Compute Is King: How Far Can the Neocloud Rally Go?
CoreWeave Q2 2026 earnings conference call
Key Takeaways (AI-Generated)
Financial Performance
- Q2 revenue reached $2.6 billion, up 112% year-over-year and 24% sequentially
- Revenue backlog hit $104 billion, up 46% year-over-year with $25+ billion new commitments
- Adjusted EBITDA doubled to $1.5 billion with 59% margin from $753 million prior year
- Net loss increased to $626 million from $290 million, with interest expense rising significantly
Business Highlights
- Added 500 megawatts in Q2, reaching 1.5 gigawatts total active power capacity
- Surpassed 1 billion model training runs tracked on platform milestone
- Managed inference platform ARR grew from $1 million to over $100 million since launch
- First cloud provider to validate Nvidia's Vera Rubin NVL 72 technology
Financial Guidance
- Raised 2026 revenue guidance to $12.4-13.2 billion with operating income $960 million-1.15 billion
- Q3 revenue expected at $3.45-3.6 billion with operating income $200-260 million
- 2026 CapEx projected at $35-39 billion with 1.85+ gigawatts active power target
- Expected exit 2026 with $250+ million managed inference ARR
Opportunities
- International expansion with 1+ GW contracted power outside US including Indonesia
- Higher-margin AI development services adoption across broader customer base
- Strategic partnerships like Solid Dime for supply chain risk mitigation
- Debt financing success reducing weighted average cost by 300 basis points
Risks
- Complex global supply chain challenges requiring strategic sourcing of critical inputs
- Local community opposition and moratoriums on data center development in certain areas
Full Transcript (AI-Generated)
Operator
By industry and use case. But the pattern is consistent. AI is moving from experimentation into core operations, and the organizations that act decisively are creating an advantage. Deployment is no longer the finish line. As AI moves into production, the way applications are built is changing, and the leaders will be those who learn and iterate the fastest.
For the last several years, many organizations treated a model like a deliverable train it, deploy it, and move on. Enterprises no longer operate that way. Training, inference, evaluation, and improvement now form a single continuous loop. Models and agents in production generate real world data. That data informs evaluation, driving new experiments which improve the model or application. Before being redeployed into production. The loop repeats and capability compounds over time.
That shift fundamentally changes both the demand curve and the economics of AI. Compute is no longer a one time requirement concentrated at the beginning of a model's life. It becomes an ongoing requirement that grows with every application in production and every cycle of improvement. Our AI native platform was built for this. It spans cutting edge cloud infrastructure, a rapidly growing managed inference business, leading developer tooling and agent solutions, and a best in class orchestration and observability layer powered by Mission Control.
Together these capabilities give customers one integrated environment. Customers deploy applications through Core Weave inference using our models or the ones they have customized with Our serverless capabilities, monitor performance with weights and biases, evaluate applications in production, experiment with new models, refine their performance through serverless reinforcement learning or sandboxes, and validate every change against quality, performance, and cost before returning it to production.
Core Weave Aria, our AI research and iteration agent, accelerates that process further by analyzing thousands of evaluation runs, surfacing insights in minutes and recommending the next experiment. That allows customers to compress the time between an idea and experiment and a production improvement. At Lightspeed in Q2, we introduced 7 new AI platform capabilities and achieved multiple industry firsts. These innovations were built alongside our customers and partners to solve real production challenges. That is why we are seeing such strong adoption.
And just this week, we surpassed 1 billion model training runs tracked on our platform. Behind that number are millions of experiments, thousands of research breakthroughs, and a growing community of engineers, researchers and organizations building the next generation of AI. Our AI development services, which carry higher margins, are also being adopted by a broader set of customers than our core cloud. That is proving to be a natural customer expansion path because the developers building AI applications today are the AI cloud infrastructure customers of tomorrow.
By serving them early, we are establishing relationships that naturally expand as AI workload scale. We have seen an explosion of growth in our managed inference platform in the few months since its launch, with growth constrained only by our near term capacity across serverless offerings and dedicated deployments. Core Weave is monetizing tokens while giving customers flexibility in how they consume our platform.
Companies such as grammarly and you.com are moving from experimentation to real production traffic, running AI coding agents, serving their own fine tune models, and deploying open weight models at scale. Customers shouldn't have to trade speed for cost, and on Core Weave they don't. They choose our platform for the combination of total cost of ownership, quality, breadth of service and performance that is reflected in our consistent leadership across cost per token and speed to 1st token on leaderboards like artificial analysis for open source models.
