2025-07-30 Meta Platforms, Inc. (META) Q2 2025 Earnings Call Transcript
Meta Platforms, Inc. (NASDAQ:META) Q2 2025 Earnings Conference Call July 30, 2025 5:00 PM ET
Company Participants
Kenneth J. Dorell - Director of Investor Relations
Mark Elliot Zuckerberg - Founder, Chairman & CEO
Susan J. S. Li - Chief Financial Officer
Conference Call Participants
Brian Thomas Nowak - Morgan Stanley, Research Division
Douglas Till Anmuth - JPMorgan Chase & Co, Research Division
Eric James Sheridan - Goldman Sachs Group, Inc., Research Division
Justin Post - BofA Securities, Research Division
Mark Elliott Shmulik - Sanford C. Bernstein & Co., LLC., Research Division
Ronald Victor Josey - Citigroup Inc., Research Division
Youssef Houssaini Squali - Truist Securities, Inc., Research Division
Operator
Good afternoon. My name is Krista, and I will be your conference operator today. At this time, I would like to welcome everyone to the Meta Second Quarter Earnings Conference Call. \[Operator Instructions] And this call will be recorded. Thank you very much.
下午好。我叫Krista，将担任今天电话会议的主持人。现在，我想欢迎大家参加Meta 2025年第二季度财报电话会议。\[操作说明] 本次会议将被录音。非常感谢。
Kenneth Dorell, Meta's Director of Investor Relations. You may begin.
Kenneth Dorell，Meta投资者关系总监。请开始。
Kenneth J. Dorell
Thank you. Good afternoon, and welcome to Meta's Second Quarter 2025 Earnings Conference Call. Joining me today are Mark Zuckerberg, CEO; and Susan Li, CFO.
谢谢。下午好，欢迎参加Meta 2025年第二季度财报电话会议。今天与我一同出席的有CEO Mark Zuckerberg和CFO Susan Li。
Our remarks today will include forward-looking statements, which are based on assumptions as of today. Actual results may differ materially as a result of various factors, including those set forth in today's earnings press release and in our quarterly report on Form 10-Q filed with the SEC. We undertake no obligation to update any forward-looking statement.
我们今天的发言将包含前瞻性声明，这些声明基于截至今日的假设。由于多种因素的影响，包括今天财报新闻稿和向SEC提交的10-Q季度报告中所列出的因素，实际结果可能与这些声明存在重大差异。我们没有义务更新任何前瞻性声明。
During this call, we will present both GAAP and certain non-GAAP financial measures. A reconciliation of GAAP to non-GAAP measures is included in today's earnings press release. The earnings press release and an accompanying investor presentation are available on our website at investor.atmeta.com.
在本次电话会议中，我们将同时介绍GAAP和部分非GAAP财务指标。GAAP与非GAAP指标的对账表已包含在今天的财报新闻稿中。财报新闻稿和投资者演示材料可在我们的网站 investor.atmeta.com 查阅。
And now I'd like to turn the call over to Mark.
现在，我想把电话交给Mark。
Mark Elliot Zuckerberg
All right. Thanks, Ken. Thanks, everyone, for joining today. We had another strong quarter with more than 3.4 billion people using at least one of our apps each day and strong engagement across the board. Our business continues to perform very well, which enables us to invest heavily in our AI efforts.
好的，谢谢Ken。感谢大家今天的参加。本季度我们再一次取得了强劲的成绩，每天有超过34亿人使用至少一款我们的应用，并且整体的用户参与度保持强劲。我们的业务持续表现良好，这使我们能够在AI方面进行大规模投资。
Over the last few months, we've begun to see glimpses of our AI systems improving themselves. And the improvement is slow for now, but undeniable and developing superintelligence, which we define as AI that surpasses human intelligence in every way, we think, is now in sight. Meta's vision is to bring personal superintelligence to everyone, so that people can direct it towards what they value in their own lives. And we believe that this has the potential to begin an exciting new era of individual empowerment.
在过去几个月里，我们已经开始看到AI系统自我改进的迹象。尽管目前改进的速度较慢，但这是不可否认的。我们认为，发展“超级智能”——即在各方面超越人类智能的AI——已近在眼前。Meta的愿景是让每个人都能拥有“个人超级智能”，从而能够将其用于他们自己生活中最看重的事物。我们相信，这将有潜力开启一个令人振奋的“个人赋能新时代”。
A lot has been written about all the economic and scientific advances that superintelligence can bring, and I'm extremely optimistic about this. But I think that if history is a guide, then an even more important role will be how superintelligence empowers people to be more creative, develop culture and communities, connect with each other and lead more fulfilling lives.
关于超级智能能带来的经济和科学进步，已有大量文章探讨过，我对此非常乐观。但我认为，如果以历史为参考，更重要的一点是，超级智能将如何赋能人们：让他们更具创造力，推动文化与社区的发展，促进彼此之间的联系，并过上更加充实的生活。
To build this future, we've established Meta Superintelligence Labs, which includes our foundations, product and FAIR teams as well as a new lab that is focused on developing the next generation of our models. We're making good progress towards Llama 4.1 and 4.2, and in parallel, we are also working on our next generation of models that will push the frontier in the next year or so.
为了实现这一未来，我们成立了Meta Superintelligence Labs，该实验室包括我们的基础研究、产品和FAIR团队，以及一个专门开发下一代模型的新实验室。目前，我们在Llama 4.1和4.2方面进展顺利，同时也在并行开发新一代模型，这些模型将在未来一年左右推动前沿发展。
We are building an elite, talent-dense team Alexandr Wang is leading the overall team, Nat Friedman is leading our AI Products and Applied Research, and Shengjia Zhao is Chief Scientist for the new effort. They are all incredibly talented leaders, and I'm excited to work closely with them and the world-class group of AI researchers and infrastructure and data engineers that we're assembling.
我们正在组建一支精英化、高密度的人才团队。Alexandr Wang领导整个团队，Nat Friedman负责AI产品和应用研究，Shengjia Zhao担任这一新项目的首席科学家。他们都是极具才华的领导者。我很高兴能与他们以及我们正在汇聚的一流AI研究人员、基础设施工程师和数据工程师密切合作。
I've spent a lot of time building this team this quarter. And the reason that so many people are excited to join is because Meta has all of the ingredients that are required to build leading models and deliver them to billions of people. The people who are joining us are going to have access to unparalleled compute as we build out several multi-gigawatt clusters. Our Prometheus cluster is coming online next year, and we think it's going to be the world's first gigawatt-plus cluster. We're also building out Hyperion, which will be able to scale up to 5 gigawatts over several years, and we have multiple more titan clusters in development as well. We are making all these investments because we have conviction that superintelligence is going to improve every aspect of what we do.
本季度我花了大量时间在组建这支团队。许多人之所以愿意加入，是因为Meta拥有构建领先模型并将其交付给数十亿用户所需的一切条件。加入我们的人将能够使用无与伦比的算力，因为我们正在建设多个多吉瓦级集群。我们的Prometheus集群将于明年上线，我们认为它将成为全球首个超过1吉瓦的集群。我们还在建设Hyperion集群，未来几年可扩展至5吉瓦，同时还有多个Titan集群正在开发中。我们之所以进行这些投资，是因为我们坚信超级智能将改善我们所做的一切。
From a business perspective, I mentioned last quarter that there are five basic opportunities that we are pursuing, improved advertising, more engaging experiences, business messaging, Meta AI and AI devices. So I can go into a bit of detail on each.
从商业角度来看，我在上季度提到我们正在追求的五大核心机会：改进广告、更具吸引力的体验、商业消息传递、Meta AI以及AI设备。接下来我会分别展开讲一点。
On advertising, the strong performance this quarter is largely thanks to AI unlocking greater efficiency and gains across our ad system. This quarter, we expanded our new AI-powered recommendation model for ads to new surfaces and improved its performance by using more signals and longer context. It's driven roughly 5% more ad conversions on Instagram and 3% on Facebook.
在广告方面，本季度的强劲表现主要得益于AI为我们的广告系统带来了更高的效率和收益。本季度，我们将新推出的AI驱动广告推荐模型扩展到更多场景，并通过使用更多信号和更长的上下文来提升其表现。这使得Instagram的广告转化率提升了约5%，Facebook提升了约3%。
We're also seeing good progress with AI for ad creative with a meaningful percent of our ad revenue now coming from campaigns using one of our generative AI features. This is going to be especially valuable for smaller advertisers with limited budgets. While agencies will continue the important work to help larger brands apply these tools strategically.
我们在广告创意领域的AI应用上也取得了显著进展，目前已有相当比例的广告收入来自使用我们生成式AI功能的广告活动。这对预算有限的小型广告主尤其有价值。同时，广告代理公司仍将在帮助大型品牌战略性应用这些工具方面发挥重要作用。
The second opportunity is more engaging experiences. AI is significantly improving our ability to show people content that they're going to find interesting and useful. Advancements in our recommendation systems have improved quality so much that it has led to a 5% increase in time spent on Facebook and 6% on Instagram, just this quarter. There is a lot of potential for content itself to get better too, we're seeing early progress with the launch of our AI video editing tools across Meta AI and our new Edits app. And there's a lot more to do here.
第二个机会是更具吸引力的用户体验。AI显著提升了我们为用户展示有趣且有用内容的能力。本季度，我们的推荐系统质量显著提高，使Facebook用户使用时长增长了5%，Instagram增长了6%。在内容本身的提升方面也潜力巨大，我们的AI视频编辑工具和新推出的Edits应用已取得早期进展，未来还有大量工作要做。
The third opportunity is business messaging. I've talked before about how I believe every business will soon have a business AI, just like they have an e-mail address, social media account and website. We are starting to see some product market fit in a number of countries where we're testing these agents, and we're integrating these business AIs into ads on Facebook and Instagram as well as directly into e-commerce websites.
第三个机会是商业消息传递。我之前提到过，我相信每家企业很快都会拥有一个“商业AI”，就像今天的电子邮件地址、社交媒体账号和网站一样。在我们进行测试的一些国家，已经开始看到产品与市场的契合。我们正在将这些商业AI整合到Facebook和Instagram的广告中，以及直接嵌入电子商务网站。
The fourth opportunity is Meta AI. Its reach is already quite impressive with more than 1 billion monthly actives. Our focus is now deepening the experience and making Meta AI the leading personal AI. As we continue improving our models, we see engagement grow. So our next generation of models is going to continue to really help here.
