Meta Platforms, Inc.

Q4 2025 Earnings Call — January 28, 2026

Analyst Brian Nowak (Morgan Stanley): Thanks for taking my questions. One for Mark, one for Susan. Mark, one is a long-term question. As you think about ramping all this investment and the personal intelligence opportunity, the metacompute opportunity, can you walk us through a little bit how you think about the largest revenue or ROIC long-term opportunities you're trying to unlock with those over the next, call it three, five, 10 years for all the investment? And then Susan, a little more near term, more like 26, I think the guide is the fastest growth you've had in almost five years. I know you have a lot of improvements on recommendations and monetization efficiency, but can you just sort of help us a little bit understand two or three of the biggest drivers of this inflection you're seeing on revenue in 26?

Executive Mark (CEO): I guess I can start with the first one. Although I have to say up front that I think my answers to a lot of your questions on this particular call may be somewhat unfulfilling, because we're in this interesting period where we've been rebuilding our AI effort. And we're six months into that, and I'm happy with how it's going. But we are going to be rolling out our initial set of models and products and businesses around that over the coming months and I will have a lot more to share on all of those fronts at that point. So I'm happy to offer kind of a high level view of some of the stuff but I apologize in advance that not much of this is going to be particularly detailed but it will be exciting as we roll it out.

I think the theme on the business, I mean this is I don't think I'm going to break any new ground here, but there are several major business opportunities that we're focused on. I think that one is just going to be improving the core products and accelerating the current business. I talked about that in terms of the connecting of the recommendation systems and the LLMs, which I think will both improve the quality of the organic experience and of advertising. We're going to see the generation of media improve the quality of content which coupled with the improvements in the recommendation systems we expect to generally accelerate the quality and effectiveness of the core business both for people who use it organically and for businesses.

There's going to be several, many, I think, new business opportunities that come up. I mean, we have been working on Meta AI for a while. I think you're starting to see some of the way that products like that get monetized across the industry. When we get that to a scale and depth that we want, we think that there are going to be opportunities both in terms of subscriptions and advertising and all of the different things that you see on that. I mean, yeah, I think there's a number of things on shopping and commerce that I'm quite excited about that I alluded to in the comments up front. And as the models launch and we demonstrate some of the capabilities, both in the first set of models and over the year, I think the models are going to get a lot better too.

We'll be able to have different products paired with those that I think will facilitate different businesses for businesses who use us and our platforms as well as direct consumer businesses. I guess it's probably also worth flagging because I don't think either of us mentioned the Manus acquisition in the upfront comments. I think that that is a good example of you have a significant number of businesses that already pay a subscription to basically use their tool to accelerate their business results. And integrating that kind of thing into our ads and business manager, so that way we can just offer more integrated solutions for the many, many millions of businesses that use and rely on our platforms is gonna be really powerful, both for accelerating their results using the existing products that we have, and I think adding new lines as well.

In 2026, we expect to deliver operating income above 2025 operating income. So to give some context on that, we are going into 2026 with strong revenue growth at the start. Of course, we are just a few weeks in, set against a healthy macro backdrop. So obviously hard to extrapolate the current trends to the full year. And, you know, there are many, many moving variables in the current landscape. We're really taking advantage of the current business strength to reinvest a lot of the revenue into what we see as very attractive investment opportunities in AI infrastructure and talent.

Analyst Eric Sheridan (Goldman Sachs): Thanks so much for taking the question. Maybe two, if I could. In prior periods, you've talked about being capacity constrained internally and not having enough compute to sort of achieve the goals you have on a platform and a product standpoint. I want to know if we get any update on currently how you think about your own internal needs for compute against that roadmap. And the second part of the question would be, as we continue to see the ads business sort of scale, especially in terms of dollar growth year on year. Have we yet seen the full first order effects of scaling the business against applying more compute to it? Or how should investors think about the direction of relationship between applying more compute and rate of change in terms of outcomes on the monetization side?

Executive Susan (CFO): On your first question, we do continue to be capacity constrained. Our teams have done a great job ramping up our infrastructure through the course of 2025, but demands for compute resources across the company have increased even faster than our supply. So we expect over the course of 2026 to have significantly more capacity this year as we add cloud, but we'll likely still be constrained through much of 2026 until additional capacity from our own facilities comes online later in the year. With that said, I think we have done a good job internally mitigating the impact of compute constraints on our business. I expect that will continue to be the case in 2026. We're continuing to focus on increasing our infrastructure efficiency in several ways, including by optimizing workloads, improving infrastructure utilization, diversifying our chip supply, and just investing in efficiency improvements as part of our core technology development efforts in areas like content and ads ranking.