Including Kimmy 2.6, K 2.7 code, GLM 5.2 and minimax M3. And that leadership is converting directly into revenue. In the past few months since its launch, booked ARR for our managed inference platform has grown from 1,000,000 to more than 100 million. We expect to exit 2026 with at least 250 million of managed inference. ARR pioneers need a different kind of platform.
The continuous AI life cycle cannot be supported by simply adding GP use to a general purpose cloud. It requires a new approach from power cooling and rack design through networking, orchestration, observability, developer tools and managed services. That is why Core Weave is purpose built for AI. Our platform is singular in its depth, breadth and technical capability.
In Q2, we became the first cloud provider to bring up and validate Nvidia's Vera Rubin NVL 72, leveraging our innovations in software defined liquid cooling and rack management to extend our track record of being first to market. We also set new ML perf records for training and inference with open source models running on the NVIDIA Grace Blackwell platform and in our tests achieve the lowest cost per token for inference.
However, performance alone is not enough. Customers need enterprise grade security and observability, reliability and compelling economics. According to Signal 65, Core Weave delivers total cost of ownership estimated to be up to 47% lower than the average hyperscaler. Customers also require our platform, which integrates these capabilities with a broader portfolio of storage, CPU and networking services across a distributed footprint of data centers globally.
In July, Gartner named Core Weave a visionary in its 2026 Magic Quadrant for Cloud AI Infrastructure. We believe that recognition provides additional independent validation of our approach to building the AI cloud. These achievements are not isolated technical milestones. They translate directly into faster deployment, higher utilization, better application performance and lower cost for customers.
Pairing product depth with best in class performance, quality and market leading TCO is a winning formula for our customers and for Core Weave. Core Weave is the foundation for AI at scale. This market requires a foundation at a magnitude unlike anything that came before. That means securing power sites, cooling, hardware, storage, networking and supply chain inputs well ahead of need and operating them as one integrated system.
As I shared at the top of the call, we ended Q2 with 1.5 gigawatts of active power, adding close to 500 megawatts in the quarter alone. To put that in perspective, we added more power in Q2 than any single neocloud operates in total today according to third party estimates. Critically, our scale is working in our favour and the math gets better from here.
Each new deployment is landing against a much larger installed base than it was even 1/4 ago. As that base grows, each new build becomes a smaller part of the whole while contracted revenue from existing deployments remains in place. This is how we are transforming scale into operating leverage. It is why margins expanded in Q2 and why we expect them to continue expanding sequentially during Q3 and Q4.
We are also securing the ingredients required to sustain growth over a multi year horizon. Contracted power grew to 3.7 gigawatts in Q2. Since quarter end, we have added roughly 500 megawatts bringing contracted power to 4.2 gigawatts as of today. These figures exclude more than 1.5 gigawatts of further potential power from powered land. We have accumulated options we have to expand at existing sites.
And LO is we have executed our first several self builds are already well underway including our first site expected to come online later this year. Powered land forms the foundation for deeper vertical integration, giving us greater operational control and supporting enhanced long term margins. We are also expanding globally and have contracted more than one GW of power outside the United States, including recently entering the APAC region with 360 megawatts in Indonesia that will begin coming online in approximately 18 months.
We expect international markets to become a major driver of growth as we meet customers where they and their end users operate. All in, we have excellent visibility to our target of at least 8 gigawatts by 2030. We expect demand to meaningfully exceed supply for years. In that environment, access to power is only part of the equation. Just as important is each necessary component required to deliver the AI cloud at scale.
Building on our close partnerships with NVIDIA and our OEM and ODM partners, our recent long term agreement with Solid Dime is 1 illustration of how we are de risking access to the critical inputs needed to serve our customers. Our investments in technology capacity, vertical integration, supply chain and global expansion all flow from the same vision. AI is increasingly pervasive. The Pioneers who move fastest will lead, and they will require a platform capable of supporting continuous learning and deployment at unprecedented scale.
Before I turn to Nitin, I want to reiterate that Core Weave enters the second-half of the year with more momentum than at any point in our history. AI is reshaping every industry. The Pioneers that are building need more than compute, and that is why they come to Core Weave for an AI cloud designed for the full AI life cycle, serving any workload from frontier training to rapidly scaling inference.
Demand continues to exceed supply across sectors, geographies and generations of infrastructure. We are delivering at extraordinary scale to a diverse set of customers with improving operating leverage and visibility into the power and critical components required to sustain growth for years. The opportunity ahead is generational. Core Weave is the essential cloud for AI. Our conviction in our strategy has never been stronger and our execution continues to reinforce it. With that, I'll turn it over to Nitin.
