Meta Platforms (META) Q3 2025 Earnings Call Transcript

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DATE

Wednesday, Oct. 29, 2025, at 4:30 p.m. ET

CALL PARTICIPANTS

• Chief Executive Officer — Mark Zuckerberg
• Chief Financial Officer — Susan Li

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RISKS

• Susan Li stated, "we cannot rule out the commission imposing further changes to that offering that could have a significant negative impact on our European revenue as early as this quarter."
• Susan Li noted, "In The US, a number of youth-related trials are scheduled for 2026. And may ultimately result in a material loss."
• The tax rate reached 87% in Q3 2025 due to a one-time noncash reduction in deferred tax assets, with Susan Li cautioning this "was unfavorably impacted" and explaining the elevated rate was not recurring.

TAKEAWAYS

• Daily Active Users -- 3.5 billion people used at least one company-owned app per day, according to Mark Zuckerberg in Q3 2025, reflecting continued community expansion.
• Instagram Monthly Actives -- Instagram had 3 billion monthly active users; Threads daily active users surpassed 150 million, reflecting strong engagement in Q3 2025, signaling good momentum across our other apps.
• Family of Apps Revenue -- $50.8 billion, up 26% year-over-year, as reported by Susan Li.
• Advertising Revenue (Family of Apps) -- $50.1 billion, up 26% year-over-year, or 25% on a constant currency basis; average price per ad rose 10% year-over-year, driven by increased advertiser demand largely driven by improved ad performance.
• Ad Impressions -- Up 14% year-over-year; "Impression growth was healthy across all regions driven by engagement and user growth particularly on video surfaces."
• Family of Apps Other Revenue -- $690 million, a 59% increase, underpinned by WhatsApp paid messaging and Meta Verified subscriptions.
• Reality Labs Revenue -- $470 million, up 74% year-over-year, due to retail partners stocking up on Quest headsets ahead of the holiday season, and strong AI glasses revenue.
• Consolidated Total Revenue -- $51.2 billion, up 26% or 25% on a constant currency basis.
• Total Expenses -- $30.7 billion, up 32% compared to the prior year; Growth was driven by higher legal costs, technical hires -- especially in AI -- and increased infrastructure operating costs.
• Employee Count -- Over 78,400, up 8% year-over-year, driven by hiring in priority areas of monetization, infrastructure, Reality Labs, Meta Superintelligence Labs, as well as regulation and compliance.
• Operating Income -- $20.5 billion, yielding a 40% operating margin.
• Interest and Other Income -- $1.1 billion, primarily from unrealized gains on our marketable equity securities.
• Tax Rate -- 87% due to a one-time noncash reduction in deferred tax assets that we no longer anticipate using under new US tax law; excluding this charge, the tax rate would have been 14% and net income would have been $18.6 billion, or $7.25 per share.
• Net Income -- $2.7 billion, or $1.05 per share as reported, including the tax adjustment.
• Capital Expenditures -- $19.4 billion, reflecting server, data center, and network infrastructure investments.
• Free Cash Flow -- Free cash flow was $10.6 billion.
• Shareholder Returns -- $3.2 billion repurchased in Class A stock and $1.3 billion paid in dividends.
• Cash and Marketable Securities -- $44.4 billion on hand; $28.8 billion in debt.
• Q4 2025 Revenue Guidance -- Anticipated total revenue in the range of $56 billion to $59 billion for Q4 2025, with about a 1% FX tailwind; The forecast includes continued strong ad revenue growth partially offset by lower year-over-year Reality Labs revenue.
• Full-Year 2025 Expense Outlook -- Updated to $116 billion to $118 billion (22%-24% growth), up from $114 billion to $118 billion.
• 2025 CapEx Outlook -- Raised to $70 billion to $72 billion from $66 billion to $72 billion.
• 2026 Spend Outlook -- "CapEx dollar growth will be notably larger in 2026 than 2025," and "total expenses will grow at a significantly faster percentage rate in 2026 than 2025," according to Susan Li, referring to Meta's consolidated expenses, mainly due to "infrastructure costs including incremental cloud expenses and depreciation," with employee compensation as the second-largest contributor.
• AI and Ads Automation Metrics -- The annual run rate for AI-powered ad tools has surpassed $60 billion; Reels' annual run rate is over $50 billion; Advertisers using Advantage Plus for lead campaigns saw a 14% lower cost per lead on average.
• Product Engagement -- Time spent on Facebook increased 5% and on Threads by 10%; video time spent on Instagram was up more than 30% year-over-year, according to Mark Zuckerberg.

