1.55 loss per diluted share in the first quarter of 2025. Approximately $1 billion of this net loss for the first quarter of 2026 was driven by unrealized mark-to-market fair value adjustment for digital assets, a direct reflection of the drop in Bitcoin price during the quarter. A reminder that based on our current Bitcoin holdings, every $10,000 change in Bitcoin price results in an approximate $350 million impact on fair value of digital assets, which is an unrealized mark-to-market adjustment to our income statement. Adjusted EBITDA for the quarter was negative $1 billion compared to negative $483.6 million in the prior year period. Similar to net loss, this figure is dominated by the Bitcoin mark-to-market change. We use adjusted EBITDA as a supplemental measure of operational performance.

A full reconciliation to net loss is included in our shareholder letter and earnings deck. On the cost side, our cost per kilowatt hour was $0.04 for our owned sites in the first quarter of 2026. For context, we believe this remains among the most competitive in the sector at a larger scale. Our purchased energy cost per Bitcoin for the quarter for our owned mining sites was $40,047 in Q1 of 2026 from $35,728 in Q1 of 2025, primarily due to higher network difficulty driven by growth in global hashrate. This resulted in an 8% decline in Bitcoin production at our own mining sites compared to the prior year period. Our daily cost per petahash per day improved 3% year-over-year to $27.6 from $28.5 in Q1 of 2025 and over the past 11 quarters has improved by 42%. We believe this remains among the lowest at scale in our sector. In the first quarter of 2026, general and administrative expense, excluding stock-based compensation, was $57.7 million compared to $36.9 million in the prior year period.

The increase reflects the scaling of our operations, higher personnel costs associated with headcount growth from the prior year period and administrative fees in support of our expanded global footprint through acquisition and integration costs. Acquisition and integration costs burdened our G&A by $11 million for the first quarter of 2026. As part of our strategic shift towards AI and critical IT, we have realigned our business operations and reduced workforce by 15%, providing combined annualized savings of $12 million. This was a difficult but strategic decision. In addition, we incurred a restructuring charge of $45.9 million due to elimination of certain business initiatives and realignment. The organization focused on scaling Bitcoin mining is different from the one required to build a digital infrastructure company. This realignment positions the company to pursue AI opportunities, as Fred discussed earlier.

Following this restructuring, we expect our quarterly G&A run rate, excluding stock-based compensation and acquisition integration costs to trend below the Q1 level as these savings are realized over time. Now let me address deleveraging our balance sheet and our recent Bitcoin sales. During the quarter, we retired approximately 33% of our outstanding debt, which included 30% of convertible notes reduction at a discount. This reduced potential future dilution, lowered leverage and improved our ability to allocate capital towards high-return strategic opportunities. We funded a portion of this debt reduction through Bitcoin monetization. Bitcoin is not only a reserve asset on our balance sheet, it is also a source of strategic financial flexibility. We will continue to deploy it thoughtfully when doing so creates measurable value for shareholders and intend to use it selectively to strengthen the balance sheet and fund strategic priorities.

During the quarter, we sold approximately $1.5 billion of Bitcoin. These funds were used to repurchase at a discount over $1 billion of face value of our 2030 and 2031 notes and reduced our line of credit by $200 million. In addition, we refinanced $150 million of our line of credit at a 7% interest rate versus 10.5% previously. I also want to highlight that we have not used our at-the-market equity offering program, or ATM, since the end of the third quarter of 2025. We have funded operations and balance sheet actions through Bitcoin monetization, not equity dilution. We think this is an important data point for shareholders as we continue to allocate capital towards the highest return opportunities. Now let me discuss our Bitcoin holdings. We held a total of 35,303 Bitcoin at the end of the quarter, a decrease of 12,228 from the previous year. Of the total, approximately 28% of the holdings were activated as loaned or pledged as collateral.