Nitin
Thanks, Mike, and good afternoon, everyone. Q2 was an exceptional quarter of a core weave marked by intense customer demand, significant ramp of our active capacity and continued execution against our product and financing. Rd. maps. Perhaps most importantly, Q2 marked the quarter in which we saw margins inflect expanding sequentially as we had discussed over the past several quarters.
Before diving into results, I wanted to spend a few moments touching upon how demand dynamics are evolving in the current environment as well as it's implications on cash flows and the value of our rapidly growing infrastructure footprint. Demand for Core V cloud remains exceptionally strong across the entirety of our customer base. With demand from multiple customers for each GPU we bring online.
We are being disciplined in how we allocate our scarce cloud capacity. We are prioritising opportunities that are strategically important, adding new customers while deepening long term existing relationships and delivering attractive returns that as Mike noted are expanding further. The scale of our AI products and services beyond GP US also continues to ramp significantly as customers consolidate spend with us.
These margin accretive businesses including storage, CPU, networking and software already exceed $400 million of ARR as of Q2. We expect they will continue to expand rapidly. Simply put, customer spending on Core V has gone up as customers recognize the increased value we deliver. And this operating margin improvement came before our July pricing changes, which included an approximately 25% increase across SKUs in response to the current demand.
Environment and the increasing ROI our customers are observing from their investments in the Core V platform as they shift to inference, we're also. Passing through component price increases in terms of how this. Translate to cash flows as we previously discussed, a typical five year contract carries strong and still expanding unit economics across it's term, but those economics do not arrive evenly.
The cost primarily in the form of CapEx is front loaded requiring a combination of debt, customer prepayments and other corporate level capital to finance. It's build out. Once the cluster is delivered, contracted revenue ramps becoming predictable and highly cash flow generative. This is all considered in our underwriting of expected margins before a contract is signed.
The deployment delivers attractive returns fully repaying asset level debt used to fund the CapEx while generating significant additional free cash flow. So when an initial contract ends, the cluster no longer has any leverage and we are free to recontract that cloud infrastructure or offer it to the market. We will have generated an attractive return even before the prospect of further monetizing the cloud infrastructure.
Every resale or renewal is incremental on top of the returns already earned within the initial term. What we are seeing today is that the upside of recontracting is real as we remain largely sold out of prior generations of NVIDIA GP US in addition to the current SKUs. So as our earlier generation fleets roll off their original contracts, they offer the potential to deliver strong returns in the subsequent years.
We are seeing this across our Ampere and Hopper fleet. As an example, we recently signed an A100 contract that extends into 2029 at an attractive price. As a reminder, this queue was introduced in 2020. Clusters of prior generations of architecture offer installed energized production grade compute already running at scale. They come with a proven ROI for customers.
In a market where new capacity is supply constrained and costs are rising, AI cloud infrastructure in production is a scarce valuable asset. While we have built a business whose economics do not rely on recontracting after initial customer term, increasingly we are seeing longer utilization at higher prices offering the potential for significant further upside.
With these tailwinds at our back, we are more confident than ever in the long term ROI of our product and capacity investments enabled by an industry leading AI cloud services. Now turning to Q2 results. Revenue was 2.6 billion in Q2, up 112% year over year and 24% sequentially, driven by continued strong execution and customer demand for Core V's AI cloud platform.
Revenue backlog ended the quarter at 104 billion, up to 46% year over year. As Mike noted, this does not include the over 25 billion of net new customer commitments we added early in Q3. Of the existing backlog, more than 50% is attached to a contract where customer delivery has commenced. We expect this figure to reach more than 2/3 of our Q2 backlog by the end of this year.
Operating expenses in the second quarter were 2.6 billion including a stock based compensation expense of 165,000,000. The increase in our operating expenses was a direct result of scaling our active power while converting backlog into revenue. This drove the corresponding increases in our cost of revenue and technology and infrastructure spend.
In addition, the increase in sales and marketing was driven by increased investment in our go to market organization as we further diversify our customer base and expand into new products and markets. GNA increased driven by personnel cost to support our growth while continuing to moderate versus revenue growth.
Adjusted EBITDA for Q2 was 1.5 billion compared to 753 million in Q2 of 2025. Doubling year over year. Our Adjusted EBITDA margin was 59%. Adjusted operating income for Q2 was 128 million compared to 200 million in Q2 of 2025 and up from 21 million last quarter, well above the high end of our guidance as operating leverage comes into a business with scale. Adjusted operating margin was 5%.