第四个机会是Meta AI。目前它的覆盖范围已相当可观，月活跃用户超过10亿。我们的重点是进一步深化体验，让Meta AI成为领先的个人AI。随着模型不断改进，我们看到用户参与度持续增长。下一代模型将继续在这一领域发挥重要作用。
And the fifth opportunity is AI devices. We continue to see strong momentum with our Ray-Ban Meta glasses with sales accelerating. We are also launching new performance AI glasses with the Oakley Meta HSTN, they have longer battery life, higher resolution camera and are designed for sports. The percent of people using Meta AI is growing, and we are seeing new users AI retention increase too, which is a good sign for that continued use.
第五个机会是AI设备。我们的Ray-Ban Meta智能眼镜持续保持强劲势头，销售正在加速。我们还将推出新的高性能AI眼镜——Oakley Meta HSTN，它们拥有更长的电池续航、更高分辨率的摄像头，并专为运动设计。使用Meta AI的人群比例在增长，新用户的AI留存率也在提升，这是一个持续使用的积极信号。
I think that AI glasses are going to be the main way that we integrate superintelligence into our day-to-day lives. So it's important to have all of these different styles and products that appeal to different people in different settings.
我认为，AI眼镜将成为我们把超级智能融入日常生活的主要方式。因此，拥有多样化的款式和产品，以满足不同人群在不同场景下的需求，非常重要。
Finally, we're seeing people continue to spend more time with our Quest ecosystem and the community continues to grow steadily. We launched the Meta Quest 3S Xbox Edition last month, and we're seeing record interest in cloud gaming. And beyond gaming, we continue to see a broader set of use cases with media and web browsing contributing a significant portion of engagement.
最后，我们看到用户在我们的Quest生态系统中花费的时间持续增加，社区也在稳步增长。上个月我们推出了Meta Quest 3S Xbox Edition，并且看到了云游戏方面创纪录的兴趣。除了游戏之外，我们还看到更广泛的使用场景，包括媒体和网页浏览，这些也贡献了大量的用户参与度。
We're going to have more to share on all of this, especially the Reality Labs work at Connect on September 17. So I encourage you all to tune into that.
关于这一切，我们将在9月17日的Connect大会上分享更多内容，尤其是Reality Labs的最新进展。我鼓励大家届时关注。
Overall, this has been a busy quarter. Strong business performance and real momentum in assembling both the talent and the compute that we need to build personal superintelligence for everyone. I am very grateful to our teams who are working hard to deliver all of this, and thanks to all of you for being on this journey with us.
总体来看，这是一个忙碌的季度。业务表现强劲，我们也在人才和算力方面积累了真正的动能，以实现为所有人构建个人超级智能的目标。我非常感谢我们的团队为这一切所付出的努力，也感谢大家一路以来的同行。
And now here is Susan.
接下来交给Susan。
Susan J. S. Li
Thanks, Mark, and good afternoon, everyone. Let's begin with our consolidated results. All comparisons are on a year-over-year basis unless otherwise noted.
谢谢你，Mark。大家下午好。我们先从合并业绩开始。除非特别说明，所有对比均为同比。
Q2 total revenue was \$47.5 billion, up 22% on both a reported and constant currency basis. Q2 total expenses were \$27.1 billion, up 12% compared to last year. In terms of the specific line items, cost of revenue increased 16%, driven mostly by higher infrastructure costs and payments to partners, partially offset by a benefit from the previously announced extension of server useful lives.
第二季度总收入为475亿美元，同比增加22%，按报告口径和固定汇率口径均如此。第二季度总支出为271亿美元，同比增加12%。具体项目方面，收入成本增长16%，主要由于基础设施成本和向合作伙伴支付费用增加，部分抵消因素来自此前宣布的服务器使用寿命延长带来的好处。
微软是18%，Google是12%，亚马逊是12%，苹果是10%。
R\&D increased 23%, mostly due to higher employee compensation and infrastructure costs. Marketing and sales increased 9% primarily due to an increase in professional services related to our ongoing platform integrity efforts as well as marketing costs, partially offset by lower employee compensation. G\&A decreased 27%, driven mostly by lower legal-related costs.
研发支出同比增长23%，主要由于员工薪酬和基础设施成本的上升。市场和销售费用同比增长9%，主要由于与我们正在进行的平台完整性工作相关的专业服务费用增加以及市场营销费用增加，部分被员工薪酬下降所抵消。一般及行政费用同比下降27%，主要原因是法律相关费用的减少。
We ended Q2 with over 75,900 employees, down 1% quarter-over-quarter, as the vast majority of the employees impacted by performance-related reductions earlier this year were no longer captured in our head count. This was partially offset by continued hiring in priority areas of monetization, infrastructure, Reality Labs, AI as well as regulation and compliance.
第二季度末我们共有超过75,900名员工，环比下降1%，因为今年早些时候受绩效相关裁减影响的大部分员工已不再计入员工总数。部分减少被在货币化、基础设施、Reality Labs、AI以及合规和监管等重点领域的持续招聘所抵消。
Second quarter operating income was \$20.4 billion, representing a 43% operating margin. Our tax rate for the quarter was 11%, which reflects excess tax benefits from share-based compensation due to the increase in our share price versus prior periods.
第二季度营业收入为204亿美元，营业利润率为43%。本季度的税率为11%，主要反映了由于股价较上期上涨导致的基于股份薪酬的超额税收优惠。
Net income was \$18.3 billion or \$7.14 per share. Capital expenditures, including principal payments on finance leases were \$17 billion, driven by investments in servers, data centers and network infrastructure.
净利润为183亿美元，折合每股7.14美元。资本支出为170亿美元，其中包括融资租赁本金支付，主要用于服务器、数据中心和网络基础设施的投资。
Free cash flow was \$8.5 billion. We repurchased \$9.8 billion of our Class A common stock and paid \$1.3 billion in dividends to shareholders. We also made \$15.1 billion in nonmarketable equity investments in the second quarter which includes our minority investment in Scale AI, along with other investment activities. We ended the quarter with \$47.1 billion in cash and marketable securities and \$28.8 billion in debt.
自由现金流为85亿美元。我们回购了98亿美元的A类普通股，并向股东支付了13亿美元的股息。我们还在第二季度进行了151亿美元的非可流通股权投资，包括对Scale AI的少数股权投资，以及其他投资活动。季度末，我们持有471亿美元的现金和有价证券，负债为288亿美元。
Moving now to our segment results. I'll begin with our Family of Apps segment. Our community across the Family of Apps continues to grow, and we estimate more than 3.4 billion people used at least one of our Family of Apps on a daily basis in June. Q2 total Family of Apps revenue was \$47.1 billion, up 22% year-over-year. Q2 Family of Apps ad revenue was \$46.6 billion, up 21% or 22% on a constant currency basis. Within that revenue, the online commerce vertical was the largest contributor to year-over-year growth.
接下来讲分部业绩。我先从Family of Apps分部开始。我们的应用家族用户社区持续增长，我们估计在6月份有超过34亿人每天使用至少一款我们的应用。第二季度Family of Apps总收入为471亿美元，同比增长22%。第二季度Family of Apps广告收入为466亿美元，同比增长21%，按固定汇率口径为22%。在广告收入中，电子商务垂直领域是同比增长的最大贡献者。
On a user geography basis, ad revenue growth was strongest in Europe and Rest of World at 24% and 23%, respectively. North America and Asia Pacific grew 21% and 18%.
从地域来看，广告收入增长最快的是欧洲和“世界其他地区”，分别为24%和23%；北美增长21%，亚太增长18%。
In Q2, the total number of ad impressions served across our services increased 11%, with growth mainly driven by Asia Pacific. Impression growth accelerated across all regions due primarily to engagement tailwinds on both Facebook and Instagram and to a lesser extent, ad load optimizations on Facebook.
第二季度，我们平台上的广告展示次数总量增长了11%，增长主要由亚太地区推动。所有地区的展示次数增速均有所加快，主要原因是Facebook和Instagram上的用户参与度提升，以及Facebook广告负载优化带来的次要贡献。
The average price per ad increased 9%, benefiting from increased advertiser demand, largely driven by improved ad performance. Pricing growth slowed modestly from the first quarter due to the accelerated impression growth in Q2.
每则广告的平均价格上涨了9%，受益于广告主需求增加，而这一需求主要由广告表现改善所推动。由于第二季度广告展示次数加速增长，定价增速较第一季度有所放缓。
Family of Apps other revenue was \$583 million, up 50%, driven by WhatsApp paid messaging revenue growth as well as Meta Verified subscriptions. We continue to direct the majority of our investments toward the development and operation of our Family of Apps.
Family of Apps的其他收入为5.83亿美元，同比增长50%，主要得益于WhatsApp付费消息收入增长以及Meta Verified订阅。我们仍将大部分投资用于Family of Apps的开发和运营。
In Q2, Family of Apps expenses were \$22.2 billion, representing 82% of our overall expenses. Family of Apps expenses were up 14% and mainly due to growth in employee compensation and infrastructure costs, partially offset by lower legal-related costs.
第二季度，Family of Apps的支出为222亿美元，占总支出的82%。Family of Apps支出同比增长14%，主要原因是员工薪酬和基础设施成本上升，部分被法律相关费用下降所抵消。
Family of Apps operating income was \$25 billion, representing a 53% operating margin.
Family of Apps的营业收入为250亿美元，营业利润率为53%。
Within our Reality Labs segment, Q2 revenue was \$370 million up 5% year-over-year due to increased sales of AI glasses, partially offset by lower Quest sales. Reality Labs expenses were \$4.9 billion, up 1% year-over-year, driven by higher non-head count-related technology development costs. Reality Labs operating loss was \$4.5 billion.
在Reality Labs板块，第二季度收入为3.7亿美元，同比增长5%，主要由于AI眼镜销量增加，但部分被Quest销量下降所抵消。Reality Labs支出为49亿美元，同比增长1%，主要由非人力相关的技术开发成本上升推动。Reality Labs营业亏损为45亿美元。
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.
接下来谈业务展望。推动我们收入表现的主要有两个因素：一是我们为用户社区提供吸引人体验的能力；二是我们长期将这种参与度变现的有效性。
On the first, daily actives continue to grow across Facebook, Instagram and WhatsApp as we make additional improvements to our recommendation systems and product experiences. We continue to see momentum with video engagement, in particular. In Q2, Instagram video time was up more than 20% year-over-year globally. We're seeing strong traction on Facebook as well, particularly in the U.S., where video time spent similarly expanded more than 20% year-over-year. These gains have been enabled by ongoing optimizations to our ranking systems to better identify the most relevant content to show.