The loaned Bitcoin generated approximately $6.4 million of interest income over the first quarter of 2026. Finally, I want to provide additional clarity on the pro forma capital structure we expect to have in place at Long Ridge upon closing the acquisition. Long Ridge's $400 million term loan is expected to be repaid at closing. We are also currently conducting a consent solicitation to waive the change of control provision in Long Ridge's $600 million secured notes, which would allow the notes to remain in place. The $115 million Can-Am facility is similarly expected to remain in place. As a result, total pro forma debt at Long Ridge is expected to be approximately $900 million, down from $1.1 billion previously, with approximately $185 million of tack-on secured notes expected to be issued. We expect to fund the remaining consideration through a combination of cash on hand, borrowings collateralized by Bitcoin and potentially proceeds from the sale of Bitcoin, depending on the market conditions at the time of closing.

We have also secured a $785 million commitment letter backstopped by a bridge loan from Barclays in case needed. We have a plan in place to finance this acquisition, and we are very excited about Long Ridge, what it will bring to MARA and our stockholders. With that, I will turn it back to Fred.

Frederick ThielChairman and Chief Executive Officer

Thank you, Salman. The actions we've taken so far this year were purposeful and they were interconnected. The Starwood joint venture creates a capital-efficient path to convert our power portfolio into AI infrastructure ownership. Long Ridge adds a differentiated power advantage platform for a premier AI and critical IT campus anchored by our existing Hannibal operations. Exaion gives us a second pathway into AI, sovereign and private cloud domestically and internationally. Balance sheet actions reduce dilution risk and increase our financial flexibility, and Bitcoin mining remains our foundation. We recognize that the market is focused on demonstrated execution, signed contracts, contracted megawatts and tangible proof that this strategy converts into shareholder value. MARA is redefining itself as a digital infrastructure company, controlling and monetizing electrons to their best value across multiple compute markets. This transition is already underway. Q1 2026 was a meaningful step forward. With that, I'll turn the call over to the operator to open it up for questions.

Questions and answers

OperatorOperator

And now we will open the call to Q&A. Your first question comes from Paul Golding with Macquarie Capital.

Paul GoldingAnalyst (Macquarie Capital)

Congrats on all the progress this quarter. I wanted to ask, at a high level — and maybe this is for Fred — as you think about the approach to expanding on the HPC strategy, on the one hand you've got multiple tenant prospects across the portfolio of existing sites and through the Starwood JV; and on the other hand you also did an opportunistic deal to acquire the Long Ridge asset. How should we think about your broader strategy between commercializing existing sites and adding capacity through these opportunistic deals? Was Long Ridge sort of a one-off because of the relationship and it coming to market? Or is this potentially a simultaneous approach that we should see unfold between assets coming to market that you would look to acquire versus the existing portfolio?

Frederick ThielChairman and Chief Executive Officer

Yes. Great question. So the Long Ridge deal has been in the works for quite a long time since we acquired the Hannibal asset originally actually. The site, obviously, Long Ridge provides us with the land that we need to be able to build a true premier campus. And the original intention with the Hannibal site was to build a much bigger data center facility. And it just took a long while for the respective parties to reach agreement on a deal here, and we obviously had to take it to market through a process to ensure that they were doing the right thing for their shareholders. But that has been a deal that's been in the works for quite a long time actually. I think going forward, what you should see is you can think of us as doing — focusing on a combination of small sites, which are perfect tuck-ins. We recently added a smaller site earlier at the end of last year, for example, which is now operational as a mining site, which has the opportunity to potentially convert into a smaller token factory facility if we wanted to do that with that site.

At the same time, we're going to continue to look for larger land and power opportunities where we can build significant campuses together with Starwood. We really have the best of both worlds here because the large-scale opportunities, having Starwood as a partner does really a wonderful job of derisking the whole process and ensuring that we're able to execute properly. At the same time, at the smaller-scale sites where we know how to develop smaller sites, especially as you start looking in the world of inference, where a lot of this is moving to ASIC technologies away from NVIDIA's traditional GPUs. Those facilities now are able to operate more in modular data center formats, which are more akin to what we've been doing all along with Bitcoin mining where all our sites operate as kind of modular data centers. And so we believe building this duopoly, if you would, of being able to develop smaller sites that specifically service inference needs for a variety of potential tenants or end customers as well as doing the larger sites with Starwood is a way that we'll be able to build a beautiful portfolio of assets that will provide long-term value to our shareholders.