Margins expanded as we scaled despite continuing to increase significant ramp costs. Net loss for Q2 was 626 million compared to a net loss of 290 million in Q2 of 2025. Interest expense for Q2 was 640 million compared to 267 million in Q2 of 2025, driven by increased debt to support the continued scaling of our infrastructure and delivery of our contracted customer commitments.
We recorded an income tax provision despite a net loss due to valuation allowance on net deferred tax assets. As noted last quarter, absent significant discrete items are a change in circumstances, our tax rate should remain broadly consistent over 2026. Adjusted net loss for Q2 was 567,000,000 compared to a net loss of 130 million in Q2 of 2025.
Turning to capital expenditures, CapEx in Q2 totaled 9.4 billion, slightly above the high end of our guided range. Higher CapEx in the quarter reflects customer deliveries accelerating construction in progress. CIP increased to 11.9 billion from 9.6 billion quarter over quarter, signalling the significant amount of PP and E we expect to deploy early in Q3 based on the large amount of power we received very late in Q2.
In fact, in June, we brought on more than 300 megawatts of active power, which makes June itself larger than any full quarter in our history. As Mike noted, the global supply chain remains complex. We continue to navigate these challenges with operational discipline and leveraging our partner relationships, including new ones like Solodyne to strategic. Source required inputs turning to our.
Balance sheet and strong liquidity position. As of June 30th, we had more than 6.9 billion in cash, cash equivalents, restricted cash and marketable securities. In Q2, we made significant progress in strengthening our balance sheet and expanding the depth and breadth of our access to capital, raising approximately 18 billion across a combination of debt, convertibles and equity.
These transactions included several firsts. Like our inaugural Euro bond as well as our first ever delayed raw term loan back. By HPC infrastructure issued in the public markets. Our most recent financing, our second publicly syndicated term loan marked another. A significant milestone as the first to include shorter duration customer contracts, the transaction which priced during one of the most dislocated weeks for credit this year was met with meaningful interest.
Despite the environment at the time we chose to complete the transaction at its full size. Our spreads have retraced since. Perhaps most importantly, the transaction demonstrated the credit markets growing conviction in long term value of NVIDIA infrastructure running on Core V Cloud. This financing is significant as it unlocks our ability to serve critical part of the enterprise market at scale, while also allowing us to accelerate the ramp of our managed inference platform and grow our exposure to shorter dated contracts that typically come at a higher ASP and margins. These transactions attracted broad and deep investor participation, highlighting the significant interest we continue to see in supporting Corbiev's journey.
The combination of these transactions brings us to over $32 billion of debt and equity capital secure to date. Over the past year, we have reduced our weighted average cost of debt by almost 300 basis points, representing approximately 1.1. 1 billion of annualized interest saving based on our end of Q2 debt load.
Turning to guidance, as a result of continued strong execution, we now expect to end the year with more than 1.85 gigawatts of active power, up from our previous guidance of more than 1.7 gigawatts. In terms of how this flows through the second-half, we expect Q3 revenue to be in the range of 3.45 to 3.6 billion. We expect Q3 adjusted operating income of 200 to 260 million as margins continue to sequentially expand, reaching low teens in Q4Q3.
Interest expense is expected to be in the range of 860 to 940 million, reflecting the growth in our debt balance to finance our accelerating deployments. We expect CapEx to be 11.5 to 13.5 billion based on the significant amount of new capacity we will be delivering to customers.
Moving on to full year, our disciplined execution and the momentum we are seeing across our customer base gives us confidence in raising our full year 2026 revenue guidance to 12.4 to 13.2 billion and adjusted operating income to 960 million to 1.15 billion as a result of our increased expectations around capacity to be delivered to customers this year as well as some of our significant recent wins.
We now expect 2026 CapEx in the range of 35 to 39 billion. Finally, we're also raising our expected end of year annualized run rate revenue to 18.5 to 19.5 billion. The long term nature and attractive margins underpinning our contracted revenue backlog continue to provide us with clear visibility and we are confident in the targets we have put forward.
In closing, Q2 demonstrated the strength of the demand environment for Core V's full technology stack and the discipline of our operating model. We strategically expanded our customer base to support the next wave of enterprise AI adoption. At increasingly attractive margins, customers are expanding their spend with Core V to leverage the full depth of our AI native platform.
We remain on track for our sequential margin expansion through the balance of the year and we have made significant additional progress on our capital structure, reducing our weighted average cost of capital while securing the financing required to support our long term growth plan. We look forward to seeing many of you at our annual developer conference fully connected in September, where you will hear from our leadership and customers alike in how our platform is accelerating AI in production. Thank you. With that, we will open up for questions.