SUMMARY

Meta Platforms (META +0.03%) a reported robust double-digit top-line growth in Q3 2025, with notable gains in global user engagement and video monetization year-over-year. Management upgraded forward capital expenditure and expense guidance, citing escalating infrastructure and AI compute requirements as central drivers for 2025 and 2026. Aggressive hiring in technical and AI roles continued, while automation in ads and messaging segments showed expanding adoption and improved advertising efficiency.

but explicitly guided for lower Reality Labs revenue, reflecting product cycle timing and holiday demand shifts.

• Reality Labs' growth benefited from retail pre-purchases and AI glasses, with headwinds in Q4 directly linked to product release cycles instead of ongoing demand.
• The transition to new US tax regulations resulted in a substantially elevated tax rate, but management expects a 12%-15% tax rate in Q4 and ongoing cash tax savings.
• Expansion of Meta's AI-driven Advantage Plus and Lattice model architectures continued to deliver lower costs per lead, improved conversions year-over-year, and further consolidation of ads ranking models, supporting incremental advertising revenue gains.
• Management emphasized the likelihood of further upward pressure on expenses as they front-load data center and compute investments "to be prepared for the most optimistic cases," according to Mark Zuckerberg in the AI cycle.
• EU regulatory action and upcoming US youth-related legal proceedings were directly highlighted by management as potential sources of significant financial risk.
• Mark Zuckerberg underscored the runway for AI improvements, noting persistent demand to "absorb a very large amount" of compute for both core business and new AI products, and that continued scaling is central to sustaining future growth.
• Management confirmed that on-balance sheet and off-balance sheet financing, such as the Blue Owl joint venture, have been designed to provide flexible, long-term infrastructure capacity and will impact capital expenditure recognition going forward.

INDUSTRY GLOSSARY

• Lattice: Meta’s unified ads model architecture that consolidates smaller, specialized models into larger, generalizable models for improved ad ranking and marketing performance.
• Advantage Plus: Meta’s automated campaign solution that optimizes ad audience, placement, and budget allocation across objectives, providing end-to-end automation for sales, app, or lead campaigns.
• Meta Superintelligence Labs (MSL): Meta’s advanced AI research group focused on developing next-generation artificial intelligence models and infrastructure.
• Reality Labs: Meta’s segment dedicated to augmented reality, virtual reality, and wearable hardware and software products.

Full Conference Call Transcript

Mark Zuckerberg: We had another strong quarter with 3.5 billion people using at least one of our apps every day. Instagram hit a major milestone with 3 billion monthly actives. And we're seeing good momentum across our other apps as well, including Threads, which recently passed 150 million daily actives and remains on track to become the leader in its category. I am very focused on establishing Meta as the leading frontier AI lab. Building personal superintelligence for everyone, delivering the app experiences and computing devices that will improve the lives of billions of people around the world. Our approach of advancing open-source AI means that when Meta innovates, everyone benefits. Meta Superintelligence Labs is off to a strong start.

I think that we've already built the lab with the highest talent density in the industry. We're heads down developing our next generation of models and products. And I'm looking forward to sharing more on that front over the coming months. We're also building what we expect to be an industry-leading amount of compute. Now there's a range of timelines for when people think that we're gonna get superintelligence. Some people think that we'll get there in a few years. Others think it will be five, seven years, or longer. I think that it's the right strategy to aggressively front-load building capacity so that way we're prepared for the most optimistic cases.

That way, if superintelligence arrives sooner, we will be ideally positioned for a generational paradigm shift in many large opportunities. If it takes longer, then we'll use the extra compute to accelerate our core business, which continues to be able to profitably use much more compute than we've been able to throw at it. And we're seeing very high demand for additional compute both internally and externally. And in the worst case, we would just slow building new infrastructure for some period while we grow into what we build. The upside is extremely high for both our existing apps and new products and businesses that are becoming possible to build.