首先，在Facebook、Instagram和WhatsApp上，日活用户持续增长，受益于我们在推荐系统和产品体验上的持续优化。尤其是在视频参与度方面，我们持续看到强劲的势头。第二季度，Instagram用户全球观看视频的时间同比增长超过20%。Facebook同样表现强劲，特别是在美国，视频观看时长同比同样增长超过20%。这些成果得益于我们对排序系统的持续优化，使其能够更好地识别最相关的内容。
We expect to deliver additional improvements throughout the year as we further scale up our models and make recommendations more adaptive to a person's interests within their session.
我们预计全年将继续推出更多改进措施，随着模型的进一步扩展，推荐系统将更好地适应用户在使用过程中的兴趣。
Another emphasis of our recommendations work is promoting original content. On Instagram, over 2/3 of recommended content in the U.S. now comes from original posts. In the second half, we'll be focused on further increasing the freshness of original posts, so the right audiences can discover original content from creators soon after it is posted.
我们在推荐工作中的另一个重点是推广原创内容。在Instagram，美国超过三分之二的推荐内容来自原创帖子。下半年，我们将重点提升原创帖子的“新鲜度”，以便目标受众能够在内容发布后尽快发现创作者的原创作品。
We are also making good progress on our longer-term ranking innovations that we expect will provide the next leg of improvements over the coming years. Our research efforts to develop cross-surface foundation recommendation models continue to progress. We are also seeing promising results from using LLM in Threads recommendation systems. The incorporation of LLMs are now driving a meaningful share of the ranking related time spent gains on Threads.
我们在长期排序创新方面也取得了良好进展，预计将在未来几年带来下一阶段的改进。我们的跨平台基础推荐模型研发工作正在推进。同时，在Threads的推荐系统中应用LLM也取得了令人鼓舞的成果。LLM的引入已经在驱动Threads用户时长增长中发挥了重要作用。
We're now exploring how to extend the use of LLMs and recommendation systems to our other apps. We're leveraging Llama and several other back-end processes as well, including actioning bug reports so we can identify and resolve recurring issues more quickly and efficiently. This has resulted in top line bug reports in the U.S. and Canada in Facebook Feed and notifications dropping by roughly 30% over the past 10 months.
我们正在探索如何将LLM和推荐系统的应用扩展到其他应用中。我们还在利用Llama以及其他一些后端流程，包括处理错误报告，以便更快、更高效地识别和解决重复性问题。这使得过去10个月中，美国和加拿大用户在Facebook动态和通知中的重大错误报告数量下降了约30%。
The primary way we're using Llama in our apps today is to power Meta AI which is now available in over 200 countries and territories. WhatsApp continues to be the largest driver of queries as people message Meta AI directly for tasks such as information gathering, homework assistance and generating images. Outside of WhatsApp, we're seeing Meta AI become an increasingly valuable complement to our content discovery engines. Meta AI usage on Facebook is expanding as people use it to ask about posts they see in Feed and find content across our platform in Search.
我们目前在应用中使用Llama的主要方式是驱动Meta AI，该服务现已在200多个国家和地区上线。WhatsApp仍然是查询量最大的驱动来源，用户直接通过消息向Meta AI提出任务请求，例如信息搜索、作业帮助和生成图片。在WhatsApp之外，我们也看到Meta AI正在成为内容发现引擎的重要补充。在Facebook上，Meta AI的使用正在扩大，用户使用它来询问他们在Feed中看到的帖子，并通过搜索在平台上发现更多内容。
高频互动的优势。
Another way we expect Meta AI will help with content discovery is through the automatic translation and dubbing of foreign language content into the audience's local language. We'll have more to share on our efforts there later this year.
我们预计Meta AI帮助内容发现的另一种方式是通过自动翻译和配音，将外语内容转换为观众的本地语言。今年晚些时候我们将分享更多相关进展。
Moving to Reality Labs. The growth of Ray-Ban Meta sales accelerated in Q2, with demand still outstripping supply for the most popular SKUs despite increases to our production earlier this year. We're working to ramp supply to better meet consumer demand later this year.
接下来是Reality Labs。Ray-Ban Meta的销售在第二季度加速增长，尽管今年早些时候我们已增加产量，但最受欢迎的SKU仍然供不应求。我们正在努力提升产能，以更好地满足今年晚些时候的消费者需求。
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 optimize ad supply across each surface to better deliver ads at the time and place they are most relevant to people. In Q2, we also began introducing ads within Feed on Threads and the Updates tab of WhatsApp, which is a separate space away from people's chats.
接下来说推动收入表现的第二个因素，即提升变现效率。这项工作的第一部分是优化自然参与中的广告投放水平。我们继续优化各个场景的广告供应，以便在最相关的时间和地点向用户展示广告。第二季度，我们开始在Threads的Feed以及WhatsApp的更新标签页（独立于聊天界面的空间）引入广告。
As of May, advertisers globally can now run video and image ads to Threads users in most countries, including the United States. While ad supply remains low and Threads is not expected to be a meaningful contributor to overall impression growth in the near term, we are optimistic about the longer-term opportunity with Threads as the community and engagement grow and monetization scales.
自5月起，全球广告主已可以在包括美国在内的大多数国家向Threads用户投放视频和图片广告。尽管广告供应仍然较低，Threads在短期内预计不会对整体广告展示增长有显著贡献，但随着其社区和用户参与度的提升以及变现规模的扩大，我们对Threads的长期机会保持乐观。
On WhatsApp, we are rolling out ads in status and channels, along with channel subscriptions in the Updates tab to help businesses reach the more than 1.5 billion daily actives who visit that part of the app. We expect the introduction of ads and status will be gradual over the course of this year and next, with low levels of expected ad supply initially.
在WhatsApp上，我们正在逐步在状态和频道中推出广告，并在更新标签页中引入频道订阅，帮助企业触达超过15亿日活用户。我们预计广告和状态的引入将在今年和明年逐步推进，初期广告供应量较低。
We also expect WhatsApp ads and status to earn a lower average price than Facebook or Instagram ads for the foreseeable future, due in part towards WhatsApp skew toward lower monetizing markets, and more limited information that can be used for targeting. Given this, we do not expect ads and status to be a meaningful contributor to total impressions or revenue growth for the next few years.
我们还预计，在可预见的未来，WhatsApp广告和状态的平均价格将低于Facebook或Instagram广告，部分原因在于WhatsApp用户群体偏向低变现市场，且可用于定向的信息有限。基于此，我们预计在未来几年内，WhatsApp广告和状态不会对广告展示总量或收入增长产生显著贡献。
不太好理解。
The second part of increasing monetization efficiency is improving marketing performance. There are three areas of this work that I'll focus on today, improving our ad systems, advancing our ads products, including by building tools that assist in ads creation and evolving our ads platform to drive results that are optimized for each business' objectives.
提升变现效率的第二部分是改善营销表现。今天我将重点介绍三个方面：改进广告系统、提升广告产品（包括构建辅助广告创作的工具），以及不断发展广告平台，以实现针对各个企业目标优化的效果。
First is our ad systems where we're innovating in both the ads retrieval and ranking stages to serve more relevant ads to people. A lot of this work involves us continuing to advance the modeling innovations we've introduced previously while expanding their adoption across our platform.
首先是我们的广告系统，我们在广告检索和排序阶段进行创新，以向用户提供更相关的广告。许多工作涉及进一步推进我们此前引入的建模创新，并扩大其在整个平台的应用。
The Andromeda model architecture we began introducing in the second half of 2024 powers the ads retrieval stage of our ad system, where we select the few thousand most relevant ads from tens of millions of potential candidates. In Q2, we made enhancements to Andromeda that enabled it to select more relevant and more personalized ads candidates while also expanding coverage to Facebook Reels. These improvements have driven nearly 4% higher conversions on Facebook Mobile Feed and Reels.
我们在2024年下半年开始引入的Andromeda模型架构驱动着广告系统的检索阶段，它负责从数千万潜在广告中筛选出几千条最相关的广告。第二季度，我们对Andromeda进行了改进，使其能够选择更相关、更个性化的广告候选项，同时扩展覆盖至Facebook Reels。这些改进推动了Facebook移动端Feed和Reels的转化率提升了近4%。
Our new Generative Ads Recommendation system, or GEM, powers the ranking stage of our ad system, which is the part of the process after ads retrieval where we determine which ads to show someone from candidates suggested by our retrieval engine. In Q2, we improved the performance of GEM by further scaling our training capacity and adding organic and ads engagement data on Instagram. We also incorporated new advanced sequence modeling techniques that helped us double the length of event sequences we use, enabling our systems to consider a longer history of the content or ads that a person has engaged with in order to provide better ad selections.
我们的新一代广告生成推荐系统（Generative Ads Recommendation system，简称GEM）驱动着广告系统的排序阶段，也就是在广告检索之后，从检索引擎推荐的候选广告中决定向用户展示哪些广告。在第二季度，我们通过进一步扩展训练能力，并加入Instagram的自然内容和广告互动数据，提升了GEM的性能。我们还引入了新的高级序列建模技术，使事件序列长度翻倍，从而让系统能够考虑用户与内容或广告的更长历史互动，以便提供更优质的广告选择。
The combination of these improvements increased ad conversions by approximately 5% on Instagram and 3% on Facebook Feed and Reels in Q2.
这些改进综合起来，使Instagram的广告转化率在第二季度提升了约5%，Facebook Feed和Reels提升了约3%。
看着不明显。
Finally, we expanded coverage of our Lattice model architecture in Q2. We first began deploying Lattice in 2023 with our later-stage ads ranking efforts, allowing us to run significantly larger models that generalize learnings across objectives and surfaces in place of numerous smaller ads models that have historically been optimized for individual objectives and surfaces.
最后，在第二季度我们扩大了Lattice模型架构的应用范围。我们在2023年首次将Lattice部署于广告排序的后期阶段，使我们能够运行规模更大的模型，以跨目标和场景进行泛化学习，取代历史上针对单一目标或场景优化的多个小模型。
In April, we began deploying Lattice to earlier-stage ads ranking models as well. This is leading not only to greater capacity and engineering efficiency but also improved performance with the recent Lattice deployments driving a nearly 4% increase in ad conversions across Facebook Feed and Reels in Q2.
