IREN Q3 FY 2026 Earnings Call (NVIDIA 5 GW Deal) | Daniel Roberts

Thanks Mike and thank you everyone for joining us today. Eight years ago, when Will and I founded this business, we spent a lot of time thinking about what the digital future actually meant for the physical world. We talked about films like The Matrix and Ready Player One, not as science fiction, but as a signal. Worlds where digital adoption was total, instantaneous, and infinite. The insight we kept coming back to was this: digital adoption curves can go from zero to one overnight. But the real world doesn't scale that way. Power, infrastructure, land, data centers, these take years to permit, finance, and build. The bigger the demand, the harder delivery becomes. That gap between exponential digital growth and the physical world's ability to service it, that structural disconnect is exactly what we set out to solve. That scarcity is now defining where AI infrastructure gets built and who can build it. Eight years later, that thesis is playing out exactly. And this quarter, we demonstrated what disciplined execution against it looks like at a global scale. In AI infrastructure, secured power is only valuable if it can be converted into customer-ready compute. That conversion is hard. It requires site control, grid connection work, permitting, design, procurement, construction, GPU installation, networking, commissioning, financing, and customer delivery. All coming together on tight timelines. Iron's strength is bringing those pieces together. We have experienced site teams, standardized designs, and repeatable construction processes that allow us to build across multiple sites in parallel. As we scale, each phase builds on the prior phase. The template becomes more repeatable, the procurement and construction process becomes more efficient, and the site teams carry that experience forward. That is where Iron has built its moat and why real assets and real capabilities are harder to replicate than they might appear. That execution capability is showing up in the numbers. More capacity, more revenue, stronger funding certainty, and in the partnerships we are announcing today. This was a significant quarter and a significant week. Let me run through the highlights. On capacity, we increased secured power to 5 GW, added new sites in Europe and APAC, energized Sweetwater One on schedule, and have Horizon 1 GPU commissioning now underway for Microsoft. On customers, all of our operational capacity is fully contracted. We are not chasing demand. We are racing to build supply fast enough to meet it in this market. The moment compute comes online, it goes to work. That is the nature of the structural imbalance between AI infrastructure supply and demand. And it is why time to compute is the most important metric we track. We increased ARR under contract to 3.1 billion, remain on track to hit 3.7 billion exiting calendar 2026, and this week signed a 3.54 billion 5-year AI cloud contract with NVIDIA. The first step in a broader strategic partnership I will come to in a moment. On capital, we had 2.66 billion of cash at April 30 and we continue to progress GPU, data center, and corporate-level financing initiatives to support the next phase of buildout. But the headline today is the NVIDIA partnership and it deserves a little more than a bullet point. Let me explain what this partnership actually means. We are working with NVIDIA to support deployment of up to 5 GW of NVIDIA DGX-aligned AI infrastructure across our global data center platform alongside DGX environments and the DGX AI factory reference architecture. The 2.1 billion NVIDIA investment is structured to reflect that. Their rights to invest only vest as NVIDIA GPU infrastructure is deployed across Iron campuses and only fully vest upon deployment of 600,000 GPUs. NVIDIA's capital is directly tied to execution. That's not a passive financial investment. NVIDIA is a partner who wins as we deliver. The 3.54 billion AI cloud contract announced today supporting NVIDIA's own internal workloads is the first step in that partnership. Eight years ago, Will and I set out to build the infrastructure the digital world would need. Today, the world's leading AI infrastructure company has chosen Iron as the partner to help build it. This next slide shows exactly how we build against this. So, here is our plan. In 2026, we are targeting 480 megawatt of AI cloud capacity, 150,000 GPUs, and 3.7 billion of ARR by year end. That is the near-term plan and the clearest bridge from capacity to revenue. In 2027, we are scaling to 1,210 megawatt with an additional 730 megawatt currently under construction across British Columbia and Texas, including Childress and the initial phase at Sweetwater One. The construction flywheel we are running in 2026 carries directly into this next phase. Beyond 2027, we are building against a 5 GW global power portfolio: North America, our new European platform in Spain, and an APAC pipeline anchored by large-scale Australian opportunities. The sequence of delivery matters because it dictates time to compute and time to compute is what drives revenue. Each phase supports the next. That's how the platform compounds. One more thing before we move on. This week we welcomed Morantis into the Iron family. 