So that was your first question. The second question about how the ads business scales. I don't have an extremely precise answer to this question. What I'd say is one of the ways that we are working to drive ads performance improvements is by improving our larger scale models along with our lighter weight ones that we use for ads inference at runtime. You know, we don't typically use our larger model architectures like GEM for inference because their size and complexity would make it too cost prohibitive. So the way that we drive performance from those models is by using them to transfer knowledge to smaller lightweight models used at runtime. But I would say that we think that there is room for our larger models to benefit from having more compute. And I think as we scale up the compute available to those models and the foundational models in different areas that power the different stages of ads ranking and recommendation, we expect that we will see gains coming from that.

Analyst Mark Shmulek (Bernstein): Yes, thanks for taking the questions, too, if I may. Mark, kind of with your comments that you kind of expect to see some meaningful changes in how work and things are done this year, I guess would you be surprised if kind of by the end of the year we've yet to see meaningful progress and adoption on some of the newer products and initiatives that you're launching? Or, you know, should we just be a bit more patient on the timeline here? And then, Susan, kind of with the guidance provided on why it's still expected to grow kind of faster this year than last year, let's say in a few months we realize we need more investment and resources that continue to go after the AI opportunity, but perhaps macro might be a bit weaker. How hard of a line is there in terms of the tie of investment levels to core performance?

Executive Mark (CEO): I think the first question was asking about kind of when do I expect the product impact to be? I mean, we're going to roll out new products over the course of the year. I think the important thing is we're not just launching one thing and we're building a lot of things. I think AI is going to enable a lot of new experiences. I outlined thematically a bunch of these in the upfront comments around personal AI, around LLMs, combining with the recommendation systems. I think that's a somewhat longer term research project that I think will yield dividends over a long period of time. But we're already definitely seeing optimizations of the recommendation systems as we're including more of the AI research improvements and advances into that, the content is gonna improve.

There are gonna be new formats. There are gonna be improvements on the glasses. There are all these different things, as well as several things that we think are new that we're gonna try that are not just extensions of the current things that we're doing. So yeah, I mean, I would expect that we'll roll these out over the course of the year and that sometimes it takes a few iterations for things to really hit and reach the kind of product market fit that you need. But I think we have enough time hopefully to, you know, we're starting off early enough in the year that I would expect that we'll see some successes by the end of the year on this as well as on the work side.

What we were talking about is I think it's very hard for anyone exactly to predict what the shape of how organizations working is going to feel, but I just think the fact that agents are really starting to work now is quite profound and I think is going to allow, we're already starting to see the people who adopt them are just being significantly more productive. And there's a big delta between the people who do it and do it well and the people who don't. I think that's going to just be a very profound dynamic for, I think, across the whole sector and probably the whole economy going forward in terms of the productivity and efficiency with which we can run these companies.

In 2026, we expect to deliver operating income above 2025 operating income. So this is comparing absolute dollars, not year over year growth. So to give some context on that, we are going into 2026 with strong revenue growth at the start. Of course, we are just a few weeks in, set against a healthy macro backdrop. So obviously hard to extrapolate the current trends to the full year. And, you know, there are many, many moving variables in the current landscape. We're really taking advantage of the current business strength to reinvest a lot of the revenue into what we see as very attractive investment opportunities in AI infrastructure and talent.

Analyst Doug Anmuth (JP Morgan): Thanks so much for taking the questions. One for Mark and one for Susan. Mark, could you just provide more detail on the progress of the MSL team several months in and more on your view on the path to a frontier model this year? And then, Susan, I know you expect to grow operating income in 26. Do you also expect to have positive free cash flow? Just how should we think about the current and any future JVs for data center and compute build out?

Executive Mark (CEO): I'm not sure I have anything else to add on the current progress on this. That's why I said upfront that I think this is somewhat of an unfulfilling time to be answering some of these questions. We're about six months into building MSL. I'm very pleased with the quality of the team. I think we have the most talent dense research effort in the industry and some of the early indicators look positive. But look, I think that this is a long-term effort. We're not here to do this to ship like one model or one product. We're doing a lot of models over time and a lot of different products. And I want to make sure that the work can speak for itself and also that we all internalize that this is a journey that we're on.

We're making very significant investments in infrastructure capacity this year to support our AI efforts. And we believe we're in a strong position to support them with the cash generation of our business this year. And, you know, at the same time, we'll continue to explore different paths as we build out our infrastructure capacity that help us provide, you know, that help provide us the long-term flexibility and option value that we look for as we support our future capacity needs against the backdrop of a very wide range of possible capacity demand over the years to come.