今年4月，我们也开始将Lattice应用于广告排序的早期阶段。这不仅提升了系统容量和工程效率，还改进了整体表现。近期的Lattice部署在第二季度推动Facebook Feed和Reels的广告转化率提升了近4%。
Next, ad products. Here, we're seeing strong momentum with our Advantage+ suite of AI-powered solutions. In Q2, we completed the rollout of our streamlined campaign creation flow for Advantage+ sales and app campaigns, which makes it easier for advertisers to realize the performance benefits from Advantage+ by having it turned on at the beginning. We've seen lifts in advertiser adoption of sales and app campaigns since we've expanded availability and are working to complete the rollout for leads campaigns in the coming months.
接下来是广告产品。在这里，我们看到我们的Advantage+ AI驱动解决方案套件保持强劲势头。第二季度，我们完成了Advantage+销售和应用广告系列的简化创建流程，这使广告主能够在一开始就更容易享受到Advantage+带来的性能提升。自从扩大可用范围以来，我们看到广告主对销售和应用广告系列的采用率有所提升，并计划在未来几个月完成潜在客户广告系列的全面上线。
Within our Advantage+ Creative suite, adoption of genAI ad creative tools continues to broaden. Nearly 2 million advertisers are now using our video generation features, image animation and video expansion, and we're seeing strong results with our text generation tools as we continue to add new features.
在Advantage+ Creative套件中，生成式AI广告创意工具的采用率持续扩大。目前已有近200万广告主在使用我们的视频生成、图片动画和视频扩展功能，同时，我们的文本生成工具在持续增加新功能的过程中也取得了强劲效果。
In Q2, we started testing AI-powered translation so that advertisers can automatically translate the caption of their ads to 10 different languages. While it's early, we have seen promising performance lifts in our prelaunch tests.
在第二季度，我们开始测试AI驱动的翻译功能，使广告主能够自动将广告文案翻译成10种不同语言。虽然还处于早期阶段，但我们在预发布测试中已经看到了令人鼓舞的表现提升。
We're also continuing to see strong adoption of image expansion among small- and medium-sized advertisers, which speaks to how these tools help businesses who have fewer resources to develop creative. With larger advertisers, we expect agencies will continue to be valuable partners in helping apply these new tools to drive performance.
我们还看到中小型广告主对图像扩展功能的强劲采用，这说明这些工具能够有效帮助资源有限的企业开发广告创意。对于大型广告主，我们预计广告代理公司将继续作为有价值的合作伙伴，帮助他们应用这些新工具以提升表现。
Outside of Advantage+, we're seeing good momentum in business messaging, particularly in the U.S., where click to message revenue grew more than 40% year-over-year in Q2. The strong U.S. growth is benefiting from a ramp in adoption of our website to message ads, which drive people to a business's website for more information before choosing to launch a chat with the business in one of our messaging apps.
在Advantage+之外，我们在商业消息传递方面也看到了良好的势头，特别是在美国，点击消息广告收入在第二季度同比增长超过40%。美国的强劲增长得益于“网站到消息广告”的采用率上升，该广告能将用户引导至企业网站获取更多信息，然后再选择通过我们的消息应用与企业发起对话。
Finally, we continue to evolve our ads platform to drive results that are optimized for each business' objectives and the way they measure results. In Q2, we completed the global rollout of our incremental attribution feature, which is the only product on the market that optimizes for and reports on incremental conversions, which are conversions that would not have happened without a person seeing the ad.
最后，我们继续发展广告平台，以实现针对各企业目标和其衡量方式优化的结果。在第二季度，我们完成了增量归因功能的全球上线，这是市场上唯一一款优化并报告“增量转化”的产品，即那些如果用户没有看到广告就不会发生的转化。
We also launched omnichannel ads globally in Q2 and which enable advertisers to optimize for incremental sales, both in-store and online with just one campaign. In tests, advertisers using omnichannel ads have seen a median 15% reduction in total cost per purchase compared to website-only optimization.
我们还在第二季度全球推出了全渠道广告，使广告主能够通过一次广告活动同时优化门店和线上渠道的增量销售。在测试中，使用全渠道广告的广告主相比仅做网站优化，单次购买的总成本中位数下降了15%。
Next, I would like to discuss our approach to capital allocation. Our primary focus remains investing capital back into the business with infrastructure and talent being our top priorities.
接下来，我想谈谈我们的资本配置策略。我们的首要重点仍然是将资本重新投入业务，其中基础设施和人才是最优先的方向。
I'll start with hiring. Our approach to adding head count continues to be targeted at the company's highest priority areas. We expect talent additions across all of our priority areas will continue to drive overall head count growth through this year and 2026. While head count growth in our other functions remains constrained, within AI, we've had a particular emphasis on recruiting leading talent within the industry, as we build out Meta Superintelligence Labs to accelerate our AI model development and product initiatives.
先从招聘谈起。我们增加员工的方式依旧是聚焦在公司最优先的领域。预计在今年和2026年，我们会在所有优先领域继续增加人才，从而推动整体员工数量增长。虽然其他职能部门的员工增长仍然受到限制，但在AI领域，我们特别强调吸引行业顶尖人才，因为我们正在建设Meta Superintelligence Labs，以加速AI模型研发和产品创新。
Next, infrastructure. We expect having sufficient compute capacity will be central to realizing many of the largest opportunities in front of us over the coming years. We continue to see very compelling returns from our AI capacity investments in our core ads and organic engagement initiatives and expect to continue investing significantly there in 2026.
接下来是基础设施。我们认为，在未来几年，拥有充足的算力将是实现重大机遇的核心。我们在广告和用户自然互动方面的AI算力投资，已经带来了非常可观的回报，并预计在2026年还将继续在这方面进行大量投资。
We also expect that developing leading AI infrastructure will be a core advantage in developing the best AI models and product experiences. So we expect to ramp our investments significantly in 2026 to support that work.
我们也认为，建设领先的AI基础设施将成为开发最佳AI模型和产品体验的核心优势。因此，我们预计将在2026年大幅增加这方面的投资，以支持相关工作。
Moving to our financial outlook. We expect third quarter 2025 total revenue to be in the range of \$47.5 billion to \$50.5 billion. Our guidance assumes foreign currency is an approximately 1% tailwind to year-over-year total revenue growth, based on current exchange rates. While we are not providing an outlook for fourth quarter revenue, we would expect our year-over-year growth rate in the fourth quarter of 2025 to be slower than the third quarter as we lap a period of stronger growth in the fourth quarter of 2024.
接下来是财务展望。我们预计2025年第三季度的总营收将在475亿美元至505亿美元之间。基于当前汇率，我们的指引假设外汇将对同比营收增长带来约1%的顺风。虽然我们没有提供2025年第四季度的营收指引，但预计2025年第四季度的同比增长率将低于第三季度，因为我们将对比2024年第四季度的高基数。
Turning now to the expense outlook. We expect full year 2025 total expenses to be in the range of \$114 billion to \$118 billion, narrowed from our prior outlook of \$113 billion to \$118 billion and reflecting a growth rate of 20% to 24% year-over-year.
再来看费用展望。我们预计2025全年总费用将在1140亿至1180亿美元之间，相比之前1130亿至1180亿美元的预期有所收窄，对应的同比增长率为20%至24%。
While we're still very early in planning for next year, there are a few factors we expect will provide meaningful upward pressure on our 2026 total expense growth rate. The largest single driver of growth will be infrastructure costs, driven by a sharp acceleration in depreciation expense growth and higher operating costs as we continue to scale up our infrastructure fleet. Aside from infrastructure, we expect the second largest driver of growth to be employee compensation as we add technical talent in priority areas and recognize a full year of compensation expenses for employees hired throughout 2025. We expect these factors will result in a 2026 year-over- year expense growth rate that is above the 2025 expense growth rate.
虽然我们对明年的规划还处于早期阶段，但有几个因素预计将对2026年总费用的增长率造成显著上行压力。最大单一驱动因素将是基础设施成本，因为随着我们持续扩大基础设施规模，折旧费用的增长将显著加快，同时运营成本也会上升。除基础设施外，我们预计第二大驱动因素将是员工薪酬，因为我们会在重点领域增加技术人才，并在2026年全年确认2025年招聘员工的薪酬成本。我们预计这些因素将导致2026年的费用同比增长率高于2025年。
没有云计算的业务是个缺陷。
Turning now to the CapEx outlook. We currently expect 2025 capital expenditures, including principal payments on finance leases, to be in the range of $66 billion to $72 billion, narrowed from our prior outlook of $64 billion to $72 billion and up approximately $30 billion year-over-year at the midpoint. While the infrastructure planning process remains highly dynamic, we currently expect another year of similarly significant CapEx dollar growth in 2026 as we continue aggressively pursuing opportunities to bring additional capacity online to meet the needs of our AI efforts and business operations.
接下来谈资本支出展望。我们目前预计，2025年的资本支出（包括融资租赁的本金支付）将在660亿至720亿美元之间，较此前640亿至720亿美元的预期区间有所收窄，并在中位数水平上较去年同比增加约300亿美元。尽管基础设施规划过程依然高度动态，但我们目前预计，2026年仍将迎来同样显著的资本支出增长，因为我们将继续积极推进新增算力产能上线，以满足AI研发和业务运营的需求。
On to tax. With the enactment of the new U.S. tax law, we anticipate a reduction in our U.S. federal cash tax for the remainder of the current year and future years. There are several alternative ways of implementing the provisions of the act, which we are currently evaluating. While we estimate that the 2025 tax rate will be higher than our Q2 tax rate, we cannot quantify the magnitude at this time.
接下来是税务。随着美国新税法的颁布，我们预计在今年剩余时间和未来几年，美国联邦现金税负将有所减少。该法案条款存在多种实施方式，我们目前正在评估。虽然我们预计2025年的税率将高于第二季度的税率，但目前无法量化其具体幅度。
In addition, we continue to monitor an active regulatory landscape, including the increasing legal and regulatory headwinds in the EU that could significantly impact our business and our financial results. For example, we continue to engage with the European Commission on our Less Personalized Ads offering or LPA, which we introduced in November 2024 and based on feedback from the European Commission in connection with the DMA.