650 engineers, operators, and customer support professionals who have spent more than a decade running cloud infrastructure for over 1,500 enterprise customers globally. To Alex and the whole Morantis team, welcome. I'll come back to what this means for our delivery capability later on, but let me start with 2026 where construction and customer demand are coming together most visibly. The 2026 expansion is focused on delivering 480 megawatts of AI cloud capacity across Childress, Prince George, and McKenzie. This is where the road map translates into near-term deployments, customer handoffs, and ARR conversion. We'll start with the largest and most complex 2026 work stream, the 300 megawatt Horizon 1 to 4 liquid-cooled deployment at Childress where NVIDIA GB300 NVL72 installations are now underway. Horizon 1 is scheduled for Microsoft handoff in Q3 and Horizons 2 to 4 remain on track for delivery by the end of this year. This is a major execution milestone. It demonstrates our ability to design, build, fit out, and commission large-scale next-generation liquid-cooled infrastructure for a hyperscale customer on an accelerated schedule. We have around 3,000 workers on site right now. That level of activity reflects both the urgency of AI infrastructure demand and also the depth of our execution capability on the ground. Importantly, the model is repeatable. Horizon 1 establishes the build template. Each subsequent phase benefits from the same design, supply chain, construction sequencing, and site team. That is how we drive faster deployment every time. Alongside the liquid-cooled build, we are also converting existing air-cooled capacity into AI cloud deployments across British Columbia and Childress. In British Columbia and Childress, we are progressing 180 megawatts of air-cooled AI cloud capacity by leveraging existing infrastructure. At Prince George, all air-cooled GPUs have now been delivered and are either operating or undergoing commissioning across the 50 megawatt site. At McKenzie, 80 megawatts of data center capacity has been prepared for GPU installations commencing in the second half of 2026. And finally, at Childress, data center retrofits are underway across an initial 50 megawatts ahead of GPU deliveries in the second half of this year. This is a capital-efficient part of the road map. We are taking existing sites and converting them toward higher-value AI cloud workloads and it works because we already have the operational teams, infrastructure, and site control in place. Air-cooled capacity can come online faster than liquid-cooled. In a market where time to compute is everything, that speed is a commercial advantage and we are using it. We're already seeing this dynamic play out commercially with capacity continuing to be contracted ahead of commissioning as customers prioritize speed to market. We now have 3.1 billion of ARR under contract, including approximately 700 million of ARR associated with a 3.54 billion 5-year contract for Blackwell GPUs to be deployed across 60 megawatts of air capacity at Childress for NVIDIA. Against the full 2026 expansion, we are targeting 3.7 billion of ARR by year end across 150,000 GPUs. The remaining uncontracted capacity represents approximately 50,000 air-cooled GPUs scheduled for delivery in phases through the second half of this year. Demand for that capacity is robust. Our focus is on using our time-to-compute advantage to secure the right customer mix. With the 2026 plan on track, let me turn to what comes next. The 2027 expansion where the platform scales to 1,210 megawatt. So the 2027 plan is about demonstrating that what we are building in 2026 is not a one-off. It is a repeatable, scalable model that should accelerate over time. Here's what that looks like in practice. In British Columbia, Canal Flats is another example of converting existing infrastructure into AI cloud capacity. We plan to retrofit all 30 megawatts of existing air-cooled capacity to support AI workloads. Capital-efficient, fast to execute, and consistent with the same model we are running at Prince George and McKenzie. In parallel, Childress continues to be the largest single contributor to the 2027 setup with both new liquid-cooled capacity and additional air-cooled retrofits adding a total of 400 megawatt of gross capacity. At Childress, the 2027 plan includes 100 megawatts of additional liquid-cooled IT load for Horizons 5 and 6 as well as retrofitting an additional 250 megawatt of existing air-cooled capacity. Of that 250 megawatt, approximately 60 megawatt will be deployed to support the NVIDIA AI cloud contract. The combination of new liquid-cooled data centers and air-cooled retrofits gives us real flexibility. We can support next-generation high-density deployments while continuing to use existing infrastructure where it is the right technical and economic fit. That flexibility is part of what makes Childress such a productive campus. In parallel, Sweetwater becomes the next major Texas campus in the 2027 plan. At Sweetwater One, the high-voltage substation has been energized on schedule and construction is now underway for the initial 200 megawatt IT load phase of liquid-cooled data centers. Energizing the substation is an important milestone. It moves Sweetwater from development into execution and establishes the electrical foundation for the broader site buildout. Sweetwater 1 is being designed for next-generation chip architectures including the NVIDIA Vera Rubin. Like Childress, we are deliberately sequencing the build so that the first phase creates the backbone for faster subsequent phases. The first 200 megawatt is not just the first 200 megawatt. It is the foundation for a much larger cycle. The commercial pipeline for our 2027 capacity is anchored on the same principle that is driving everything we are building. Our vertical integration is a genuine advantage for customers because we control more of the critical path than anyone else in this market. Power, land, data center, construction, the pieces that cause delays for others are the pieces we own and control. Customers want certainty that capacity will be available when promised. The phased 2027 buildout plan gives us a concrete basis for those conversations and we are having them. We are in the process of negotiating large-scale AI cloud deployments across our 2027 capacity today. Demand is not the constraint. However, it is highly unlikely to be the constraint. The priority is delivering capacity on schedule and converting our time-to-compute advantage into durable long-term customer relationships. We do expect the customer mix to