Analyst Justin Post (Bank of America): Great. A couple, maybe one for Mark and one for Susan. It just seems like you're going to have a tremendous amount of capacity. How do you think about expanding your opportunities beyond ads? Things like subscriptions or licensing cloud models, just with all the interesting things you're building. I don't expect any product announcements, but can you do things beyond ads? And then for Susan, it's really interesting to see the acceleration, even XFX in advertising. I'm just wondering if you're seeing a general acceleration in e-commerce activity, where do you think the dollars are coming from? And is the entire internet ecosystem accelerating? I'm just wondering your thoughts on that.

Executive Mark (CEO): So yes, we are focused on things beyond ads. I think the numbers make it so that for the next couple of years, ads are going to be by far the most important driver of growth in our business. So that's why as we're working on this, we have a balance of new things that we're trying to do while also investing very heavily in making sure that all of the work that we're doing in AI improves both the quality and business performance of the core apps and businesses that we run there.

Executive Susan (CFO): Justin, on your second question, we saw healthy year over year growth across all verticals in Q4 with the exception of politics as we lapped the U.S. presidential election last year. The online commerce vertical was the largest contributor to year-over-year growth. That was followed by professional services and technology. So in online commerce, year-over-year growth was strong. It was actually relatively consistent with Q3 levels, and that was broad-based across advertiser regions and sizes. In general, we saw that the demand leading up to the holiday shopping period sustained through cyber five and into the end of the year, you know, it was very healthy for us.

Analyst Ross Sandler (Barclays): Mark, you mentioned bringing Horizon World into mobile. We haven't heard much from the Horizon World Squad on these calls. So interesting that that's making it in. It seems like the combo of AI and what you guys have built with Horizon might open up the door to a bunch of new potential areas in gaming or new forms of communication. So could you just elaborate on what the plan is there?

Executive Mark (CEO): Yeah. So let me talk about the basic theme here. One core idea that I've talked about on some of these calls over the years is that people always want to express themselves and experience the world in whatever the richest format is that they can. So I talked about this up front today. When we started, a lot of this was text, right? That was the kind of the best we could do. Then we all got phones, they had cameras, like a lot of this medium became visual, but with photos. We went through a period where the mobile networks were kind of weak and every time you wanted to watch a video would buffer. And once that got worked out, now the majority of the content is video.

I think that we're going to get more formats that are more interactive and immersive. And you're going to get them in your feeds. So you can imagine this. I mean, there's obviously a lot of details to fill in on this. But you can imagine being able to easily, through a prompt, create a world or create a game and be able to share that with people who they care about. And you see it in your feed and you can jump right into it and you can engage in it. And there are 3D versions of that and there are 2D versions of that. And Horizon, I think, fits very well with the kind of immersive 3D version of that.

Analyst Ron Josie (Citi): Great, thanks for taking the question. I wanted to drill down maybe, Susan, on your comments around ranking recommendation model changes. You know, clearly lots of tailwinds here, given the results from GEMS, Andromeda, Lattice, consolidation of models, et cetera. So can you help us understand a little bit more just about the roadmap and where we stand within ranking recommendation model changes?

Executive Susan (CFO): Yeah, thanks for the question, Ron. You know, we have, I'm just, I was sorting out if your question was more specific to ads or if it was more specific to kind of the engagement side, but I'll try to talk a little bit about both. So on the sort of core engagement piece, you know, we launched several ranking improvements in Q4 on Facebook and Instagram that drove incremental engagement. And there isn't really one single launch that is driving most of the gains. It's multiple optimizations to our recommendation systems that are helping us make more accurate predictions about what will be interesting to each person.

We see a lot of headroom to improve recommendations in 2026, which we expect will drive additional engagement growth on both apps. First, we plan on to continue scaling up our models and increase the amount of data we use, including a longer history of content interactions to further improve the overall quality of recommendations. We're also going to start validating the use of ad signals and organic content recommendations as we continue to work towards having a more shared platform for organic and ads recommendations over time.

Analyst Ken Gawrowski (Wells Fargo): Thank you very much. Two, if I may, please. First, for Mark, how critical is it for META to have a leading general purpose model? Or is there a sufficient capability in a model that really excels at specific use cases, maybe similar to what you see at Anthropic in coding today? We'd love to, if you could, opine on that. And then second, maybe, I just want to push again, maybe on this last question, Susan, on the visibility you have. You talked about the improvements you're making in 26 on the models, the fine tuning of the core, both in engagement and ad relevance. Could you talk about, are you seeing any signs of diminishing returns to those investments? And do you think, do you have visibility beyond 26 into further opportunities there?