Operator
We will now begin the question and answer session. Please limit yourself to one question and one follow up. If you would like to ask a question, please press *1 on your telephone keypad. To withdraw your question, press *1. Again. Please pick up your handset while asking a question. If you are muted locally, Please remember to unmute your device. Please stand by while we compile the Q and roster.
Your first question comes from the line of Samik Chatterjee with JP Morgan. Your line is open. Please go ahead.
Samik Chatterjee
Hey guys, thanks for taking the questions and Congrats on a strong overall Brent here. Maybe just a couple of topics. 1, you did mention the renewal opportunity with shorter term contracts and some of some of the older contracts from of expiration to leverage sort of the pricing that we're seeing in the market. Can you just help us think through as you engage in some of that? With customers, what you're finding in terms of typical customer intent in terms of contract.
And how much of your install base of? Equipment is maybe up for renewal over the next few years. If you can get us give us a sense of how to think about the magnitude of that opportunity and I will follow. Thank you.
Mike
Thank you for the question. And you know, excited to spend a little bit of time with you talking about what was a truly outstanding quarter for the for the company across our infrastructure, across our software, across our solutions, across our sales and contracts with new clients and existing clients. Yeah. You know one of the most exciting components of what we are beginning to understand and what we what we believe the market is providing real insight into right now is that the older generations of infrastructure continue to have significant value for use cases within many of the consumers of AI.
And, and we've talked about this literally for years now that the the most bleeding edge solutions that are coming out of NVIDIA that we build into our cloud and deliver to our most demanding customers. That's really important for some of the most cutting edge use cases. But within that environment, in within that ecosystem, there are an enormous number of other use cases that can make use of older, more later dated skews.
And the fact that we have been able to go ahead and sell AGPU whose architecture was from 2020 in a contract that was fully priced out to 2029 really provides some insight into what the future is going to look like as this infrastructure comes off contract In terms of the capacity that's coming up for renewal, something that is a very limited part of our fleet and the ES PS of the older generation remain higher or in, you know at levels that we've seen about a year ago.
The second part of the piece that is very interesting in our business is as these fleets come off maturity, it allows us to have a great product in terms of managed inference to serve for our customers, which as Mike noted, is a very fast evolving nature of our business. Part of our business which we expect to continue to grow rapidly and expect to have about $250 million of ARR by the end of the year.
Samik Chatterjee
And for my follow up, thanks for all the details there. But in terms of the follow up, can you talk about the supply chain a bit? You're obviously navigating it pretty well. Capacity online, but in terms of the agreement that you have now with solid I'm for. Example how are you looking at? Sort of the need to maybe do something more broad based. Across supply chain in terms of longer term agreements to assure yourself of more supply. As well so that you can continue to sort of execute on the power, on the capacity that you want to bring online. Thank you.
Mike
Yeah, it's, it's, it's great question. So look, end of the day, my job is to ensure that this company has the capacity to deliver the product that our clients require. And in order to do that, we need to aggressively manage a complicated supply chain and that supply chain includes everything from land and power and shell through GPUs and networking through memory, all of which is being challenged by the growth and expansion of artificial intelligence.
In order to do that, we have built over the last several years really long standing deep relationships with our Odms, our OEMs, NVIDIA, the the companies that supply us with memory, all of them. And what we've done is we've thought about what is necessary, sorry, to ensure that we have access to the infrastructure and the components and the capital that we need in order to deliver our products at a acceptable price and quality to our clients.
And it's one of the things that's just embedded in the DNA of Core Weave. That's what we do. It's part of what we do every single day is nurture these relationships and ensure that we have access to everything that we knew need in order to deliver the product, which is media infrastructure delivered through our cloud. Now one thing coming to note here is the increase in the value of output of the Core V cloud has outpaced the value of the input.
You know, input increases that we are currently experiencing in the supply chain. And as a result of it, what you're seeing is margins expand. As Mike noted, you know in his comments around, you know, the typical contribution margins that we saw last quarter were 5 to 10 percentage points higher than what we've observed in the recent quarters.
Samik Chatterjee
Great, great. Thank you. Thanks for taking my questions.
Operator
Your next question comes from the line of Brad Zelnick with Deutsche Bank. Your line is open. Please go ahead.