evolve over time, hyperscalers, AI natives, enterprises, and on-demand use cases, but we do not need to force that outcome. The platform will attract the right customers as it continues to scale. Beyond 2027, the same execution model extends into a much larger 5 GW global platform. We now have 5 GW of secured power. To put that in context, that is not a pipeline number or an aspiration. That is secured power and it represents one of the largest portfolios assembled for AI infrastructure anywhere in the world. The question now is how we build against it. The answer is a phased global platform across North America, Europe, and APAC with additional development opportunities beyond that. Let me walk you through each region. We'll start with North America, which remains the largest component of the long-term platform. In North America, the next major phase is driven by Sweetwater and Kiowa, our flagship gigawatt-scale campuses in Texas and Oklahoma, where data center capacity is expected to commence ramping across 2027 and 2028. We also have multiple development projects advancing through the connection processes, including batch zero candidates in Texas, which represent some of the most strategic, valuable grid connection opportunities in the country. The North American pipeline has a natural progression of scale. Childress demonstrates the operating model today. Sweetwater expands it across an even larger campus and Kiowa provides the path to another hyperscale-tier opportunity as power ramps from 2028. Every campus builds on the last. That's the compounding effect of having secured the right land and power positions early. At the same time, we're expanding the platform into Europe through Spain. Today, we announced the acquisition of Nostrom Group and with it our entry into Europe. The transaction adds 490 megawatts of secured power in Spain, a gigawatt-scale development pipeline, and a team of more than 50 people across development, engineering, construction, and operations. But what it really adds is a platform and the right people to build it. I want to acknowledge Gabriel Nabrida and the Nostrom team. Gabriel spent nearly two decades in European energy at EDP Renewables managing gigawatts of operating assets across multiple European markets and most recently as CEO of EDP Solar. He understands European power infrastructure as well as anyone and we are excited to have him leading Iron's European platform. Spain is the right place to start. Supportive AI policy, abundant renewables, lower build costs, and strong connectivity into broader European demand. Europe is a market where power availability and grid timelines are increasingly shaping where customers can actually deploy. And Spain gives us a credible, scalable answer to that question. This is not just a power acquisition. It's the establishment of Iron's European platform. From Europe, we move to the other side of the world and an opportunity that matches the scale of everything we've just described. Australia is obviously not a new idea for us. We have been progressing large-scale Australian projects towards secured grid access for some time and we think the opportunity here is as significant as anywhere in our portfolio. Asia Pacific is home to roughly 4.8 billion people, around 60% of the world's population. That includes some of the fastest-growing AI demand markets on Earth: Indonesia, Singapore, Japan, Korea. The infrastructure requirement to service that demand is enormous and it is largely unmet. Australia is uniquely positioned to serve it. Abundant renewables, a trusted jurisdiction, strong rule of law, and as the submarine connectivity map shows, direct fiber links into major demand centers across the region. It is the natural anchor point for AI infrastructure serving APAC. We are already seeing hyperscalers and frontier labs make significant commitments to Australian operations and we intend to be a major part of that story. Beyond Australia, we continue to progress global development opportunities that extend Iron's runway further. The platform we are building is designed to create scale into demand wherever it develops and the pipeline gives us the flexibility to do exactly that. That is the global platform: secured power across North America, Europe, and the development pipeline extending into APAC and beyond. But securing power and building data centers is only part of the equation. The other part is what happens when the compute goes live. How it is deployed, managed, and supported for customers at scale. That is where I'd like to spend a moment on Morantis. This week we welcomed Morantis into the Iron family. And I want to take a moment to acknowledge that 650 people joined Iron this week: engineers, operators, customer support professionals, a team that has spent more than a decade building and running cloud infrastructure for over 1,500 enterprise customers globally. That track record speaks for itself. And what they bring is specific. Their Cordon AI platform manages AI infrastructure across bare metal, virtual machines, and Kubernetes environments, exactly the complexity our customers are dealing with as deployments scale. They are also a founding ISV partner of the NVIDIA AI Cloud Ready initiative which means they are already deeply embedded in the same ecosystem we are building into as we scale. Delivery is not just about bringing GPUs online. It is about what happens after: provisioning, monitoring, supporting customers through increasingly complex environments. Morantis strengthens all of that. We are already seeing it and they will play a central role in supporting our NVIDIA AI cloud contract. To Alex and the whole Morantis team, a big welcome. We're super excited to have you. So, what you have heard today is a company that has secured power at scale, is contracting revenue at scale, and is now building delivery capability at global scale. Anthony will now walk you through how we are funding it.