Executive Mark (CEO): I think the question was around how important is it for us to have a general model. You know, the way that I think about Meta is we're a deep technology company. Some people think about us as we build these apps and experiences, but the thing that allows us to build all these things is that we build and control the underlying technology that allows us to integrate and design the experiences that we want and not just be constrained to what others in the ecosystem are building or allow us to build.

I think it's very important to be able to have the capability to build the experiences that you want if you want to be one of the major companies in the world that helps to shape the future of these products. But yeah, I mean, I think it's quite important, otherwise we wouldn't be so focused on this where we're clearly extremely focused on this.

Executive Susan (CFO): On your second question, interestingly, a year ago on this call, I think I talked about the set of investments we were making in 2025 as part of our 2025 budgeting process across our ads performance and organic engagement initiatives. And those investments have generally paid off. And we feel really good about the process we ran in terms of using projected ROI to stack rank investments, make sure that we had a robust measurement system, funded things that were positive ROI, and then tracking how they performed over the course of the year.

And we've just finished running our 2026 budgeting process, and we have funded a similar set of investments, which we expect will enable us to continue delivering strong revenue growth in 2026. Having said that, I expect both full year reported and constant currency revenue growth to be below the levels in Q1 for a few reasons. First, we would expect that currency tailwinds will dissipate later in the year based on current rates. Second, we'll be lapping stronger periods of growth later in the year that benefited from our 2025 ad performance investments and the strong macro landscape.

Analyst Mark Mahaney (Evercore): Okay, two questions, please. Meta AI, any update on what you're seeing there in terms of engagement and usage? And do you think you're just starting to be able to apply improvements to that specific functionality? And then just real quickly on share repurchases, Susan, I don't think you bought any stock back in the quarter. It's been a while, maybe a year since you haven't bought anything back. You talked about capital allocation a little bit into the year. It didn't sound like...

Q3 2025 Earnings Call — October 29, 2025

Brian Nowak (Morgan Stanley): Thanks for taking my questions. I have two for Susan. The first one, Susan, so the pipeline for core improvements to come in 26 with models and ad ranking models and more types of compute seems very exciting, and the infrastructure build seems sizable behind that. Can you help us a little understand some of the early quantifiable signals you're seeing on AB tests from some of these improvements to come that sort of make you most excited and give you confidence. You're going to get ROIC from all this CapEx? That's the first one. Second one's a little faster. How large is the Reality Labs revenue headwind in the 4Q guidance? Thanks.

Susan (Executive): Thanks, Brian, for the question. I think your first question had a couple parts to it. So I'm going to try to disaggregate those parts and let me know if this addresses what you're getting to. I will say that the growth in 2026 CapEx relative to 2025 comes from growth in each of the core areas, MSL, core AI, as well as non-AI spend. So all of those areas are growing, but the MSL AI needs are growing the most. In terms of the core AI pipeline, I think we talked about last year when we were going into the 2025 budget process, we had a roadmap of resource investments across both headcount and compute that we thought would pay off in 2026. And it's really a very broad range of sort of different ads ranking and performance efforts. And we're continuing to see that those have paid off through the course of the year.

There is a long list of specific efforts, but one of the measures that we look at to monitor this is how are we driving ad performance? How are conversions growing? When we control for that and look at value-weighted conversion rates, we're seeing very strong year-over-year growth and weighted conversions continue to grow faster than impressions. We also talked about some of the new model architecture over the course of the year and the degree to which the new model architecture is enabling us also to take advantage of having more data and more compute to drive ads performance. So we expect that that's going to be a continued story in 2026. We are, in fact, at the beginning of our 2026 budgeting process now, and we see a similar list of revenue investments that we're excited to be able to invest in. And so we think that that's going to be a big part of our ability to continue to drive strong revenue performance throughout the year. On your second question, which is the Reality Labs revenue headwind, I don't think we have quantified the exact size of that. We expect that Q4 Reality Labs revenue will be lower than last year for a couple reasons that I alluded to.

The biggest factor is we're lapping the introduction of Quest 3S and Q4 of last year, and we don't have a new headset in the market this year. We also recorded all of our holiday-related Quest 3S sales in Q4 24 since the headset was launched in October 24. This year, we're recognizing some of those Quest 3S sales in Q3 as retail partners have procured Quest headsets in advance of the holiday season. We're still expecting significant year-over-year growth in AI glasses revenue in Q4 as we benefit from strong demand for the recent products that we've introduced, but that is more than offset by the headwinds to the Quest headsets.