此外，我们持续关注活跃的监管环境，其中包括欧盟日益加剧的法律和监管阻力，这可能对我们的业务和财务业绩产生重大影响。例如，我们正就“低个性化广告”（LPA）与欧盟委员会保持沟通，该产品于2024年11月推出，是基于委员会在《数字市场法案》(DMA) 框架下的反馈。
As the commission provides further feedback on LPA, we cannot rule out that it may seek to impose further modifications to it that would result in a materially worse user and advertiser experience. This could have a significant negative impact on our European revenue as early as later this quarter. We have appealed the European Commission's DMA decision, but any modifications to our model may be imposed during the appeal process.
随着欧盟委员会对LPA提供进一步反馈，我们不能排除其可能要求进一步修改，从而导致用户和广告商体验显著恶化。这可能会在本季度晚些时候就对我们在欧洲的营收产生重大负面影响。我们已对欧盟委员会的DMA裁决提出上诉，但在上诉过程中，任何对我们模式的修改都有可能被强制执行。
In closing, this was another strong quarter for our business as our investments in infrastructure and technical talent continue to improve core ads performance and engagement on our platforms. We expect the significant investments we're making now will allow us to continue leveraging advances in AI to extend those gains and unlock a new set of opportunities in the years to come. With that, Krista, let's open up the call for questions.
最后总结，本季度我们业务再次表现强劲，基础设施和技术人才方面的投资继续推动核心广告表现和平台用户互动的提升。我们预计当前的大规模投资将使我们能够持续利用AI的进步来延续这些成果，并在未来几年解锁新的机遇。说到这里，Krista，我们可以开放问答环节了。
Question-and-Answer Session
问答环节
Operator
主持人
\[Operator Instructions] Your first question comes from the line of Eric Sheridan with Goldman Sachs.
\[操作提示] 您的第一个问题来自高盛的 Eric Sheridan。
Eric James Sheridan
Mark, when you think about where the AI parts of your business have been evolving over the last 3 to 6 months, I wanted to know what your key learnings were as you went deep into that strategy that informed some of the shifts in both talent, acquisition and compute, coupled with some of the blogs you put out recently in terms of how that strategy might have evolved based on those key learnings?
Mark，当你回顾过去三到六个月中你们业务的AI部分发展时，我想知道你在深入推进该战略过程中获得的关键经验教训是什么，这些经验如何影响了你们在人才、收购和算力方面的调整？再结合你最近发表的一些博客内容，这些经验是如何推动战略演变的？
And Susan, building on Mark's comments on scaling talent and compute, I want to know if you go a little bit deeper on how we should be thinking about those two components driving some of the commentary you've given around OpEx and CapEx over the next 12 to 18 months.
另外，Susan，基于Mark关于扩大人才和算力的评论，我希望你能更深入说明一下，在未来12到18个月中，这两个因素应如何影响我们对你在运营开支（OpEx）和资本开支（CapEx）相关评论的理解。
Mark Elliot Zuckerberg
Yes, sure. I can start. At a high level, I think that there are all these questions that people have about what are going to be the time lines to get to really strong AI or superintelligence or whatever you want to call it. And I guess that each step along the way so far, we've observed the more kind of aggressive assumptions, or the fastest assumptions have been the ones that have most accurately predicted what would happen. And I think that, that just continued to happen over the course of this year, too.
好的，当然。我可以先开始。从宏观来看，人们总是有很多关于实现强大AI或者超级智能（不管你怎么称呼它）的时间表的问题。而迄今为止，在这个过程中，我们发现那些更为激进的假设，或者说最乐观的预测，反而最准确地反映了实际发生的情况。我认为在今年的进展中，这种情况也在继续出现。
And so I've given a number of those anecdotes on these earnings calls in the past. And I think, certainly, some of the work that we're seeing with teams internally being able to adapt Llama 4 to build autonomous AI agents that can help improve the Facebook algorithm to increase quality and engagement are like -- I mean, that's like a fairly profound thing if you think about it. I mean it's happening in low volume right now. So I'm not sure that, that result by itself was a major contributor to this quarter's earnings or anything like that. But I think the trajectory on this stuff is very optimistic.
我在以往的财报电话会议中已经分享过一些案例。而且，毫无疑问，我们内部团队已经能够利用Llama 4开发自主AI代理，这些代理可以帮助改进Facebook的算法，从而提升内容质量和用户参与度——这其实是一个相当深远的突破。虽然目前还处于低规模测试阶段，所以我不认为这一成果单独对本季度的财务表现有重大贡献。但从整体发展趋势来看，这是非常乐观的。
And I think it's one of the interesting challenges in running a business like this now is there's just a very high chance it seems like the world is going to look pretty different in a few years from now. And on the one hand, there are all these things that we can do, there are improvements to our core products that exist.
我认为经营这样一家公司的有趣挑战之一在于，现在很有可能在几年后世界的样貌会大不相同。一方面，我们可以做很多事情，可以对现有的核心产品不断改进。
And then I think we have this principle that we believe in across the company, which we tell people take superintelligence seriously. And the basic principle is this idea that we think that this is going to really shape all of our systems sooner rather than later, not necessarily on the trajectory of a quarter or 2, but on the trajectory of a few years. And I think that that's just going to change a lot of the assumptions around how different things work across the company.
此外，公司内部有一个我们非常认同的原则，我们告诉大家要认真对待超级智能。其核心理念是，我们认为这将会在不远的未来彻底塑造我们的所有系统——不是以季度为单位，而是以几年为单位的时间尺度。这将改变公司内部很多关于业务运作方式的基本假设。
So anyway, I think it's basically just what we're continually observing how this works and what the trajectory or the pace of AI progress has been. I think it continues to be on the faster end. And that I think informs a lot of the decisions from everything from the importance and value of having the absolute best and most elite talent-dense team at the company to making sure that we have a leading compute fleet so that the people here can do -- obviously, the researchers here have more compute per person to be able to lead their research and then roll it out to billions of people across our products, making sure that we build and drive these products through all of the different things that we do, which I think is one of the things that our company is the best in the world at is basically when we take a technology, we're good at driving that through all of our apps and our ad systems and all that stuff, it's not just going to kind of sit on the vine.
所以，总的来说，我们一直在观察AI的发展规律以及进展速度。我认为它依然处于快速发展的区间。这一认识指导了我们的许多决策，从确保我们拥有最优秀、最精英、人才密度最高的团队，到确保我们配备行业领先的算力资源，使研究人员能够获得更多人均算力来推进研究，再到将这些成果应用到数十亿用户的产品中。我们必须确保通过我们的各种业务来开发和推动这些产品——我认为这正是我们公司在全球最擅长的能力之一，即把一项技术真正大规模应用到我们的应用程序、广告系统等业务中，而不是让它停留在研发阶段。
I think that there's no other company, I think that is as good as us at kind of taking something and kind of getting it in front of billions of people. So yes, I mean, we're just going to push very aggressively on all of that. But at some level, yes, this is -- there's sort of a bet in the trajectory that we're seeing and those are the signals that we're seeing. But we're just trying to read it.
我认为没有其他公司能像我们一样把一项技术真正推广到数十亿用户面前。所以，是的，我们会在所有这些方面采取非常积极的行动。但从某种意义上讲，这也是基于我们对AI发展轨迹的判断和我们所看到的信号所做的战略性押注。而我们的任务就是去解读这些信号。
Susan J. S. Li
Eric, for the second part of your question, we haven't, in fact, kicked off our budgeting process for 2026. So thinking about next year, there are clearly many, many moving pieces in a very dynamic operating environment. But there are certain aspects that we have some visibility into today, including the rough shape of our 2026 infrastructure plans. And that flows through into our expense expectations next year. And we also have some visibility into the compensation expense growth that we'll recognize from the AI talent that we're hiring this year. And so those two things are part of why we gave a little bit of an early preview into the expectations for growth for 2026 total expenses as well as for 2026 CapEx.
Eric，关于你问题的第二部分，我们实际上还没有启动2026年的预算流程。所以在考虑明年的时候，在这样一个高度动态的运营环境下，确实有很多不确定因素。但目前我们对某些方面已经有了一定的可见性，包括2026年基础设施规划的大致方向。这也会反映到我们对明年费用的预期上。同时，我们也对今年招聘AI人才所带来的薪酬成本增长有一定的可见性。因此，这两个因素是我们提前对2026年总费用和资本开支（CapEx）增长预期进行初步披露的部分原因。
So on the total expenses side, as I mentioned, we expect infrastructure will be the single largest contributor to 2026 expense growth. That's driven primarily by a sharp acceleration in depreciation expense growth in 2026, largely driven by recognizing incremental depreciation from assets that we purchased and place in service in '26 as well as from infrastructure deployed through 2025 that will recognize a full year of depreciation next year. We also expect a greater mix of our CapEx to be in shorter-lived assets in 2025 and '26 than it has been in prior years.
在总费用方面，正如我所提到的，我们预计基础设施将是2026年费用增长的最大驱动因素。这主要来自折旧费用的显著加速增长，原因包括：2026年新增并投入使用的资产所带来的额外折旧，以及2025年部署的基础设施将在2026年确认整整一年的折旧。此外，我们预计2025年和2026年的资本开支中，短期资产的比例将高于以往几年。
And then the other component of infra cost growth next year would come from higher operating expenses, including energy costs, leases, maintenance and operational expenses that are associated with maintaining that fleet. And we also expect some increased spend on cloud services in '26 to meet our capacity needs as well as growth in network-related costs.
另外，2026年基础设施成本增长的另一部分将来自更高的运营费用，包括能源成本、租赁费、维护费用和与运行整个机群相关的运营开支。我们还预计在2026年会增加云服务的支出以满足容量需求，同时网络相关成本也将增长。
So a lot going on, on the infrastructure side as it contributes to the 2026 total expense number. After that, employee compensation is the next largest driver of expense growth in '26. Again, driven primarily in the investments that we're making in technical talent, including recognizing a full year of compensation expense for the AI talent we hire this year.
因此，基础设施相关的开支将在2026年总费用中占据重要比重。其次，员工薪酬将是2026年费用增长的第二大驱动因素。这主要来自我们在技术人才方面的投资，包括对今年招聘的AI人才在2026年确认完整年度的薪酬费用。
I realize this answer is getting a little long, so I'll try to wrap up quickly. On the CapEx side, the big driver of our increased CapEx in '26 will be scaling genAI capacity as we build out training capacity that's going to drive higher spend across servers, networking, data centers next year. We also expect that we're going to continue investing significantly in core AI in 2026. And again, this is a pretty -- a very dynamic area of planning, but we wanted to share kind of our early thoughts as things are shaping up.