Across Facebook, Instagram, and Threads, our AI recommendation systems are delivering higher quality and more relevant content, which led to 5% more time spent on Facebook in Q3 and 10% on Threads. Video is a particular bright spot. With video time spent on Instagram up more than 30% since last year. And as video continues to grow across our apps, Reels now has an annual run rate of over $50 billion. Improvements in our recommendation systems will also become even more leveraged as the volume of AI-created content grows. Social media has gone through two eras so far. First was when all content was from friends, family, and accounts that you followed directly.

The second was when we added all of the creator content. Now as AI makes it easier to create and remix content, we're going to add yet another huge corpus of content on top of those. Recommendation systems that understand all this content more deeply and show you the right content to help you achieve your goals are going to be increasingly valuable. Our ads business continues to perform very well largely due to improvements in our AI ranking systems as well. This quarter, we saw meaningful advances from unifying different models into simpler, more general models, which drive both better performance and efficiency.

And now the annual run rate going through our completely end-to-end AI-powered ad tools has passed $60 billion. And one way that I think about our company overall is that there are three giant transformers that run Facebook, and ads recommendations. We have a very strong pipeline of lots of ways to improve these models by incorporating new AI advances and capabilities. And at the same time, we are also working on combining these three major AI systems into a single unified AI system that will effectively run our family of apps and business, using increasing intelligence to improve the trillions of recommendations that we'll make for people every day.

I'm also very excited about the new products that we're going to be able to build. More than a billion monthly actives already use Meta AI, and we see usage increase as we improve our underlying models. I'm very excited to get a frontier model into Meta AI. I think that the opportunity there is very large. The same goes for our business AI. Every day, people have more than 1 billion active threads with business accounts across our messaging platforms ranging from product questions to customer support. Our business AIs will enable tens of millions of businesses to scale these conversations and improve their sales at low cost.

And the better our models get, the better this is gonna work for all businesses. This quarter, we also launched Vibes, which is the next generation of our AI creation tools and content experiences. Retention is looking good so far. And its usage keeps growing quickly week over week. I'm looking forward to ramping up the growth of Vibes over the coming months. More broadly, I think that Vibes is an example of a new content type enabled by AI and I think that there are more opportunities to build many more novel types of content ahead as well.

As our new models become ready, I'm looking forward to starting to show everyone some of the new kinds of products that we're working on. At Connect, we announced our 2025 line of AI glasses. The response so far has been great. The new Ray-Ban Meta glasses and Oakley Meta Vanguards are both selling well. The people love the improved battery life, camera resolution, new AI capabilities, and the great design. And there's our new Meta Ray-Ban display glasses, our first glasses with a high-resolution display and the Meta Neural Band to interact with them. They sold out in almost every store within 48 hours, with demo slots fully booked through the end of next month.

So we're gonna have to invest in increasing manufacturing and selling more of those. This is an area where we are clearly leading and have a huge opportunity ahead. Taking a step back, if we deliver even a fraction of the opportunity ahead for our existing apps, and the new experiences that are possible. Then I think that the next few years will be the most exciting period in our history. We've got a lot to do, but we're making real progress delivering strong business results building the talent density and infrastructure needed for the next era, and leading the way on AI devices that will define the next computing platform.

I'm proud of how our teams are rising to the challenge, and I'm grateful for their dedication, hard work, and creativity. As always, thank you all for being a part of this journey with us. And now here's Susan. Thanks, Mark, and good afternoon, everyone.

Susan Li: Let's begin with our segment results. All comparisons are on a year-over-year basis unless otherwise noted. Our community across the family of apps continues to grow, and we estimate more than 3.5 billion people use at least one of our family of apps on a daily basis in September. Q3 total family of apps revenue was $50.8 billion, up 26% year over year. Q3 family of apps ad revenue was $50.1 billion, up 26% or 25% on a constant currency basis. Q3, the total number of ad impressions served across our services increased 14%. Impression growth was healthy across all regions driven by engagement and user growth particularly on video surfaces.