Doug Anmuth (JP Morgan): Great, thanks for taking the question. I appreciate the strategy to front load capacity for superintelligence. Can you just talk about your thought process in kind of triangulating the capex dollar growth and the significantly faster expense growth next year with core growth in the business and then the impact on earnings and free cash flow? And do you have targets that we should be thinking about for cash on hand or net cash overall? Thanks.

Susan (Executive): Thanks, Doug. We're right now, I would say, in the process of relatively early, actually still in the process of putting together our budget for 2026. And it is on the capacity side, a particularly dynamic process. We're certainly seeing that we wish we had more capacity today than we do. We would be able to put it towards good use. Certainly not only would the MSL team appreciate having more capacity, but we'd be able to put it towards good and ROI positive use in the core business as well. So we're really trying to plan ahead, not only to ensure that we have the capacity we need in 2026, but also to give ourselves the sort of flexibility and option value to have the capacity that we think we could need in 27 and 28. So that said, you know, there are lots of moving pieces in the budget. It's not baked yet. It's still sort of in the process of coming together. We don't have, you know, specific targets to share. But we do feel like, you know, our strategic priority is really making sure that we have the compute that we need to be well positioned to succeed at AI.

Management: Yeah, I mean, I'll add a few thoughts on this too, although, I mean, as Susan said, we're still working through the actual budget and I think we'll typically have more to share on that early next year. But to date, we keep on seeing this pattern where we build some amount of infrastructure to what we think is an aggressive assumption. And then we keep on having more demand to be able to use more compute, especially in the core business in ways that we think would be quite profitable than we end up having compute for. So I think that that suggests that being able to make a significantly larger investment here is very likely to be a profitable thing over some period. The primary use of it is going to be to accelerate the AI research and the new AI work that we're doing and how that relates to both the core business and new products. But any compute that we don't need for that, we feel pretty good that we're going to be able to absorb a very large amount of that to just convert into more intelligence and better recommendations in our family of apps and ads in a profitable way.

Now, I mean, it's, of course, possible to overshoot that, right? And if we do, I mean, this is what I mentioned in my comments, then, you know, we see that there's just a lot of demand for other new things that we'd build internally, externally, like almost every week, people come to us from outside the company asking us to, you know, stand up an API service or asking if we have different compute that they could get from us. And we haven't done that yet. But obviously, if you got to a point where you overbuilt, you could have that as an option. And then, you know, the kind of the very worst case would be that we effectively have just pre-built for a couple of years, in which case, of course, there would be some loss and depreciation, but we'd grow into that and use it over time.

So my view on this is that rather than continuing to be constrained on CapEx and feeling in the core business like we have significant investments that we could make that we're not able to make that would be profitable, that the right thing to do is to try to accelerate this to make sure that we have the compute that we need, both for the AI research and new things that we're doing, and to try to get to a different state on our compute stance on the core business. So that's kind of how I'm thinking about that overall. Of course, there's a lot of operational constraints, too, on what one can build, right? So we're basically trying to work through this all, and I think we'll have more to share in the coming months and over the course of next year. But I think that there's just a huge, huge amount of opportunities ahead here.

Eric Sheridan (Goldman Sachs): Thanks so much for taking the question. Mark, I wanted to reflect on some of your comments with respect to scaling towards superintelligence and bringing it back to consumer AI. Maybe reflect a little bit on the signals you've gotten on the way consumers across family of apps interact with Meta AI today and how you think about scaling and exiting models from the superintelligence effort might change the utility and behavior around Meta AI in the years ahead. Thanks.

Mark (Executive): Yeah, I mean, a lot of people use Meta AI today. I mean, as I said in my comments up front, there's more than a billion people who use it on a monthly basis. And what we see is that as we improve the quality of the model, primarily for post-training Lama 4 at this point, we continue to see improvements in usage. So our view is that when we get the new models that we're building in MSL, in there and get truly frontier models with novel capabilities that you don't have in other places, then I think that this is just a massive latent opportunity. I would guess that Meta, I think, has the best track record of any company out there of taking a new product that people love and getting it to billions of people in terms of usage. So I think that the ability to plug in leading models is going to... I would predict lead to a very large amount of use of these things over the coming years. So I'm very excited about that in terms of new products. It's not just Meta AI as an assistant. I think that there are gonna be all kinds of new products around different content formats.

And we're starting to see that with video and content creation, but I think that there's gonna be a lot more like that, that I'm quite excited about. And then there are the business versions of all of these too, like business AI. And then that's, of course, one part of the story is the new things that will be possible to build. And then the other part is how more intelligent models are just going to improve the core business and improve the recommendations that we make across the family of apps and improve the recommendations and advertising. As we've shown, there's sort of this very large amount of headroom, and the opportunity there keeps growing as we are improving and optimizing the AI there. And I think that that really shows no sign of being near the end. I think that there's quite a bit more to do there. And like I said in response to the last question, we are sort of perennially operating in the family of apps and ads business in a compute starved state at this point, which is on the one hand, sort of an odd thing to say, given the compute that we've built up. But we really are taking a lot of the resources and using them to advance future things that we're doing.