我意识到这个回答有点长，所以我会尽快总结。在资本开支方面，2026年CapEx增长的最大驱动力将是扩大生成式AI的算力，我们正在建设训练能力，这将在明年带动服务器、网络和数据中心方面的更高投入。我们还预计在2026年会继续在核心AI上进行大量投资。再次强调，这是一个非常动态的规划领域，但我们希望能够分享我们目前对趋势形成中的一些初步想法。
Operator
主持人
Your next question comes from the line of Brian Nowak with Morgan Stanley.
接下来是来自摩根士丹利的 Brian Nowak 的问题。
Brian Thomas Nowak
I have two. The first one, Mark, just to kind of go back to the intelligence labs and sort of the vision for superintelligence. As you sort of sit here now versus 12 months ago, can you just sort of walk us through any changes of technological constraints or technological gating factors that you are most focused on overcoming in the next 24 months that may have been different than they were in the past, just to make sure you can really lead in the idea of superintelligence over the next 10 years?
我有两个问题。第一个问题是，Mark，回到intelligence labs以及超级智能的愿景。站在现在的角度对比12个月前，你能否谈一谈在未来24个月里，你最关注需要克服的技术约束或关键限制因素有哪些？这些因素与过去相比是否有变化？从而确保你们在未来10年里能真正引领超级智能的发展？
And then the second one to Susan or Mark, one on the core. You've made so many improvements to the core to drive higher engagement, recommendations, et cetera. Can you just walk us through a couple of the factors you're still most excited about to come in the next 18 months that you think could drive a further lift to engagement on the core platform?
第二个问题想请Susan或Mark回答，关于核心平台。你们已经对核心平台做了很多改进，以推动更高的用户参与度和推荐质量。能否介绍一下在未来18个月里，你们最期待的几个因素是什么？这些因素可能会进一步提升核心平台的用户参与度？
Mark Elliot Zuckerberg
Yes, sure. I mean in terms of the research agenda and a bunch of the areas that we're very focused on, I do think focusing on self-improvement is a very important area of research. And there's obviously different scaling paradigms, and I don't want to get too much into the detail of research that we're doing on this. But I think that for developing superintelligence, at some level, you're not just going to be learning from people because you're trying to build something that is fundamentally smarter than people. So it's going to need to learn how to -- or you're going to need to develop a way for it to be able to improve itself.
好的，当然。从研究议程以及我们重点关注的一系列领域来看，我认为“自我改进”是一个非常重要的研究方向。显然，这里存在不同的扩展范式，我不想过多涉及我们正在进行的研究细节。但我认为，要发展超级智能，在某种意义上，它不只是向人类学习，因为我们试图构建的是比人类更聪明的东西。所以它必须学会如何自我提升——或者说，我们需要开发一种机制，使其能够自我改进。
So that, I think, is a very fundamental thing. That is going to have a very broad implications for how we build products, how we run the company, new things that we can invent, new discoveries that can be made, society more broadly. I think that that's just a very fundamental part of this.
因此，我认为这是一个非常根本的要素。这将在如何构建产品、如何运营公司、我们能发明哪些新事物、能实现哪些新发现，以及对整个社会层面，都会产生广泛影响。我认为这就是超级智能研究的一个核心组成部分。
In terms of the shape of the effort overall, I guess I've just gotten a little bit more convinced around the ability for small talent-dense teams to be the optimal configuration for driving frontier research. And it's a bit of a different setup than we have on our other world-class machine learning system.
从整体投入的形态来看，我越来越相信小型、高人才密度的团队是推动前沿研究的最佳配置。这与我们在其他世界级机器学习系统上的组织方式有些不同。
So if you look at like what we do in Instagram or Facebook or our ad system, we can very productively have many hundreds or thousands of people basically working on improving those systems, and we have very well-developed systems for kind of individuals to run tests and be able to test a bunch of different things. You don't need every researcher there to have the whole system in their head. But I think for this -- for the leading research on superintelligence, you really want the smallest group that can hold the whole thing in their head, which drives, I think, some of the physics around the team size and how -- and the dynamics around how that works.
举例来说，在Instagram、Facebook或广告系统的研发中，我们可以非常高效地组织数百甚至上千人来优化这些系统，而且我们已经建立了非常成熟的体系，让个人研究人员可以独立运行实验、测试不同的方案。在这种场景下，不需要每个研究人员都完全掌握整个系统。但在超级智能的前沿研究中，你真正需要的是一个尽可能小的团队，这个团队能够在脑中完整把握整个系统。这也决定了团队规模及其运作动态上的一些“物理规律”。
But I'll hand it over to Susan to talk about more of the practical stuff.
不过接下来我把话交给Susan，让她谈一些更实际的内容。
Susan J. S. Li
Brian, on the sort of forward-looking road map for the core recommendation engine. There are a handful of shorter-term things that we're focused on in the near term. One is we're focused on making recommendations even more adaptive to what a person is engaging with during their session so that the recommendations we surface are the most relevant to what they're interested in at that moment. And we're making optimizations to help the best content from smaller creators break-out by matching it to the right audiences sooner after it gets posted.
Brian，关于核心推荐引擎的前瞻性路线图，我们在近期主要聚焦几个短期目标。其一是让推荐结果更具适应性，根据用户在一次使用会话中的实时互动调整，从而确保推荐的内容与他们当下兴趣最相关。我们还在进行优化，以便让小创作者的优质内容能够更快被匹配到合适的受众，从而获得更好的传播效果。
字节的推荐引擎已经没什么独特性。
And we're also working on improving the ability for our systems to discover more diversified and niche interest for each person through interest exploration and learning explicit user preferences. We're also planning to scale up our models further and incorporate more advanced techniques that should improve the overall quality of recommendations.
此外，我们正在提升系统的能力，使其能够通过兴趣探索和学习用户的显性偏好，更好地发现每位用户多样化和小众的兴趣点。我们还计划进一步扩大模型规模，并引入更先进的技术，以提升推荐的整体质量。
But we also have a lot of long-term bets in the hopper around areas like developing foundational models that will support recommendations across multiple services. Incorporating LLMs more deeply into our recommendation systems. And a big focus of this work is going to be on optimizing the systems to make them more efficient. So that we can continue to scale up the capacity that we use for our recommendation systems without eroding the ROI that we deliver.
同时，我们也有许多长期投入的方向，比如开发能够支持跨多个服务的基础模型，更深入地将大语言模型（LLMs）融入推荐系统。而这项工作的重点之一，将是优化系统以提高效率，从而在不断扩大推荐系统规模的同时，依然能够保持我们所交付的投资回报率（ROI）不被稀释。
Operator
主持人
Your next question comes from the line of Doug Anmuth with JPMorgan.
接下来是摩根大通的 Doug Anmuth 提问。
Douglas Till Anmuth
One for Mark and one for Susan. Mark, Meta has been a huge proponent of open source AI, has your thinking changed here at all, just as you pursue superintelligence and push for even greater returns on your significant infrastructure investments?
我有两个问题，一个给Mark，一个给Susan。Mark，Meta一直是开源AI的积极推动者。随着你们推进超级智能并寻求在重大基础设施投资上获得更大回报，你在开源问题上的想法有没有发生变化？
And then, Susan, your comments on '26 CapEx suggest more than \$100 billion of spend next year potentially. Do you continue to expect to finance all this yourself? Or could there be opportunities to partner here?
另外，Susan，你对2026年资本开支的评论显示，明年可能会超过1000亿美元。你们是否仍预计完全自筹资金？还是会考虑合作机会？
Mark Elliot Zuckerberg
Yes. I mean on open source, I don't think that our thinking has particularly changed on this. We've always open sourced some of our models and not open sourced everything that we've done. So I would expect that we will continue to produce and share leading open source models.
好的，关于开源问题，我认为我们的想法并没有发生根本性的变化。我们一直以来都是开源部分模型，而不是把所有成果都开源。所以我预计我们将会继续产出并分享一些领先的开源模型。
I also think that there are a couple of trends that are playing out. One is that we're getting models that are so big that they're just not practical for a lot of other people to use. So it's -- we would kind of wrestle with whether it's productive or helpful to share that or if that's really just primarily helping competitors or something like that. So I think that there's that concern. And then obviously, as you approach real superintelligence, I think there is a whole different set of safety concerns that I think we need to take very seriously, that I wrote about in my note this morning.
我还认为，目前有几个趋势正在显现。一是模型规模变得非常庞大，以至于对很多其他机构来说并不具备实际可用性。因此，我们需要权衡共享这些模型是否真的有生产力或帮助性，还是主要在帮助竞争对手。这是一个担忧。其次，显然随着接近真正的超级智能，还会出现一整套不同的安全问题，我认为必须非常认真对待。我今天早上的备忘录中也写过相关内容。
But I think the bottom line is, I would expect that we will continue open sourcing work. I expect us to continue to be a leader there. And I also expect us to continue to not open source everything that we do, which is a continuation of kind of what we've been kind of working on.
但我认为核心结论是：我们会继续开源部分成果，并且预计会继续在这一领域保持领先地位。同时，我们也会继续坚持并非将所有工作开源，这与我们过去的做法是一脉相承的。
And yes, I mean, I think Susan will talk a little bit more about the infrastructure, but it really is a massive investment. We think it will be good over time. But we do take very seriously that this is a just massive amount of capital to convert into many gigawatts of compute which we think is going to help us produce leading research and quality products and in running the business, I do look for opportunities to basically convert capital into quality of products that we can deliver for people. But this is certainly a massive bet that we're kind of -- we're focused on, and we want to make sure that what we build accrues to building the best products that we can deliver to the billions of people who use our services.
此外，我认为Susan会进一步谈到基础设施，但这确实是一项巨大的投资。我们认为从长期来看这是有价值的。但我们也非常认真地对待这一点：这是将庞大资本转化为数吉瓦算力的过程，而这些算力将帮助我们产出领先的研究成果和高质量产品。在经营业务时，我会寻找机会，将资本有效转化为我们能够交付给用户的产品质量。但这无疑是一项巨大的战略性押注，我们正专注于此，并希望确保我们所构建的基础，最终能为数十亿用户提供最佳产品。
Susan J. S. Li
Doug, on your second question about how we expect to finance the growing CapEx next year. We certainly expect that we will finance some large share of that ourselves, but we're also exploring ways to work with financial partners to co-develop data centers. We don't have any finalized transactions to announce, but we generally believe that there will be models here that will attract significant external financing to support large-scale data center projects that are developed using our ability to build world-class infrastructure while providing us with flexibility should our infrastructure requirements change over time. So we are exploring many different paths.