Paul GoldingAnalyst (Macquarie Capital)

Maybe just as a quick follow-up. I was wondering if I could pull on that inference versus training thread a bit. Are you able to share any detail around the general mix of interest right now from these prospects? Is it indexing more towards the inferencing use cases? Or is it more towards training or equally distributed?

Frederick ThielChairman and Chief Executive Officer

Sure. So when you generically use the word hyperscaler, you're typically talking about somebody who has large amounts of data that they have collected that they train a model on that they then use that model to do things. Amazon, Google, Microsoft use data they have to essentially do inference — train a model and then do inference on that model. So you have a lot of those sites that are a combination of training and inference. If you've been following what Jensen and NVIDIA has been talking about, his belief is that these training sites will, over time, do more and more inference. I think the models going forward, you're going to see a need for sites where people can deploy models that they have done in-house and run them. These are the token factory sites, which I think we're going to see a lot more of where essentially somebody needs the ability to run a handful of megawatts of model scale.

We're starting to see already financial players — meaning non-data center players — wanting to now have data center capacity that they can use for it; it could be financial trading, it could be healthcare data, it could be other things where the ability to develop models and run your business using these models has become mission-critical. Therefore, you don't want to put it up in the cloud; you want to do it in your own private cloud. And so this is where Exaion marries to this model very attractively. We're able to engage with any tenant across whether they want traditional large hyperscaler sites, which are training and inference together typically, or somebody who just wants proprietary air-gapped capacity for either training and/or inference typically together or just inference and just wants essentially a token factory. They want to run a Qwen model. They want to run an open-weight model.

And they literally are just looking for this mix of lowest cost per token with best quality of service. As an example, if you're a financial trading company, you may do model development at a data center where latency is not important because you're really training a model. But once you deploy that model to actually run it, you're going to run it somewhere on or near-prem where latency is next to zero. So that's a quality of service. You're willing to pay more per token if the quality of service suits exactly your needs. And if quality of service — meaning latency, speed and connection time — isn't important, then you can run it at a token factory that's more remote. We believe the market is going to consist of a variety of those tiers, and we're already in talking with enterprise customers doing part of our market research. What we're finding is there are companies whose public cloud bills have gone from hundreds of thousands of dollars a month to millions of dollars a month because they are running models in the public cloud, and they're finding it just financially not an option.

You're also seeing the large model providers needing more and more capacity to run their models. As they develop more and more tools — I'll use as an example, Anthropic has just released new tools for financial analysts, for investment banks. They're doing all of these vertically designed agentic frameworks. These are systems that consume huge amounts of tokens, but they still are running essentially on your data, but it's still Claude that's running in the background. So there's a need to be able to run across a huge infrastructure of sites globally to be able to operate these things. I think you're going to see inference growing, but training is still going to be growing for the foreseeable six to seven years, I think. But you're just going to see inference volumes increase dramatically as more and more agentic technology comes to play. We're seeing thousand-fold increases in agentic token consumption when somebody moves from chat to using Cowork or Claude Code, for example. Just talk to any CIO and ask what their token bills are lately, and they'll share with you that token maximization is not something they want to really incentivize people to do.

OperatorOperator

Your next question comes from Chris Brendler with Rosenblatt Securities.

Christopher BrendlerAnalyst (Rosenblatt Securities)

I wanted to ask on the G&A line; it has seen a pretty significant increase over the last couple of quarters, even if you back out stock-based comp and the callout on acquisition expenses. And just sort of trying to reconcile that versus the headcount reductions. I know that's probably more forward-looking, but can you talk a little bit about some of the investments you've made and what areas? I was struck by your comments about repositioning the organization as you outsource more and more stuff to Starwood; I would think the organization may not be as large in the future as more and more Bitcoin mining folks are repositioned. Just can you talk about the path of expenses? Because it seems like it's a little elevated still in my mind.

Frederick ThielChairman and Chief Executive Officer

Salman, do you want to take that?