And we think that there's a lot more compute that we could put towards these that would just unlock a huge amount of opportunity in the core business as well.

Mark Shmulek (Bernstein): Yes, hi. Thanks for taking the questions. Susan, as you think about the visibility into kind of the runway next year of continued ad performance and engagement improvements, how do you think about kind of the scale of those improvements versus kind of the progress we've seen over the last two years? And then, Mark, as you think about kind of the timing of some of these newer efforts coming out of super intelligence labs, is us anchoring to kind of an updated frontier model launch sometime next year, like the right way for us to think about it? Or should we be looking at kind of progress from new products you're excited to see ship like vibes? Thank you.

Susan (Executive): Thanks, Mark. So on the sort of ads improvement side, you know, some of the innovations that we have been launching actually involve sort of improving our larger scale models. So we, you know, don't use our larger model architectures like GEM for inference because their size and complexity would make it too cost prohibitive. The way that we drive performance from those models is by using them to transfer knowledge to smaller lightweight models that are used at runtime. And then in addition to the foundation model work, we are working on advancing our inference models by developing new techniques and architectures that then allow us to scale up compute and complexity in an ROI positive way. So in general, you know, we obviously have a very large base of, you know, advertisers. There's a lot of demand liquidity in the system and even, you know, small scale improvements that we are able to make in terms of driving, you know, basis point improvements in the performance of ads or single digit, you know, increases in conversions relative to impressions in a given quarter, you know, off of a large base mean that we're really able to continue to grow the absolute dollars of revenue growth in a pretty meaningful way.

Justin Post (Bank of America): Actually, hey, Justin, just give us one second. I think there was a second question that we just want to get to on MSL.

Management: Yeah, I mean, I'll keep it quick. I mean, I don't think we have any specific timing to announce, certainly, on the models or products, but I expect that you will see both. We expect to build novel models and novel products, and I'm excited to share more when we have it.

Kristen (Analyst): Great, thanks. So, Mark, you mentioned the prior two content cycles, and obviously you've been able to generate very attractive margins on them. As we get into the AI cycle, obviously some concerns on the investment, but can you talk a little bit about how you're thinking about tools that could be coming out for users? I know there's some new competition. And then secondly, how do you think about margins in this content cycle? Any reason to think they would be different versus prior cycles? Thank you.

Mark (Executive): I think it's too early to really understand what the margins are going to be for the new products that we build. I mean, I think certainly every, each product has somewhat different characteristics and I think we'll kind of understand how that goes over time. Yeah. I mean, my general goal is to build a business that maximizes value for the people who use our products and maximizes profitability, not margin. So I think we'll kind of just try to build the best things that we can and try to deliver the most value that we can for most people.

Ross Sandler (Barclays): Great. Mark, some of the goals for competing AI labs are around achieving AGI or these other milestones that are out there and a little esoteric. How are you setting up your new team in terms of achieving those types of goals versus products that can generate revenue from meta kind of right out of the gate? And is the goal that you had articulated to us previously around giving billions of people kind of a personal AI to use still the direction of travel that you see or is there, you know, other things like kind of this vibes or Sora angle that, that, you know, you think are potentially important? How should we think about like the overall direction? Thank you.

Mark (Executive): Sure. So the way that I think about this is that the research is going to enable new technological capabilities to exist. And then those capabilities can get built into all kinds of different products. So the ability to reason more intelligently is, for example, very important across a large number of things. It would be useful for an assistant. It will also be useful in business AI. It will also be useful in the AI agent that we're building to help advertisers figure out what their campaigns are going to be. It will also have implications for eventually how we do ranking and recommendations of people's feeds and make different decisions there. That's just one example. I mean, certainly the capability to be able to produce very high quality good video is going to be useful for giving people new creative tools. It will help increase the amount of content inventory that can be shown in Instagram and Facebook and therefore should enable an increase in engagement there. It should help advertisers be able to create creative that will help us monetize better. So you can just go kind of down the list of capabilities that you'd expect.