Brad Zelnick
Great. Thanks very much and Congrats on the strong execution. My my first question, I wanted to ask about your managed inference offering which is off to a really strong start. What are your initial learnings and and what are the factors that inform your thinking on allocating capacity to it going forward versus your traditional take or pay deals? And I have a follow up to that as well. Thanks.
Mike
Yeah, thank you for for the compliment. It really was a great, great quarter for us. We're very excited about it. Look, when when we think about our offering, we really think about it holistically and we have made enormous strides through the last several years to focus on building scale through these long term take or pay contracts. As we've hit hyper scale, we understand that we are going to need to broaden our offering to provide the products that our clients needs that to deliver products that have higher margins, to provide the software solutions, to provide access to CPU's, all of the things that are necessary for our clients to be successful.
And when we think about the the the the lessons that we've learned as we've gone through this unbelievable and unique scaling of our managed inference product, which went from $1,000,000 to $100 million inside of a single quarter. We really think about the fact that, that is an incredible opportunity for us to offer the most bleeding edge compute that we have, but also a wonderful way for us to access and use contract, the GPS that are coming off contract in a way to extract maximum value for the company at overtime.
So look, the market is very deep. We think that we have an embedded advantage because of our control over the silicon and we think that we're going to be very successful in that market overtime.
Nitin
And Brad, one thing to note here is you know, we announced yesterday around our DDTL 5.5 closing and that shows that the capital markets are extremely interested and supportive of core Reefs, you know product in terms of underwriting shorter duration contracts which is definitely. Tailwind as we look at these markets to support our customer needs.
Brad Zelnick
Thank you, Nick, and thank you, Mike. That actually leads to my next question. So on the five to 10% better margin that you're seeing on on recent deals that you're signing, can you help unpack the drivers? How much is a function of shorter duration deals versus strong competitive differentiation or other factors? And what are you seeing more broadly just out there in the market as it relates to pricing? Thank you.
Mike
So it's a combination of a lot of things and it's difficult to, to, to deconstruct it. The infrastructure that we deliver through the Core Weave Cloud is more valuable to our customers than any other solution that they can encounter. The, the, the quality of the platform, the reliability of the infrastructure, the security, the TCO, all of those things contribute to customers coming back to us again and again and expanding their footprint within our our cloud and infrastructure.
And so there is a piece of it which is they understand how much more valuable a given piece of infrastructure is delivered through us. The second piece of it is many of our clients are monetizing their products and so they are more aggressive about coming in and willing to pay us higher margins because they need access to the compute that will allow them to be successful.
The, the, the, this is a phenomenon that's occurring across the infrastructure space, but it's particularly occurring within our ecosystem. And it's very exciting to see as the premium product that we deliver is priced in a premium fashion by the consumers of this compute.
Brad Zelnick
Thank you.
Operator
Your next question comes from the line of Amit Daryani with Evercore ISI. Your line is open. Please go ahead.
Irvin Lou
Hi, thank you. This is Irvin Lou on for Amit. I had one and a follow up. So my first question is it, it sounds like there's upward pressure to pricing across multiple vectors including you know the higher value you provide to your customers, the pass through of higher component cost and the recontracting opportunity coming up. So with that in mind, should we still think of kind of the 18 to $19 billion in ARR as kind of the exit target for 2027?
Nitin
Yeah. So we increase the exit ARR number that we provided in guidance to you folks right now at 18 1/2 to 19 point 19 1/2 for 2026. So that is baked in our guidance that we provided to you.
Irvin Lou
Got it, got it. Thank you for that. And then for my follow up, I think the regulatory backdrop for data centers appears to be increasingly difficult. You know there have been reports of local opposition to data centers. With this in mind, can you talk about your confidence level in deploying more than three gigawatts of active power by the end of next year and kind of your road map to 8 gigawatts by the end of the decade? Thank you.
Mike
Sure. And your question is very timely and very important for the entire AI space and the entire data center space. I guess I'll start with we, we, we believe that the, the certain communities have moved forward with moratoriums and we, we feel like moratoriums are they're, they're not going to impact the demand for this infrastructure. They are going to impact where this infrastructure gets built.
And so our approach to how you engage with the stakeholders is that you have to be extremely collaborative with the communities that ultimately host the infrastructure. And that's based on transparency. You have to work with the local governments, you've got to work with the utilities, you've got to work with the policymakers in order to allow yourself to to ensure that what you're building fits into the communities that you're entering.
You know, ultimately, at the end of the day, it is in our interest and it is in their interest for us to be good neighbors and of their community. A lot of that comes down to making sure that you're paying for grid upgrades so that it doesn't fall or impact the rate base. You know, you create an enormous number of construction jobs. You, you, there are long term jobs that are left that, that that survive within the data centers. You know, the data centers that that are being built contribute to the tax base.