The average price per ad increased 10% year over year, benefiting from increased advertiser demand largely driven by improved ad performance. This was partially offset by impression growth, particularly from lower monetizing regions and surfaces. Family of apps other revenue was $690 million, up 59%. Driven by WhatsApp paid messaging revenue growth, as well as Meta verified subscriptions. Within our Reality Labs segment, Q3 revenue was $470 million, up 74% year over year. The significant year-over-year growth in Q3 was partly due to retail partners stocking up on Quest headsets ahead of the holiday season. We did not have a similar benefit in the third quarter of last year since our Quest 3s headset launched in 2024.

Aside from this, strong AI glasses revenue also contributed to revenue growth Q3. Moving now to our consolidated results. Q3 total revenue was $51.2 billion, up 26% or 25% on a constant currency basis. Q3 total expenses were $30.7 billion, up 32% compared to last year. Year-over-year expense growth accelerated 20 percentage points from Q2. Due primarily to three factors. First, legal-related expense growth was higher than in Q2. Due to charges we recorded in the third quarter as well as us lapping a period of accrual reversals in the third quarter a year ago. Second, employee compensation growth accelerated, driven by technical hires, particularly AI talent.

Finally, growth in infrastructure costs accelerated due to increased infrastructure operating costs associated with our expanded data center fleet. Depreciation on our incremental CapEx spend, and third-party cloud spend. We ended Q3 with over 78,400 employees, up 8% year over year. Driven by hiring in priority areas of monetization, infrastructure, Reality Labs, Meta Superintelligence Labs, as well as regulation and compliance. Third quarter operating income was $20.5 billion, representing a 40% operating margin. Q3 interest and other income was $1.1 billion driven primarily by unrealized gains on our marketable equity securities.

Our tax rate for the quarter was 87% which was unfavorably impacted by a one-time noncash reduction in deferred tax assets that we no longer anticipate using under new US tax law. Our tax rate would have been 14% excluding this charge. Although the transition to the new US tax law resulted in an accounting charge in the third quarter, we continue to expect we will recognize significant cash tax savings for the remainder of the current year and future years, under the new law, and this quarter's charge reflects the total expected impact from the transition to the new US tax law. Net income was $2.7 billion or $1.05 per share.

Excluding the one-time tax charge, our net income and EPS would have been $18.6 billion and $7.25 share respectively. Capital expenditures including principal payments on finance leases were $19.4 billion, driven by investments in servers data centers, and network infrastructure. Free cash flow was $10.6 billion. We repurchased $3.2 billion of our Class A common stock and paid $1.3 billion in dividends to shareholders. We ended the quarter with $44.4 billion in cash and marketable securities and $28.8 billion in debt. Turning now to the business outlook. There are two primary factors that drive our revenue performance. Our ability to deliver engaging experiences for our community and our effectiveness at monetizing that engagement over time.

On the first, daily actives continue to grow year over year across Facebook, Instagram, and WhatsApp. We're continuing to see improvements to our products and recommendations, drive incremental engagement with year-over-year growth in global time spent accelerating On both Facebook and Instagram in Q3. In The US, overall time spent on Facebook and Instagram grew double digits year over driven by continued video strength as well as healthy growth in non-video time on Facebook. The engagement gains continue to be driven by product work and ongoing improvements to our recommendation systems, as we optimize our model architectures, implement advanced modeling techniques, and integrate more signals about people's interests. Also continue to focus on increasing the freshness of recommended content.

On Facebook, our systems are now surfacing twice as many reels published that day. At the start of the year. Looking to 2026, we expect to advance our recommendation systems across several dimensions. On Instagram, one focus is evolving our systems to surface content across a broader set of topics that cater to the diverse interests of each person. This follows a similar approach we've implemented on Facebook that has driven good results. We also expect to make significant progress on our longer-term ranking innovations in 2026.

We're seeing promising new results from our research efforts to create foundational ranking models and expect the new model innovations we're developing as part of this will enable us to significantly scale up the amount of data and compute we use to train our recommendation models in 2026. Yielding more relevant recommendations. Another large focus next year is leveraging LLMs to improve content understanding. We expect this is going to enable our systems to more precisely label the keywords and topics within videos and posts, which will allow our systems to both develop deeper intuition about a person's interests and retrieve the content. That matches them. Finally, we're making good progress with Meta AI and Threads.