And I think each one will enable a bunch of different things. And I think the art of product development here is looking at the list of technology capabilities and figuring out what new products are going to be useful and prioritizing those. But fundamentally, I would sort of expect this exponential curve in new technology capabilities that are going to become available. And the other thing that I expect is that I think being the best in a given area will drive great returns rather than, this is not like a check the box exercise of like, okay, we can generate some kind of content and someone else can. I think that like the company that is the best at each of these capabilities, I think will get a large amount of the potential value for doing that. So there are lots of different capabilities to build. I'm not sure that any one company is going to be the best at all of them. I doubt that's going to be the case. But a lot of what we're trying to do is not kind of do some things that others have done. We're really trying to build novel capabilities.

And I'm keeping this high level because I'm not I don't want to necessarily from a competitive or strategic perspective get into what we're prioritizing. But that hopefully gives you a sense of how we're thinking about what we're doing. We want to be able to kind of build novel things, build them into a lot of our products, and then have the compute to scale them to billions of people. And we think that that's going to both show up in terms of new products being possible and new businesses and very significant improvements to the current business too.

Mark Mahoney (Evercore ISI): Thanks. Can I just ask just a question on Meta AI and both the product and the monetization path? So when you look at it, what you've seen that's most encouraging to you in terms of the adoption and the use of Meta AI and then know when you think about, I know you generally like to roll out and then deepen engagement and then later think about monetization, like where do you think you are on that path now? Is it clear to you what the monetization options are for Meta AI? Thank you very much.

Mark (Executive): I mean, I think the most promising thing that we're seeing is one that we were able to build something that a large number of people use and I think that's valuable and then secondly that as we there is a clear correlation as we improve the models in ways that we think make them better that people use them more so that shows that we have a runway to basically be able to improve engagement and turn this into a product that's leading over time. In terms of where we are on this, and we basically just did this huge effort to boot up meta superintelligence labs and build what I am very proud of is, I think, the highest talent density lab in the industry at this point. There are a lot of really great researchers and infrastructure folks and data folks who are now a part of this effort, who are focused on training the next generation of work and doing some really novel work. And when that is ready, I think that we will be able to plug that into a number of the products that we're building. And I think that that will be very exciting. But I think that that's really the next thing that we're looking at.

And then from there, I think that these models will also improve modernization in all the different ways that we've talked about so far in terms of improving engagement, improving advertising, helping advertisers engage. There's one opportunity that we usually talk about on these calls but hasn't come up as much here is just the ability to make it so that advertisers are increasingly just going to be able to give us a business objective and give us a credit card or bank account and have the AI system basically figure out everything else that's necessary, including generating video or different types of creative that might resonate with different people that are personalized in different ways, finding who the right customers are. All of the capabilities that we're building, I think, go towards improving all of these different things. So I'm quite optimistic about that.

Ronald Josie (Citi): All right. Thanks for taking the question. And this maybe dovetails perfectly off, Mark, what you just talked about. And, you know, we heard a lot about end-to-end automation here, I think reaching a $60 billion ARR. I wanted to hear about, if you can talk to us more just about adoption rates amongst the advertisers and then maybe bigger picture, as you incorporate ranking recommendation changes like Andromeda, DEMS, or Lattice, just talk to us how this automation is driving, call it a higher ROI for advertisers overall as we bring it all together. Thank you.

Management: Yeah, so we've been sort of laying the continued brick-by-brick build of Advantage Plus and extending the set of objectives that it applies to over time. And so in Q3, we completed the global rollout of the streamlined campaign creation flow for Advantage Plus lead campaigns. So now advertisers who are running sales app or lead campaigns have end-to-end automation turned on from the beginning. And like, you know, the kind of application of the streamlined campaign creation flow for other objectives, this generally allows advertisers to optimize and automate several aspects of the campaign setup process at once. That includes things like audience selection, where to show the ad, how the budget gets paced and distributed across ad sets to drive the most efficient outcomes. Advertisers who run lead campaigns using Advantage Plus are seeing a 14% lower cost per lead on average than those who are not. And I would say that we think that there is still a lot of opportunity generally to grow adoption of Advantage Plus. A lot of advertisers only use our end-to-end automated solutions for a portion of their campaigns, so we can grow share there.

And to capture that opportunity, we're focused on driving continued performance improvements and addressing some of the key use cases that we still need in order to grow adoption. We're also working to broaden adoption among advertisers who use one of our single-step automated solutions. For example, advertisers who might only use a piece of it, like Advantage Plus Audiences, by helping them understand the benefits of using more than one automated solution at the same time. So I would say Advantage Plus is sort of an ongoing platform by which we both continue to expand the feature set that is available in Advantage Plus and then expand the extensibility or the coverage of that feature set to sort of the broader set of advertisers. Mark mentioned that the annual revenue run right now for advertisers who are using these automated options is, you know, $60 billion. And again, we see that there's room to continue growing that.