Thanks, Anthony. So, eight years ago, Will and I asked a simple question. What does the world need to build the right digital future? The answer was power, land, data centers, and compute, and the ability to bring them all together at scale faster than anyone else. Today, that thesis is playing out, and we are just getting started. With that, we will open the call for Q&A.

And maybe just to add to that quickly, Kent, I think to directly answer the question, there's nothing stopping us contracting that capacity today. It just gets easier the closer you get. So the focus is on time to compute, the demand we know is there and all it does is make the conversations and the negotiations that we are having live time for a lot of that capacity much easier when you've got a defined construction and delivery plan rather than trying to make things up on the fly in parallel with a full-form agreement.

Sure. Look, in some ways Australia is very similar to other markets and the operation of the electricity market in Australia managed by AEMO is very similar to what we see in Texas as ERCOT. There are markets in Australia which resemble Texas in other ways: lots of land, good transmission line capacity, good fiber connectivity, and abundant renewables, which isn't located close to other demand centers, similar to what we see in West Texas. So, there are a lot of parallels. The reality is Texas is just an easier place to do business and we've been able to accelerate faster there. But it hasn't stopped us continuing to incubate projects down in Australia and we're getting far closer to those projects becoming a bit more of the reality. And I think the demand environment and the ability to service APAC and the demand constraints that we're seeing and hearing in our conversations with hyperscalers means that Australia looks like a fantastic frontier for us and we'll look to accelerate that in parallel with North America and Europe.