Salman KhanChief Financial Officer

Sure. Chris, thank you for the question. As you know, we've said this before, we've been growing over the years. As part of our announcement in Q1, we looked at our organization and reorganized ourselves more focused on what is in the pipeline in the future. As discussed in today's call, we've got the Long Ridge acquisition and the Starwood joint venture, which we're very excited about. You have to remember that we are still very good at what MARA is good at: securing low-cost power at scale, $0.04 per kilowatt hour at multi-gigawatt capacity that not many can claim. We have the operations to manage that from a Bitcoin mining perspective today. That capacity that we have and the additional capacity that we plan to acquire can be dropped into our joint venture in certain cases, for example with Starwood, because we maximize our return by not having to invest incremental dollars when we get credit for the assets we drop into the partnership.

So our dilution compared to other miners is much lower. Historically, MARA was a pure-play Bitcoin miner. MARA going forward remains a technology company that happens to be surrounded by energy in the middle and AI and critical IT where we expect to monetize and generate free cash flow from a long-term perspective. We looked at the overall structure and asked what skills we're missing that we need to add to get there, and what skills we don't need for the growth of our previous pure-play Bitcoin mining business. That's what resulted in the reorganization. In terms of the cost structure, I would expect, as we have stated in our prepared remarks, for costs to be lower than what we incurred in Q1 as savings are realized. But you also have to realize that when we are having these transformative transactions and acquisitions, there are costs associated with those. As we have disclosed in our adjusted EBITDA disclosures, we will continue to disclose and isolate those costs so you can see what is recurring and what is nonrecurring, which helps modeling the cost better.

Frederick ThielChairman and Chief Executive Officer

And then, Chris, the other thing is, obviously, the transition takes time. If I sign a lease tomorrow, that site is still mining Bitcoin for another 18 months, maybe while the site is being built. So it's not just that we're going to let go of a whole bunch of operations folks just because we're transitioning the strategy. It takes time.

Christopher BrendlerAnalyst (Rosenblatt Securities)

Okay. My follow-up question was on the funding plan. A lot of former Bitcoin miners have started shying away from the ATM. You mentioned you haven't used the ATM since September. As you think about your profile, are you striving to be more of an investment-grade credit and use more traditional project financing methods in 2026? Or is that more of a longer-term plan?

Salman KhanChief Financial Officer

Yes. So a couple of things to think about, Chris. The transactions we're discussing — and you can look at examples of what other miners have disclosed with HPC conversions — we expect to have a few announcements around tenants in the second half of this year. Usually, these transactions are either with an investment-grade counterparty or backstopped as others have announced. So from a financing perspective, yes, those financings are considered investment-grade from a project finance standpoint. When you talk about our profile and cash flows, our goal is to create this vehicle where we continue to acquire low-cost power sites and drop them into the partnership with limited capital needs depending on project size and continue to have those triple-net lease revenues flowing through our P&L. As we generate more predefined future free cash flows, our balance sheet position improves and you can have a better conversation around credit quality. Historically, this sector has not been evaluated heavily by rating agencies. But with multi-gigawatt capacity and opportunities to generate long-term free cash flow from 15-year low-risk projects, it certainly invites rating consideration.

OperatorOperator

Next question comes from Brett Knoblauch with Cantor Fitzgerald.

Brett KnoblauchAnalyst (Cantor Fitzgerald)

Fred, on the Long Ridge acquisition, you outlined a path to maybe a 600-megawatt AI campus. Could you help put a timeframe around that? Where are they in terms of that extra 200-megawatt grid connect that they're pursuing now? And how long would it take to expand generation capacity and what approvals would you need?

Frederick ThielChairman and Chief Executive Officer

Sure. So the behind-the-meter expansion is already in process. That's on a shorter timeframe than the grid expansion. The grid expansion application submission process is what it is, but as you look at the development timeframe, a 200-megawatt facility will likely take 18 to 24 months before it comes online. By that time, an additional 200 megawatts behind the meter should be available. Shortly thereafter, we expect the remaining 200 megawatts to come online from the grid interconnection. The key is getting the first site up and running for the tenant and then having the power in the queue and ready to go. But the behind-the-meter additional capacity is what will come on the soonest of the two additional capacity increases.