Yusuf Squali (Truist Securities): Great. Thank you very much. Mark, on wearables in particular, do you think you'll be able to sell enough hardware to recoup your investment, or is that dependent on maybe creating new avenues for revenue from things like advertising services and commerce through that new computing platform? And if so, what are kind of the gating factors there? And then Susan, how do you see the on-balance sheet versus off-balance sheet financing of your AI initiatives? You've recently struck a deal with Blue Owl for the Louisiana Data Center. Is that part of the CapEx guide for 26? And if it's not, how significant will that way of funding be for meta going forward? And basically, would that slow down your CapEx growth past 2026? Thank you.

Mark (Executive): I can talk about wearables, and then Susan can jump in on the other part. So I know there are a few pieces here. One is that the work that on Ray-Ban meta and the Oakley meta products is going very well. I think, yeah, I mean, at some point, if these continue going as well as it has been, then, I think it will be a very profitable investment. I think that there's some revenue that we get from basically selling the devices and then some that will come from additional services and from the AI on top of it. So I think that there's a big opportunity. Certainly the investment here is not just to kind of build just the device. It's also to build these services on top. Right now, a lot of people get the devices for a range of things that don't even include the AI, even though they like the AI. But I think over time, the AI is going to become the main thing that people are using them for. And I think that that's going to end up having a big business opportunity by itself.

But as products like the Ray-Ban Meta and Oakley Metas are growing, we're also going to keep on investing in things like the more full field of view product form of the Orion prototype that we showed at Connect last year. So those things are obviously earlier in their curve towards getting to being a sustaining business. And our general view is that we want to build these out to reach many hundreds of millions or billions of people. And that's the point at which we think that this is going to be just an extremely profitable business.

Susan (Executive): Yusef, to your second question, so the JV that we announced with Blue Owl is sort of an example of finding a solution that enabled us to partner with external capital providers to co-develop data centers in a way that gives us long-term optionality in supporting our future capacity needs, just given both the magnitude but also uncertainty of what the capacity outlook in future years looks like. In terms of how that is recognized as CapEx, our prior CapEx reflected a portion of the data center build cost prior to the joint venture being established. Going forward, the construction costs of the data center will not be recorded in CapEx as the data center is constructed. We will contribute 20% of the remaining construction costs required, which is in line with our ownership stake, and those will be recorded as other investing cash flows.

Ken Gawrowski (Wells Fargo): Thank you. Just one for me, please. Mark, as you think about with hopefully a leading frontier model next year in hand, could you talk about where you think the value will accrue in this evolving ecosystem? Will it be with the platforms, or do you think that this will be mostly the value will accrue to the scaled first-party applications? Thank you.

Mark (Executive): I guess I'm not exactly sure what you mean by platform versus application in this context. I mean, I think that there's just a lot of value to create with AI overall. So, I mean, clearly you're seeing the people who are making the hardware. NVIDIA is doing an amazing job, right? I think extremely well-deserved success. The cloud partners and companies are doing very well. I think that that will likely continue. I think there's a huge opportunity there. But if you look at it today, the companies that are building apps, I mean, a lot of the apps are still relatively small. And I know that's obviously going to be a huge opportunity. And I think what we've seen overall is basically people take like individual technology advances and build them into products that then build either communities or other kinds of network effects and then end up being very sustaining businesses. And I think what we haven't really seen as much in the history of the technology industry is the rate of new capabilities being introduced because around each of these capabilities, you can build many new products that I think each will turn into interesting businesses. So yeah, I don't know.

I mean, I'm generally pretty optimistic about there being a very large opportunity. But in terms of new things to build, I think being able to build them and then scale them to billions of people is a huge muscle that Meta has developed. And I think we do very well. And I certainly think that that's going to deliver a huge amount of value, both in the core business and all the ways that we talked about how it's going to improve recommendations and the quality of the services as well as unifying the models together and so that way when these systems are deciding what to show they can just pull from a wider pool and that we've these are things that we've just seen over the you know 20 plus years of running the company that they just deliver consistent wins we're going to keep on being able to make the systems more general and smarter and make better recommendations for people and have a larger pool of inventory. ==That is all going to be great.

And then there's going to be a lot of new things that I think we're going to be able to take and scale to billions of people over time and build new businesses, whether that's advertising or commerce supported or people paying for it or different kinds of things.== So yeah, I think it's pretty early, but I think we're seeing the returns in the core business. That's giving us a lot of confidence that we should be investing a lot more. And we want to make sure that we're not under-investing.

Management: Great. Thank you everyone for joining us today. We look forward to speaking with you again soon. This concludes today's conference call. Thank you for your participation.