Look, it's going to evolve and there's a lot of unknowns around this but if you break it down, a hyperscale contract can mean two things. They can mean hyperscalers using capacity for their own purposes in terms of training and servicing workloads such as their own AI models or it can mean they're just acting as intermediaries to aggregate capacity for end customers that we're talking to directly. So obviously in the case of the latter, whether you're dealing with a hyperscaler or going directly to the end customer, the end demand is the same. Then you've got different types of workloads. So inference and training. Inference is a little more latency-sensitive. Training you can probably afford a bit more latency. And indicatively we've had conversations around training models in Australia. Yes, the USA to Australia is a long geographic distance but it's actually not that far over fiber particularly where you're talking about training models. And given where inference sits today as well, we're all using ChatGPT or Claude. The response times are still adjusting to the level of demand and the supply to service it. So look, it will evolve over time and our objective is to build out an expansive ecosystem of end customers. The partnership with NVIDIA is designed around that. The Morantis integration into our business is designed to help facilitate that over time in addition to all the near-term operational capabilities that it brings out. So the goal is very much to build out that diversified customer base over time across all of those markets.

In terms of the 5 GW more broadly and maybe just to address that in the plan. So that's obviously a lot of capital today, but the reality is you don't need all that capital day one. There's an S-curve of construction. It takes time. It takes years to deliver this. This is the whole point around time to compute. It's not just a case of getting power and land. It's assembling multi-thousand construction teams and actually delivering it. And the funding for that just is progressive over time. So, as we've seen, as we continue to deliver, we continue to drive revenue, we can reinvest that revenue in capex and it continues to unlock more and more financing sources over time. And part of the partnership with NVIDIA, we've announced they've got the ability to invest in Iron as we commission GPUs. But equally there's other support mechanisms being discussed to the extent that we need them but the reality is capital markets are open. They've been very supportive of our plan and we anticipate that continuing. The moment that changes, there's a whole world of capital out there in terms of other options whether you're creative around private markets or otherwise. When you look at the GPU financing, which is the lion's share of that capex, the Microsoft contract is a great template. We financed 95% of that capex at an average interest rate of about 3% through prepayments and GPU financing. So the capital is out there as long as you sign good contracts and you show that you can execute and operate this capacity.

Oh, sorry, Kent. Look, again, we're trying to reiterate this as much as we can, and I'm very happy for someone to point it out, but there are no idle GPUs, and the prospect of them there being GPUs sitting there unused, given how structurally constrained this market is, let alone the near-term, but in the medium term, it's not the focus. We are having a lot of customer conversations, but all of our operational capacity is fully contracted. We're contracting substantial portions of capacity before it even arrives. And we're in discussions with a variety of customers all the way from hyperscale clients down to AI-native labs for all of that 2026 and 2027 capacity. So when a signature is put on a paper, it just flows naturally. Our conviction is around the demand-supply and you cannot tap into that unless you bring the capacity online and this is the thing, a customer contract doesn't deliver revenue. Having compute online delivers revenue and that has been the focus.

It's something that we're looking closely at, Joe. There is no set formula as to the proportional splits between different types of customers. There are benefits in having hyperscale clients in terms of financeability, contractual certainty. But there are also consequences in terms of price because you're not servicing the end customer in many of those instances. But the ability to service the end customer has been something we've focused on since day one. All of our early deployments have been very focused on non-hyperscale customers and getting as close to AI natives and enterprise as we can. So, the Morantis acquisition certainly helps that. I'm not going to sit here and say we're going 100% hyperscale, we're going 100% AI-native end market. The reality is that that blend will just emerge organically over time. And this again is part of the close working relationship we've got with NVIDIA. We've spent a lot of the last fortnight in their San Jose office working through how we service all types of customers all the way from the trillion-dollar hyperscales through to the emerging AI scale-ups where a lot of this innovation and development is taking place. And it's funny speaking to someone the other day, you don't need a sales team in this market, particularly when you've got NVIDIA. They see the whole ecosystem, the introductions, the referrals, putting us in touch with anyone that needs capacity, it's just happening so organically, so quickly, live time that it'll just play out a good way. But I think a combination of hyperscale, a combination of other is absolutely the goal.

Thanks, operator. Thanks everyone for joining us today. We remain focused on execution, delivering the 2026 plan, advancing the 2027 buildout, and positioning our now global platform for the opportunity beyond that. And we look forward to updating you as we deliver. Thanks everyone.