Brett KnoblauchAnalyst (Cantor Fitzgerald)

Awesome. Helpful. And then maybe as a follow-up, I think you reiterated you expect the first lease with Starwood to get signed at some point this year. What's giving you the confidence that this could be executed as quickly as you're expecting?

Frederick ThielChairman and Chief Executive Officer

Competition amongst the prospective tenants to get into the site. We have, as I think we said in our prepared remarks, multiple tenants looking across multiple sites that make up 90% of our capacity today. Demand in this market isn't decreasing. People are getting ever more antsy about getting more capacity. You can see what some of the model players have been doing just to garner more capacity out there. As a model provider, you are directly limited in your ability to grow capacity by the amount of compute you have because you can only have so many clients hitting your model before your compute runs out of gas. The only thing you can do is yield management and raise your prices. Some model providers have essentially put capacity caps and raised fees because they did not fully expect the explosion in demand for tokens that has happened once agentic technologies started to be introduced. Open-source and provider innovations opened the floodgates for people to start looking at how to do this.

This is not just an enterprise play or a consumer play; it's across the full spectrum of users. People are starting to build agents and use tools like Claude Cowork. Google is about to release Remy, which will be an agentic helper in the Google ecosystem — a huge part of the SMB market with Gmail, Google Calendar, etc. — driving more demand. As you add customers, you need to do more inference. At the same time, model sizes are growing. Look at what Anthropic has said about Ethos: it needs 10x or 100x more compute than prior models. When you look at the increment in both model size and compute requirement for training and operating models, plus inference, there's huge demand for capacity today. We have multiple prospective tenants competing for opportunities to get into some of our sites, and we're well-positioned with the amount of capacity we have and a partner like Starwood to take advantage of that.

OperatorOperator

Your next question comes from Ben Sommers with BTIG.

Benjamin SommersAnalyst (BTIG)

You mentioned conversations with both hyperscalers and enterprise customers. Curious if there's any preference there from your side. Also, is there any difference in the conversations and how you think about the customer mix longer term as you build out the HPC business?

Frederick ThielChairman and Chief Executive Officer

From a per-megawatt basis, the hyperscalers will dominate by a large extent because of the sheer capacity they need. A single enterprise 25-megawatt deployment provides meaningful capacity for an enterprise customer. In the near term, think roughly 90/10 in favor of hyperscalers, and over time perhaps closer to 60/40, but that will depend on how enterprises decide to proceed — whether they want on-prem private cloud or near-prem solutions. Exaion is well-suited to service private cloud needs, and we can help operate that. We think hyperscalers will be the first set of tenants we scale with; over time, enterprise customer mix will increase.

Benjamin SommersAnalyst (BTIG)

Got it. Super helpful. Since announcing the partnership with Starwood, has there been any change in how you're thinking about developing the power portfolio moving forward? Has their long-tenured expertise in the data center market helped scale what MARA currently has in the power portfolio?

Frederick ThielChairman and Chief Executive Officer

The beauty of the partnership is the complementarity. We are very good at building a pipeline of sites, acquiring land and power at attractive prices. Starwood is excellent at finding tenants, getting sites designed, built and operational. There's little overlap and great synergy. That makes the relationship very effective. We're focused on filling the funnel of prospective sites so we remain a reliable source of capacity for tenants. A key difference between our model and many peers is they often start with one large site and sink all attention and capital into it, then move to the next. With the Starwood model, we can acquire multiple sites and have them developed in parallel, enabling us to scale faster. While we may have been later to the party, we expect to catch up quickly and scale past peers because of the value of this partnership.

OperatorOperator

That's our last question for today. I will hand the floor back to Robert Samuels for closing remarks.

Robert SamuelsVice President, Investor Relations

Thanks, operator, and thank you, everyone, for joining us today. If you do have any questions that were not answered during today's call, please feel free to contact our Investor Relations team at ir.mara.com. Thanks very much. Enjoy the rest of the day.

OperatorOperator

Thank you. All parties may disconnect.

Transcripts come from a third-party provider (Alpha Vantage), not first-party parsing. Speaker titles are as supplied and are not normalized.