All these things are are incredibly important to how you. You enter into a community and how you engage that community as you're building this infrastructure that is so necessary in order to be able to provide America's AI leadership. And so you know when we when we talk through the numbers with with you guys, we basing our progress on where we are today and what we have guided here. None of those numbers will be impacted by the regulatory pushback as of today.
We are comfortable with it. We continue to expand, we continue to engage our, our, our data centers are, are are best in class and we expect to be held to that as we continue to build our infrastructure across the globe.
Nitin
And Irving, just to give you some numbers in perspective here, you know, if you look at our gigawatts contracted today, they're already at 4.2 gigawatts contracted. In addition, we have about 1.5 of powered lag options to execute LO is that we have executed that puts you close to about 6 gigawatts already in terms of how we think about power and it's middle of 2026. So we remain well on track to execute against our stated goal. Upgraded that 8 gigawatts of active power by end of 2030.
Irvin Lou
Got it. Thank you for the color.
Operator
Your next question comes from the line of Raimo Lenschow with Barclays. Your line is open. Please go ahead.
Raimo Lenschow
Thank you. Congrats from me as well. I just I wanted to talk a little bit about the growing importance of inference for you guys. How does your fleet need to evolve because inference needs to a lot more CPU, a lot more storage. Can you do that in the existing data centers? Do they need to involve, can you speak to that as well to make sure we have the capacity they're going forward?
Mike
Yeah, it's a great question. It's, it's a question we've been talking about now for several quarters. We believe that when you're building infrastructure, you don't, you don't build infrastructure for training and you don't build infrastructure for inference. You build AI infrastructure. And when you build AI infrastructure, you need to ensure that you have all of the components to be able to serve the full AI loop, everything from training through inference as it cycles back and forth, as it moves through the, the, the iterations that are required in order to serve your clients and those companies that are consuming this.
And so really the infrastructure that we built will move seamlessly into the ability to serve inference over time.
Raimo Lenschow
OK, perfect. And then one follow up is like obviously with the news from Meta yesterday, a lot of questions that we faced today was around doing AI in the edge etcetera. And then you know all these concerns came up again. Like can you talk about like how you see the market evolving between edge smaller clouds, New York clouds and the hyperscaler? Thank you.
Mike
Yeah, one of the one of the things about Core Weave that should never be underestimated is we sit at the epicenter of an incredible amount of information flow from across the entire industry, right. The hyperscalers use us, the, the labs and use us. You've seen enterprise begin to scale within our platform. The, the, the information flow that's coming back and feeding us the, the clues to how the world is going to look in the future has been incredibly powerful for us in terms of how we position our our, our, ourselves and our compute to serve our clients.
Look at at the end of the day, we believe that there are workloads that are going to be served from the edge and there are workloads that do not require the same level of latency protection. And we have built our cloud to be able to serve both of those constituents effectively and we will continue to build in that fashion. We will be informed by our clients continuously whether they need a little bit more of edge, they need a little bit more of scale that is not as latency sensitive.
All of those things are being fed to us on a continual basis. And so, yes, we do see workloads on the edge and yes, we do see workloads that don't require to be on the edge. And we are very, very comfortable that the scale of our infrastructure and the ability to move it back and forth is going to provide a competitive advantage for core weave overtime.
Nitin
Very much to your point in terms of increased competition, even with this increased competition, we are seeing demand, pricing and margin all expanding, which is a signal. For the growth in the cold weave kind of you know product as well as you know our growth in overall. In an already massive term that exists.
Raimo Lenschow
Yeah, exactly. Yeah, OK, makes sense. Thank you.
Operator
Your next question comes from the line of Michael Turin with Wells Fargo Securities. Your line is open. Please go ahead.
Michael Turin
Hey, great. Thanks very much. Appreciate you. You taking the question, I realize there's likely some rounding here, but you added an impressive 500 megawatts of active power in the quarter of the revenue. If we're looking at the sequential ads is fairly consistent of last quarter. We can hear all the commentary around the uplift that's coming. So then maybe help us think through the linearity of capacity added and when that 300 megawatts added in June starts to hit more of a steady state in terms of model contribution.
And also would be useful as a second part to hear any early market signals you're gathering on, on Vera Rubin monetization and what the uplift there could look like versus prior generations? Thank you.