The number of people using Meta AI across our family of apps continues to grow. And we're increasingly leveraging first-party content into Meta AI results with the majority of Meta AI's responses to Facebook deep dive queries in The US now showing related reels. We're also seeing a lot of traction with media generation. People have created over 20 billion images using our products, And since launching Vibes within Meta AI in September, we've seen media generation in the app increase more than tenfold. On Threads, we see strong growth in both daily actives and the depth of engagement as we continue to improve recommendations.

The ranking optimizations we made in Q3 alone drove a 10% increase in time spent on Threads. We also continue to ship new features, including launching direct message in Q3, so anyone on Threads can now message one another within the app. Now to the second driver of our revenue performance. Increasing monetization efficiency. The first part of this work is optimizing the level of ads within organic engagement. We continue to refine ad supply across each of our major within Facebook and Instagram to better deliver ads at the time and place they are most relevant to people. Longer term, we have exciting ads supply opportunities on both Threads and WhatsApp status.

Ads are now running globally in feed on Threads, and we're following our typical monetization playbook, of optimizing the ads formats and performance before we ramp supply. Within WhatsApp status, we're continuing to gradually introduce ads. And expect to complete the rollout next year. The second part of increasing monetization efficiency is improving marketing performance. Advancing our ad systems remains a critical aspect of this work. And we are driving performance gains through ongoing improvements in our larger scale ads ranking models. For example, we continue to broaden the adoption of Lattice, our unified model architecture. In Q3, we rolled out Lattice to app ads which drove a nearly 3% gain in conversions for that objective.

Since introducing Lattice back in 2023, along with other back-end improvements, we have now cut the number of ads ranking in recommendation models by approximately 100. As we consolidated smaller and more specialized models into larger ones that use the lattice architecture, generalize learnings across surfaces and objectives. We continue to observe performance improvements as we combine models and expect to drive additional gains as we consolidate another 200 models over the coming years, into a smaller number of highly capable models. In addition to advancing our foundational ads models, we're innovating on our runtime models we use downstream of them for ads inference.

For example, we began piloting a new runtime ads ranking model in Q3 that leverages more compute and data than our prior models to select more relevant ads. In testing, we've seen this new model drive a more than 2% lift in conversions on Instagram. We also significantly improved performance of Andromeda in Q3, by combining models across retrieval and early stage ranking into a single model. Driving a 14% increase in ads quality on Facebook surfaces. Within our ads products, we're seeing continued momentum, which Advantage Plus. In Q3, we completed the rollout of our streamlined campaign creation flow for advantage plus lead campaigns.

So now advertisers running sales, app, or lead campaigns have end-to-end automation turned on from the beginning. Allowing our systems to look across our platform to optimize performance by automatically choosing criteria, like who to show the ads to, and where to show them. The annual run rate of revenue running through our end-to-end automated solutions has now reached $60 billion following the implementation of the new streamlined creation flow. As we continue to see more advertisers leverage the performance benefits of our solutions.

Within our advantage plus creative suite, the number of advertisers using at least one of our video generation features was up 20% versus the prior quarter as adoption of image animation and video expansion continues to scale. We've also added more generative AI features to make it easier for advertisers to optimize their ad creatives and drive increased performance. In Q3, we introduced AI-generated music. So advertisers can have music generated for their ad that aligns with the tone and message of the creative. Finally, business messaging remains a significant opportunity for us. We're seeing strong growth across our portfolio of solutions. Including with click to WhatsApp ads. Which grew revenue 60% year over year in Q3.

We're also making good progress on our business AI efforts. We've been focused on building a turnkey AI that helps businesses generate leads and drive sales. We've been opening access in recent months to more businesses within our initial test markets, The Philippines and Mexico, and have seen strong usage with millions of conversations between people and business AIs taking place since July. This month, we expanded availability within WhatsApp and to all eligible businesses in Mexico and The Philippines, respectively. In The US, we're also starting to roll out the ability for merchants to add their business AIs to their website so we can support the full sale funnel from ad to purchase.

Next, I would like to discuss our approach to capital allocation. Our primary focus is deploying capital to support the company's highest order priorities, including developing leading AI products models and business solutions. As we make significant investments in infrastructure to support this work, we are focused on preserving maximum long-term flexibility to ensure we can meet our future capacity needs while also being able to respond to how the market develops in the years ahead. We're doing so in several ways, including staging data center so we can spring up capacity quickly in future years as we need it, as well as establishing strategic partnerships that give us option value for future compute needs.