Doug，关于你第二个问题，即我们如何预计为明年不断增长的资本开支融资。我们当然预计会自筹相当大的一部分资金，但我们也在探索与金融合作伙伴合作，共同开发数据中心的方式。目前还没有可以宣布的最终交易，但我们普遍认为，这类模式会吸引大量外部融资来支持大型数据中心项目。借助我们建设世界级基础设施的能力，同时又能在基础设施需求随时间变化时保持灵活性。因此，我们正在探索多种不同的路径。
Operator
主持人
Your next question comes from the line of Justin Post with Bank of America.
接下来是美国银行的 Justin Post 提问。
Justin Post
I'll ask another one on infrastructure. Mark, your spend is now approaching some of the biggest hyperscalers out there. Do you think of all this capacity mostly for internal uses? Or do you think there's a way to share or even come up with a business model where leveraging that capacity for external uses?
我再问一个关于基础设施的问题。Mark，你们的支出现在已经接近全球最大的超大规模云厂商的水平。你认为这些算力主要还是用于内部需求？还是你认为会有机会对外共享，甚至发展出一种新的商业模式，将这部分算力外部化利用？
And then Susan, when you think about the ROI on this CapEx, I'm sure you have internal models, I'm sure you can't share all that, but how are you thinking about the ROI? And are you optimistic about the long-term returns?
另外，Susan，在你们考虑资本开支ROI时，我相信你们有内部模型，虽然你不能完全披露，但能否谈谈你们是如何看待ROI的？你们对长期回报是否乐观？
Susan J. S. Li
Justin, I can go ahead and take a crack at both of those. And obviously, Mark, you should feel free to weigh in.
Justin，这两个问题我都可以先回答。当然，Mark也可以补充。
Right now, we are focused on ensuring that we have enough capacity for our internal use cases, which includes both all of the core AI work that we do to support the recommendation engine work on the organic content side to support all the ads ranking and recommendation work. And then, of course, to make sure that we are building the training capacity that we think we need in order to build frontier AI models. And to make sure that we're preparing ourselves for the types of inference use cases that we think might -- that we might have ahead of us as we eventually focus not only on developing frontier models, but also how we can expand into the kinds of consumer use cases that we think will be hopefully widely useful and engaging for our users.
目前，我们的重点是确保内部用例的算力需求能够被满足。这包括：所有支持推荐引擎的核心AI工作、广告排序和推荐系统相关的工作。当然，还有建设我们认为所需的训练算力，以便研发前沿AI模型。同时也要为未来的推理场景做好准备——因为我们不仅要专注于研发前沿模型，还希望能够扩展到更多面向消费者的用例，这些应用有望广泛实用并增强用户参与度。
So at present, we're not really thinking about external use cases on the infrastructure, but it's a good question.
因此，目前我们并没有真正考虑将基础设施用于外部场景，但这是个好问题。
大量算力用于推荐引擎，有可能只此一家。
On your second question, which is really around the sort of ROI on CapEx, there are a couple of things. So again, on the core AI side, we continue to see strong ROI. Our ability to measure that is quite good, and we feel sort of very good about the rigorous measurement and returns that we see there.
关于你第二个问题，也就是资本开支的ROI，有几个方面。首先，在核心AI领域，我们持续看到强劲的ROI。我们具备较强的测量能力，对这些严格测量所展现的回报感到非常有信心。
On the genAI side, we are clearly much, much earlier on the return curve and we don't expect that the genAI work is going to be a meaningful driver of revenue this year or next year. But we remain generally very optimistic about the monetization opportunities that will open up, and Mark spoke to them in his script, the sort of five pillars, so I won't repeat them here. And we think that over the medium- to long-term time frame, those are opportunities that are very adjacent and intuitive for where -- in terms of where our business is today, why they would be big opportunities for us and that there will be sort of big markets attached to each of them.
在生成式AI方面，我们显然还处于回报曲线的非常早期阶段，我们并不预计今年或明年生成式AI会成为收入的显著驱动因素。但我们依然对其未来的变现机会保持非常乐观。Mark在发言稿中提到过相关的五大支柱方向，我这里不再重复。我们认为，在中长期内，这些方向与我们现有业务高度相关且直观合理，并且每个方向都将对应庞大的市场机会。
So we, again, are also, I would say -- the last thing I would add here is we are building the infrastructure with fungibility in mind. Obviously, there are a lot of things that you have to build up front in terms of the data center shells, the networking infrastructure, et cetera. But we will be ordering servers, which ultimately will be the biggest bulk of CapEx spend as we need them and when we need them and making sort of the best decisions at those times in terms of figuring out where the capacity will go to use.
最后我还要补充一点：我们在建设基础设施时充分考虑了灵活性。显然，像数据中心外壳、网络基础设施等，需要提前建设。但最终占资本开支最大部分的是服务器，我们会在需要时分批采购，并在每次采购时作出最佳决策，以确定这些算力的分配和使用方向。
Operator
主持人
Your next question comes from the line of Mark Shmulik with Bernstein.
接下来是来自伯恩斯坦的 Mark Shmulik 提问。
Mark Elliott Shmulik
Mark, as you go after the superintelligence vision, especially for those of us on the outside, what are kind of some of the markers or KPIs that you're tracking on whether you're on track and making progress? Is it really against kind of those five pillars you outlined above? Or should we be thinking more broadly?
Mark，当你们推进超级智能的愿景时，尤其是对于我们这些局外人来说，应该关注哪些标志或关键绩效指标（KPI），以判断你们是否在正确的轨道上取得进展？这些是否主要还是基于你之前提到的五大支柱，还是我们应该更广泛地去看待？
And Susan, obviously AI delivering great ROI today, all those investments and also building towards kind of longer-term goals, just curious, has there just been any change or adjustment to how you think about the relationship between revenues or core business performance and the cadence of investment?
另外，Susan，现在AI显然已经带来了很高的ROI，这些投资也在为长期目标做准备。我想知道，你们是否对收入或核心业务表现与投资节奏之间的关系有过任何新的思考或调整？
Mark Elliot Zuckerberg
Yes, in terms of what to look at, I mean, what I'm going to look at internally, the quality of the people on the teams, the quality of the models that we're producing, the rate of improvement of our other AI systems across the company and the extent to which the leading kind of foundation models that we're building contribute to improving all of the other AI systems and kind of everything that we're doing around the company.
好的，就衡量指标而言，我在内部主要关注的是：团队人才的质量、我们产出模型的质量、公司其他AI系统的改进速度，以及我们所构建的领先基础模型在多大程度上能够提升其他AI系统，以及整体推动公司各方面的进展。
Then I think you just get into our standard product and business playbook, which is translating that technology into new products, which will first scale to billions of people and then over time, we will monetize. But I think that there's going to be some lag in that, right? And that, I think, is kind of always the way that we work is, whether we're building some new social product or this, something like Meta AI or a new product around this, we're going to work on getting to leading scale, building the highest quality product, focused on that for a few years. And then once we're really confident in that position, then we'll focus on ramping up the business around it.
接着，这就进入到我们标准的产品和商业运作模式：把技术转化为新产品，首先实现规模化，覆盖数十亿用户，然后再逐步进行商业化。我认为这里面会存在一定的滞后，这也是我们一贯的做法。无论是构建新的社交产品，还是像 Meta AI 这样的新型产品，我们的首要目标都是实现领先规模，并在数年间专注于打造最高质量的产品。一旦我们对这个定位有了足够的信心，就会转而专注于围绕它发展商业化。
So it's -- I mean, going back to the last question a little bit, it's sort of when you compare this business to some of the cloud businesses, it's like we do have this delay where we focus on building research and then doing research and then ramping consumer products, and it often does take some period of time before we really are ramping up the business around it. I think that's kind of a known property of our business and the cycle around it.
所以，回到上一个问题的角度来看，如果把我们的业务和一些云业务进行比较，可以看到我们确实存在这种节奏差异：我们会先专注于研究，再进入研发阶段，然后才扩展到消费级产品。这通常需要一定的时间，才能真正开始推动围绕它的商业化。我认为这是我们业务性质和周期的一个固有特征。
But I guess, on the flip side, we believe that if you are building superintelligence, you should use all of your GPUs to make it so that you're serving your customers really well with that. And we think that there's going to be a much higher return than we can do by generating that directly rather than just kind of renting or leasing out the infrastructure at other companies.
不过，另一方面，我们相信，如果你在打造超级智能，就应该把所有GPU都用在为用户提供最佳服务上。我们认为，这样产生的回报远远高于把算力租赁或外包给其他公司的方式。
相比于云计算，社交是一个差异化的产品，理论上更有前途。
Susan J. S. Li
On the second part of your question, we've said in the past that our primary focus from a profitability perspective is driving consolidated operating profit growth over time. And it won't be linear. In some years, we'll deliver above-average profit growth. And in years where we're making big investments, I think we will see that impact the amount of operating profit growth that we can deliver.
关于你问题的第二部分，我们过去已经说过，从盈利角度来看，我们的首要目标是推动合并后的运营利润长期增长。而这不会是线性的。在某些年份，我们会实现高于平均水平的利润增长；但在大规模投资的年份，我们的运营利润增长幅度将会受到一定影响。
And at the moment, we see a lot of attractive investment opportunities that we believe are going to set us up to deliver compelling profit growth in the coming years for all of our investors. And so we're focused on constraining investments elsewhere as we pursue those investments. But we really believe that this is a time for us to really make investments in the future of AI as I think it will open up both new opportunities for us in addition to strengthen our core business.
目前，我们看到了很多有吸引力的投资机会，我们相信这些投资将为我们在未来几年向所有投资者交付可观的利润增长打下基础。因此，我们在追求这些投资的同时，也会对其他领域的投资进行约束。但我们真心认为，现在正是投资AI未来的关键时机，因为它不仅会为我们带来新的机会，还会进一步强化我们的核心业务。
Operator
主持人
Your next question comes from the line of Ron Josey with Citi.