Nitin
Yeah. So as you mentioned, like you know you saw Q3 we added about, you know, sorry, Q2 we added about 500 megawatts of power. 300 of that alone was in the month of June, which is higher than any amount of power that we've added in any history of prior quarter for coral reef. So definitely that power was back in load. In terms of Q2, which you will start seeing kind of come through in Q3 and Q4 in our business. And then in terms of the.
Mike
Yeah, so, so let me, let me maybe I'll take a moment to speak to you, to Vera Rubin. Vera Rubin is, is, is a generation that is seeing the margin expansion right from the start. And so it's really exciting for us. You know, the demand for the Vera Rubin platform is enormous and the pricing power that Core Weave has been able to garner with its Core Weave cloud delivering that infrastructure really bodes well. And when we were talking about that, you know, 5 to 10% margin step function that we're seeing, you know, a lot of that is coming in, in the beer Ruben skew, We're we're we're excited about where that's going to lead. We think that it's going to be a very, very successful SKU for core weave and core weave coins.
Michael Turin
Thanks very much.
Operator
Your next question comes from the line of Brett Knoblauch with Cantor Fitzgerald. Your line is open. Please go ahead.
Brett Knoblauch
Hi guys, thank you for taking my question. Congrats on the the very strong quarter. Mike, I guess just kind of based on the prepared remarks, it looks like the price environments never really didn't better for older generation and obviously newer generations you've used here. As you look at the GPU fleet that's maybe rolling off contracts. Can you talk about the cadence of how you guys look to either re contract that or kind of put it on spot or in your inference products? And how far in advance of the roll off of those contracts would you look to kind of make that decision?
Mike
Yeah. So look, it's a good question. It's one we're working through. Keep in mind that the, the environment for inference is incredibly dynamic and it is scaling so fast as we you know, kind of struggle to keep up with the, the build out of new infrastructure. The the, the flexibility that we are given because we have infrastructure coming offline allows us to continue to scale the inference product as we're continuing to explore exactly how big, how, how expensive is the manage inference opportunity for us.
Some of the infrastructure that comes offline, we go ahead and we place back into a term contract if we think the economics warrant putting it in. And the economics include both the term that we're able to garner, you know, as we think about the, the, the long term stability of the company and the long term obligations that we need to support as we continue to build and scale the company.
But we also do recognize that in the short term, there is an opportunity to sell on shorter term contracts and extract additional margin on this infrastructure as the world tries to catch up with what is a systemic disequilibrium that has really existed for several years now and will continue to exist for the foreseeable future.
Brett Knoblauch
Anything that kind of leads to my next question, I guess off the back of DDTL 5.5 where you were able to kind of get funding for shorter duration contracts combined with kind of this data center Nimbyism, you know, political atmosphere that's kind of taking off. It feels like you guys should be quite well positioned given you are the most scaled to realize the most price benefits. How does the success of DTL 5.5 change the way you view on kind of target durations on a go forward basis? Does is that an ad you want to use more to maybe extract more margin and shorter duration contracts given, you know, the useful life is there?
Mike
Yeah, I mean you're you're, you're, you're exactly right. The the, the, the execution of the DDTL5 puts Corwave in a position where we get to populate the curve in terms of what we think is the most profitable configuration for term leasing. And so we want to sell our compute on long term contracts. We also want to sell it on shorter term contracts to extract additional margin and we have been really, really aggressive about doing that.
We were the first ones to bring the 5.5 to market in order to be able to really plug into those. There's there's one more really important part of the short term contracts that I think it's important for everyone to understand when you're thinking about enterprise. Enterprise tends to want to enter into contracts that are not five years in length. They tend to think in shorter cycles than that and so.
By enabling the financing market to support the the the contracts in 5.5, we're able to go ahead and diversify our terms so that we're able to support additional contracts. It opens up whole new markets for us. These clients want to buy compute for two years or three years and that's not a market that was easily accessible to us until we were able to bring DDTL 5.5 to market. And now that market will accelerate meaningfully as we're able to offer compute to our customers on a time frame that they are able to consume it, buy it and enter into contracts to purchase it from us.
Brett Knoblauch
Awesome, well said. Thank you, Mike.
Operator
This concludes our question and answer session. I will now turn the call back to Mike in Trader for closing remarks.
Mike
Before we sign off, I want to thank our team, customers and partners for their trust, hard work and commitment to core weave. None of these achievements would have been possible without you. I'm incredibly proud of what we have accomplished together and for what comes next as we build the essential cloud for AI. Thank you all for joining today. We appreciate your support and we look forward to updating you on our progress in the quarters to come.
Operator
This concludes today's call. Thank you for attending. You may now disconnect.
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