The strong financial position cash generation of our business enable us to make these investments while also accessing additional pools of cost-efficient capital. Moving to our financial outlook. We expect fourth quarter 2025 total revenue to be in the range of $56 billion to $59 billion. Our guidance assumes foreign currency is an approximately 1% tailwind to year-over-year total revenue growth. Based on current exchange rates. Our outlook reflects an expectation for continued strong ad revenue growth Partially offset by lower year-over-year Reality Labs revenue in Q4.

The anticipated reduction in Reality Labs revenue is due to us lapping the introduction of QUEST 3s in Q4 of last year, as well as retail partners procuring Quest headsets during Q3 of this year to prepare for the holiday season. Which were recorded as revenue in the third quarter. Turning to the expense and CapEx outlooks. I'll first start with 2025 before providing some commentary on our planning for 2026. We expect full year 2025 total expenses to be in the range of $116 billion to $118 billion updated from our prior outlook of $114 a $118 billion and reflecting a growth rate of 22% to 24% year over year.

We currently expect 2025 capital expenditures including principal payments on finance leases, to be in the range of $70 to $72 billion increased from our prior outlook of $66 to $72 billion. Onto tax. Absent any changes to our tax landscape, we expect our fourth quarter 2025 tax rate to be 12% to 15%. Turning now to 2026. We are at an exciting point for our company where we have continued runway to improve our core services today as well as the opportunity to build new AI-powered experiences and services that will transform how people engage with our products in the future.

We expect the set of investments we're making within our ads and organic engagement initiatives next year will enable us to continue to deliver strong revenue growth in 2026. While our progress on AI models and products will position us to capitalize on new revenue opportunities in the years to come. A central requirement to realizing these opportunities is infrastructure capacity. As we have begun to plan for next year, become clear that our compute needs have continued to expand meaningfully. Including versus our own expectations last quarter. We are still working through our capacity plans for next year.

But we expect to invest aggressively to meet these needs both by building our own infrastructure and contracting with third-party cloud providers. We anticipate this will provide further upward pressure on our CapEx and expense plans next year. As a result, our current expectation is that CapEx dollar growth will be notably larger in 2026 than 2025. We also anticipate total expenses will grow at a significantly faster percentage rate in 2026 than 2025, with growth primarily driven by infrastructure costs including incremental cloud expenses and depreciation. Employee compensation costs will be the second largest contributor to growth. As we recognize a full year of compensation for employees hired throughout 2025, particularly AI talent.

And add technical talent in priority areas. Finally, we continue to monitor legal and regulatory matters. Including the increasing headwinds in The EU and The US that could significantly impact our business and financial results. For example, the EU, we continue to engage constructively with the European Commission on our less personalized ads offering. However, we cannot rule out the commission imposing further changes to that offering that could have a significant negative impact on our European revenue as early as this quarter. In The US, a number of youth-related trials are scheduled for 2026. And may ultimately result in a material loss. In closing, this was another good quarter for our business.

We have an exciting set of opportunities to continue improving our core business delivering innovative new experiences and services for the people and businesses using our products in the years to come. With that, Christa, let's open up the call for questions.

Krista: Thank you. We will now open the lines for question and answer session. If you are streaming today's call, please mute your computer speakers. And your first question comes from the line of Brian Nowak with Morgan Stanley. Please go ahead.

Brian Nowak: Thanks for taking my questions. I have a 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. So, 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 gonna get ROIC from all this CapEx? That's the first one. Second one is a little faster. How large is the Reality Labs revenue headwind in the 4Q guidance? Thanks.

Susan Li: Thanks, Brian, for the question. I think your first question had a couple parts to it. So I'm gonna 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, CoreAI, as well as non-AI spend. So all of those areas are growing, but these MSL AI needs are growing the most. In terms of the core AI pipeline, you know, I think we talked about, last year, we were going into the 2025 budget process, we had a road map of resource investments across both headcount and compute.