接下来是花旗银行的 Ron Josey 提问。
Ronald Victor Josey
Mark, I wanted to ask you on Meta AI, and I think you talked about in the call just growing engagement overall, particularly on WhatsApp. And now we have 1 billion users on the platform and the focus is now on driving personalization. So I want to understand a little bit more how these next-gen models can help drive adoption here, particularly with Behemoth coming online at some point.
Mark，我想问一下关于Meta AI的问题。我记得你在电话会上提到过整体用户参与度的提升，尤其是在WhatsApp上。目前该平台已有10亿用户，重点现在是推动个性化。我想更深入了解下一代模型如何在这里推动用户采用，尤其是未来Behemoth模型上线时的情况。
And then as people are using that Meta AI with WhatsApp, thoughts on search and queries and potentially monetizing that.
另外，当用户在WhatsApp中使用Meta AI时，关于搜索、查询以及潜在的变现方式，你们是如何考虑的？
Mark Elliot Zuckerberg
Yes, I'm not going to get super deep into the road map on this, but the basic -- we do see that as we continue improving the models behind Meta AI and post training and just engagement increases and as we swap in the updated models, when we go from Llama 4 to Llama 4.1 when we have that, we expect that just -- the models are inherently pretty general. So it's -- yes, you focus on specific areas, but in general, it just sort of gets better at a lot of different things that people want to ask it or want to do with it. And I think with each version, both like what we're doing on a week-to-week basis in terms of continuing to train it, and when we drop kind of new generations or big dot releases of each generation, that will improve engagement, too.
是的，我不会在这里深入展开具体的路线图，但基本情况是：我们发现，随着Meta AI背后模型的不断改进、持续训练和用户互动的增加，以及随着我们替换新版本模型，比如从Llama 4升级到Llama 4.1时，我们预计整体体验会有显著提升。因为这些模型本身具有很强的通用性。虽然我们会在特定领域进行优化，但总体上，它会在用户想问的问题或想完成的任务上变得越来越好。我认为，每次迭代，无论是我们每周持续训练所带来的提升，还是新一代或大版本的发布，都会推动用户参与度的进一步增长。
社交软件记录了每个人的重要记忆，可能是很重要的上下文。
So we're focused on that. I'm not going to go into the specific research areas or capabilities that we're planning on dropping in the future. But obviously, I'm pretty excited about it.
所以我们目前主要专注于这方面。我不会详细谈论未来计划推出的具体研究领域或功能，但显然，我对此感到非常兴奋。
Operator
主持人
The last question comes from the line of use of Youssef Squali with Truist Securities.
最后一个问题来自 Truist Securities 的 Youssef Squali。
Youssef Houssaini Squali
I have two. So Mark, the Ray-Ban initiative has been a \[ hallmark ] for you guys so far. Where are we on the development of glasses? And has that new computational platform that you've talked about in the past, is it moving faster or slower than you thought? And as you leverage Meta AI, do you believe glasses ultimately replace smartphones? Or do you need the new form factor that's AI first?
我有两个问题。Mark，Ray-Ban 项目到目前为止一直是你们的重要里程碑。请问眼镜的开发进展到哪一步了？你过去提到过的新计算平台，目前的推进速度是比你预期更快还是更慢？另外，随着你们利用 Meta AI，你是否认为眼镜最终会取代智能手机？还是需要一种全新的、以AI为核心的新形态设备？
And then, Susan, just quickly, how do you guys see SBC progressing over the next couple of years? Is it fair to assume it will grow materially faster than the revenue and OpEx? And how do you minimize shareholder dilution?
另外，Susan，请简单谈一下你们对未来几年基于股份的薪酬（SBC）的看法。是否可以认为它的增长速度将显著快于收入和运营开支？你们又如何尽量减少股东稀释？
Mark Elliot Zuckerberg
Yes, I can talk a bit about the glasses. Yes, I mean, I'm very excited about the progress that we're making. I think both the Ray-Ban Metas and I'm very excited about the Oakley Meta, the HSTNs too. And other things that we have planned. Yes, I mean, this product category is clearly doing quite well. And I think it's good for a lot of things. It is stylish eyewear, so people like wearing them just as glasses. It has a bunch of interesting functionality. And then the use of Meta AI in them just continues to grow, and the percent of people who are using it for that on a daily basis is increasing, and that's all good to see.
好的，我可以谈一下眼镜项目。我对我们目前取得的进展感到非常兴奋。不仅是 Ray-Ban Metas，我也对 Oakley Meta 和 HSTNs 感到很期待，还有我们计划中的其他产品。总体来说，这一产品类别的表现相当不错。一方面，它是时尚的眼镜，人们单纯作为眼镜佩戴就很喜欢；另一方面，它还具备很多有趣的功能。而且 Meta AI 在其中的使用持续增长，每天使用 AI 功能的人群比例不断提高，这是一个非常积极的信号。
I mean, I continue to think that glasses are basically going to be the ideal form factor for AI because you can let an AI see what you see throughout the day, hear what you hear, talk to you. Once you get a display in there, whether it's the kind of wide holographic field of view like we showed with Orion or just a smaller display that might be good for displaying some information, and that's also going to unlock a lot of value where you can just interact with an AI system throughout the day in this multimodal way. It can see the content around you, it can generate a UI for you, show you information and be helpful.
我依然认为，眼镜将是AI的理想形态设备，因为它能让AI看到你所看到的、听到你所听到的，并与您对话。一旦在眼镜中加入显示功能，不管是像我们在 Orion 演示中展示的宽幅全息视野，还是适合显示部分信息的小型屏幕，都能释放巨大的价值。这样，你可以以多模态的方式全天与AI系统互动：它可以识别你周围的内容、生成UI界面、展示信息并提供帮助。
I mean, I personally think that just like if -- I wear contact lenses, I feel like if I didn't have my vision corrected, I'd be sort of at a cognitive disadvantage going through the world. And I think in the future, if you don't have glasses that have AI or some way to interact with AI, I think you're kind of similarly, probably be at a pretty significant cognitive disadvantage compared to other people and who you're working with, or competing against.
就我个人而言，我戴隐形眼镜，如果视力没有得到矫正，我会觉得在日常生活中处于认知劣势。我认为未来也是如此：如果你没有一副带有AI功能的眼镜，或者缺少与AI互动的方式，你很可能会在认知上相对于他人——无论是同事还是竞争对手——处于明显的劣势。
非常好的解释。
So I think that this is a pretty fundamental form factor. There are a lot of different versions of it. Right now, we're building ones that I think are stylish, but aren't focused on the display. I think there's a whole set of different things to explore with displays. This is kind of what we've been maxing out with Reality Labs over the last 5 to 10 years is basically doing the research on all of these different things.
因此，我认为眼镜是一个非常基础性的形态设备。这其中会有很多不同版本。目前我们在打造一些我认为时尚的眼镜，但并不专注于显示功能。我认为在显示方面还有一整套可以探索的方向。这基本上就是我们在过去5到10年中通过Reality Labs一直在深入研究的课题。
And it's a -- I don't know, 10 years ago, I would have -- like the other thing that's awesome about glasses is, they are going to be the ideal way to blend the physical and digital worlds together. So the whole metaverse vision, I think, is going to end up being extremely important, too, and AI is going to accelerate that, too.
另外，眼镜的另一个令人兴奋的点是，它将成为融合物理世界和数字世界的理想方式。所以我认为，整个元宇宙的愿景最终也将变得极为重要，而AI会加速这一进程。
It -- just that if you'd asked me 5 years ago, whether we'd have kind of holograms that created immersive experiences or superintelligence first, I think most people would have thought that you'd get the holograms first. And it's this interesting kind of quirk of the tech industry that I think we're going to end up having really strong AI first. But because we've been investing in this, I think we're just several years ahead on building out glasses. And I think that that's something that we're excited to keep on investing in heavily because I think it's going to be a really important part of the future.
如果你在5年前问我，我们会先拥有沉浸式全息体验，还是先拥有超级智能，我想大多数人都会认为全息影像会先实现。但科技行业就是这样奇特，我认为我们最终会先拥有强大的AI。不过，正因为我们一直在投资眼镜研发，我认为我们在眼镜领域已经领先了好几年。我对此感到非常兴奋，并且会继续加大投入，因为我认为眼镜将在未来发挥极其重要的作用。
Kenneth J. Dorell
Youssef, we didn't quite get your second question, do you mind just repeating it?
Youssef，我们没有完全听清你的第二个问题，可以再重复一下吗？
Youssef Houssaini Squali
Sure. Just as you look at the spend on stock-based compensation over the next couple of years with all these hires, I'm assuming that we're going to see that materially -- or grow materially faster maybe than revenue and OpEx. And I just want to know how -- what you guys are doing to plan to minimize shareholder dilution. Is it mostly buybacks or anything else?
好的。在未来几年，随着你们不断招聘，我预计基于股票的薪酬（SBC）支出将显著增长，可能会比收入和运营开支增长更快。我想知道，你们打算如何尽量减少股东稀释？主要是通过股票回购吗？还是有其他措施？
Susan J. S. Li
Thanks, Youssef. So I mean, the impact of the sort of increased compensation costs, including SBC, of our AI hires this year is reflected in the revised 2025 expense outlook and in the -- the comments I made about sort of 2026 expense outlook. Those are obviously a big driver of 2026 expense growth as we recognize the full year of compensation for the additional talent we're bringing on.
谢谢你，Youssef。今年因招聘AI人才而增加的薪酬成本，包括SBC，已经反映在我们修订后的2025年费用展望中，以及我之前关于2026年费用展望的评论中。显然，这些将是2026年费用增长的重要驱动因素，因为我们要确认新增人才的全年薪酬。
Having said that, so we factored that into our sort of expense outlook. Having said that, we certainly -- we are very focused on making sure on keeping an eye on dilution. And we generally believe that our strong financial position is going to allow us to support these investments while continuing to repurchase shares as part of the sort of buyback program that offsets equity compensation and as well as provide quarterly cash dividend distributions to our investors.
话虽如此，我们已经把这一点纳入了费用展望。但我们也非常关注股东稀释的问题。我们普遍认为，凭借强劲的财务状况，我们能够在支持这些投资的同时，继续通过股票回购来对冲股权薪酬带来的影响，并继续向投资者提供季度现金分红。
Kenneth J. Dorell
Great. Thank you, everyone, for joining us today. We look forward to speaking with you again soon.
好的。感谢大家今天的参与，我们期待很快再次与各位交流。
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