That we thought would pay off, you know, 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, you know, 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, you know, how are we driving ad performance, How are conversions growing? Conversions is a complex metric for us because advertisers optimize for so many different conversions. With different values. But when we control for that and look at value-weighted conversion rates, we're seeing very strong year-over-year growth and conversions continue.

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's going to be a continued story in 2026. We are in fact at the beginning of our 2020 budgeting process now, and we, you know, see a similar list of revenue investments. That we you know, that we're excited to be able to invest in.

And so we think 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 in 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 2024 since the headset was launched in October 2024.

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.

Krista: Your next question comes from the line of Doug Anmuth with JPMorgan. Please go ahead.

Doug Anmuth: Great. Thanks for taking the question. I appreciate the strategy to front-load capacity for superintelligence. Can you just talk about your thought process and 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 even do you have targets that we should be thinking about for cash on hand or net cash overall? Thanks.

Susan Li: Thanks, Doug. We're right now, I would say, in the process of we're relatively early, actually, still in the process of putting together our budget for 2026. And it is on the on the side, a particularly, you know, 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. Certain not only with the MSL team, 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 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, you know, that's that's sort of the foremost priority as we're putting together the budget.

Mark Zuckerberg: Yeah. I mean, I'll add a few thoughts on this too, although 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 then we end up having compute for.

So I think that suggests that being able to make a significant larger investment here is very likely to be a profitable thing over some period. Because if 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.

And if we do, I mean, this is what I mentioned in comments, then you know, we see that there's just a lot of demand for other new things that we 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 prebuilt 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, the right thing to do is to try to accelerate this to make sure that we have the 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 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.

Krista: Your next question comes from the line of Eric Sheridan with Goldman Sachs. Please go ahead.

Eric Sheridan: Thanks so much for taking the question. Mark, 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 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 Zuckerberg: Yeah. I mean, a lot of people use Meta AI today. I mean, as I said in my comments upfront, 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 four 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, like, truly frontier models novel capabilities that you don't have in other places, then I think that this is just a massive latent opportunity. Right?

We know mean, I would guess that you know, 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 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 I'm quite excited about. And then there are the business versions of all these too, like business AI. And then know, that's, of course, one part of the story is the new things that will be possible to build. Then the other part, is how more intelligent models are just gonna improve the core business. And improve the recommendations that we make across the family of apps and improve the recommendations in advertising. And I think there's just a as we've shown, there's sort of this very large amount of headroom and the opportunity there keeps growing as we as we are improving and optimizing the AI there.

And I think that really shows no sign of being near the end. I think that there's quite a bit more to do there. And know, like I said, in response to the last question, we are sort of perennially operating 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, you know, 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.

Krista: Your question comes from the line of Mark Shmulik with Bernstein. Please go ahead.

Mark Shmulik: Yes. Hi. Thanks for taking the questions. Susan, as you 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, as you think about kind of the timing of some of these newer efforts coming out of Superintelligence Labs, is that anchoring to kind of an updated Frontier model on 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 Li: 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 JEM for inference, because their size and complexity would make it too cost prohibitive. The way that we drive performance from those models 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. An ROI positive way.

So, in general, you know, we obviously have a very large base of 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.

Krista: Your next question comes from the line of Justin Post with Bank of America. Please go ahead.

Justin Post: Actually, you.

Mark Zuckerberg: Hey, Justin. Just give us one second. I think there was a second question that we would just wanna get to on MSL. 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.

Krista: Krista, Justin, please go ahead.

Justin Post: Great. Thanks. So, Mark, you mentioned the prior two concepts. 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 you think about margins in this context cycle? Any reason to think they would be different versus prior cycles? Thank you.

Mark Zuckerberg: I think it's too early to really understand what the margin are gonna be for the 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. Mean, my general goal is to build a business that maximizes value for the people who use our products and maximizes profit not margin. So I think we'll kind of just try to build the best things that we can and to deliver the most value that we can for most people.

Krista: Your next question comes from the line of Ross Sandler with Barclays. Please go ahead.

Ross Sandler: Great. Hey, Mark. Some of the goals for competing AI labs are around achieving AGI or these other milestones that are kind of, like, 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 kinda 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 the still the direction of travel that you see, or is there you know, other things like kind of this vibe or Sora angle that, you know, you think are potentially important?

How should we think about, like, the overall direction? Thank you.

Mark Zuckerberg: 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 gonna 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.

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 gonna be useful and prioritizing those. But fundamentally, I would sort of expect this exponential curve in new technology capabilities are gonna become available. And the other thing that I expect is that I think being the best a given area will drive great returns rather than this is not like a check the box exercise of, like, okay. 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, think, will get a large amount of the potential value for doing that. So are lots of different capabilities to build. I'm not sure that any one company is gonna be the best at all of them. I doubt that's gonna be the case. But a lot of what we're trying to do is not like not kind of do some things that others have done. We're really trying to build novel capabilities, and I'm this high level because I'm not don't wanna 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 wanna 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's gonna both show up in terms of new products keep being possible, and new businesses. And very significant improvements to the current business too.

Krista: Your next question comes from the line of Mark Mahaney with Evercore ISI. Please go ahead.

Mark Mahaney: Thanks. Can I just ask just a question on Meta AI and both 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 when you think about I know you generally like to roll out and then, you know, 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? You very much.

Mark Zuckerberg: 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. 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 were a lot of really great researchers and infrastructure folks and data folks who are now a part of this effort, are 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 products that we're building, and I think that will be very exciting.

But I think that's really the next thing that we're looking at. And then from there, I think that these models will also improve monetization in all of the different ways that we've talked about so far in terms of improving engagement, improving advertising, helping advertisers engage.

I mean, there's the one opportunity that we just 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 gonna be able to give us a business objective and give us a credit card or bank account and like, have the AI system basically figure out everything else that's necessary, including generating video or different types of creative that might resonate with 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 quite optimistic about that.

Krista: Your next question comes from the line of Ronald Josey with Citi. Please go ahead.

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

Susan Li: Yeah. So we've been sort of laying the continued brick by brick build of Advantage Plus and extending the 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. And, you know, we see that Advantage Plus continues to drive performance gains. 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 this the same time. So I would say, Advantage Plus is sort of 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 the sort of the broader set of advertisers. You know, I think Mark, mentioned that the annual revenue run rate now for advertisers who are using these automated options is, you know, $60 billion. And, we see that there's room to continue growing that.

Krista: Your next question comes from the line of Youssef Squali with Truist Securities. Please go ahead.

Youssef Squali: 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 on of your AI initiatives? You've recently struck a deal with Blue Owl. The Louisiana data center. Is that part of the CapEx guide for '26? And if it's not, how significant will that weigh a funding be for Meta going forward?

And basically, would that slow down your CapEx growth past 2026? Thank you.

Mark Zuckerberg: Can talk about wearables, then and 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 product 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 a 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, 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's gonna end up having a big business opportunity by itself.

But, you know, as products like the Ray-Ban Meta and Oakley Metas are growing, We're also gonna 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 wanna build these out to reach many hundreds of millions or billions of people. And the point at which we think that this is gonna be just an extremely profitable business.

Susan Li: Youssef, to your second question, so the JV that we announced with BlueOwl 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. Supporting our future capacity needs just given both the magnitude, but also uncertainty of what the capacity outlook in 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 cost 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 line with our ownership stake, and those will be recorded as other investing cash flows.

Krista: Your last question comes from the line of Ken Gawrelski with Wells Fargo. Please go ahead.

Ken Gawrelski: Thank you. Just one for me, please. Mark, as you think about with the 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 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 Zuckerberg: I guess I'm not exactly sure what you mean by platform versus application in this context. But I mean, I think that I mean, I think 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, I mean, 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 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 think that's obviously gonna be a huge opportunity.

And I think what we've seen overall is basically people take individual technology advances, and build them into products that then build either communities or other kinds of network effect 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 yes, 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, 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's gonna deliver a huge amount of value.

Both in the core business for all the ways that we talked about, how it's gonna 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, twenty plus years of running the company that they just deliver consistent wins, and we're gonna 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. And that is all gonna be great.

There's gonna be a lot of new things that I think we're gonna 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, it's 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 wanna make sure that we're not under investing.

Kenneth Dorell: Great. Thank you everyone for joining us today. We look forward to speaking with you again soon.

Krista: This concludes today's conference call. Thank you for your participation and you may now disconnect.