Meta Platforms, Inc. (META) 2026 Q3 法說會逐字稿

Good afternoon. My name is Krista, and I'll be your conference operator today. At this time, I would like to welcome everyone to Meta's third-quarter 2026 earnings conference call. (Operator Instructions) We ask that you limit yourself to one question, and this call will be recorded.

下午好。我叫 Krista，今天將擔任本次電話會議的接線員。此刻，我想歡迎各位參加 Meta 2026 年第三季財報電話會議。（接線員指示）我們請各位每人僅限提問一個問題，本通話將被錄音。

Thank you very much. Rob Bevegni, Meta's Director of Investor Relations, you may begin.

非常感謝。Meta 投資人關係總監 Rob Bevegni，您可以開始。

Thank you. Good afternoon and welcome to Meta Platform's third-quarter 2026 earnings conference call. Joining me today to discuss our results are Mark Zuckerberg, CEO; and Susan Li, CFO. Our remarks today will include forward-looking statements, which are based on assumptions as of today.

謝謝。下午好，歡迎參加 Meta Platforms 2026 年第三季財報電話會議。今天與我一同討論業績的有執行長 Mark Zuckerberg，以及財務長 Susan Li。我們今天的發言將包含前瞻性陳述，係基於截至今日的假設。

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.

實際結果可能因各種因素而與前述內容存在重大差異，包括今日財報新聞稿以及我們向美國證券交易委員會（SEC）提交的 10-Q 季度報告中所列示的因素。我們不承擔更新任何前瞻性陳述的義務。

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@meta.com.

在本次電話會議中，我們將同時呈現 GAAP 以及若干非 GAAP 財務衡量指標。GAAP 與非 GAAP 指標之間的調節表已包含於今日的財報新聞稿中。財報新聞稿及隨附的投資人簡報可於我們網站 investor@meta.com 取得。

And now, I'd like to turn the call over to Mark.

接下來，我想把電話交給 Mark。

All right, everyone. Thanks for joining today. This has been a busy and exciting few months. Our family of apps is now used by 3.64 billion people each day, and we are seeing all-time highs in engagement on both Facebook and Instagram, driven by strong growth in video. Threads has now overtaken X in monthly actives and continues to grow quickly. WhatsApp is hitting all-time highs in messaging and is becoming an increasingly important platform for agents as well.

好的，各位。感謝今天加入。過去幾個月既忙碌又令人振奮。我們的應用程式家族目前每天有 36.4 億人使用；在影片強勁成長的帶動下，Facebook 與 Instagram 的互動度都創下歷史新高。Threads 的月活躍用戶數已超越 X，且持續快速成長。WhatsApp 的訊息量也創下歷史新高，並且正成為代理人（agents）日益重要的平台。

In the last few months, we have had several major milestones towards our goal of delivering personal superintelligence to everyone. We had one of our most successful launches ever with the Muse personal agent. We shipped Muse Wonder as our first frontier model, and we shipped several new glasses and gadgets with Muse integration, including coming soon to our new audio glasses.

在過去幾個月，我們朝著「為每個人提供個人超級智慧」的目標，達成了數個重要里程碑。Muse 個人代理人的推出，是我們歷來最成功的產品發表之一。我們推出了 Muse Wonder，作為我們第一個前沿模型；同時也推出了多款整合 Muse 的新眼鏡與裝置，其中也包括即將推出、整合於我們新款音訊眼鏡的功能。

We've been discussing our vision for personal superintelligence for more than a year now. We want to help every person have an extremely capable personal agent that understands their goals and can help you achieve them and improve your life in whatever ways you want, whether that's improving your relationships, helping you save time, save money, build a business, create new things, or anything else that you can dream of.

我們談論個人超級智慧的願景已經超過一年。我們希望幫助每個人都擁有一個能力極強的個人代理人，能理解他們的目標並協助你達成，並以你想要的任何方式改善生活——無論是改善人際關係、幫你節省時間、節省金錢、建立事業、創造新事物，或任何你能想像的事情。

Muse is the product form of this vision. So now we have the foundational technology in place to deliver this. There is still a lot of work ahead, but our initial position is very strong. In just a month and a half, more than 10 million people in the US and Canada have set up Muse personal agents. Growth continues to be strong, and we have been number one in the App Store almost every day.

Muse 是這個願景的產品化形式。因此，我們現在已具備交付這一切的基礎技術。前方仍有大量工作要做，但我們的起步位置非常強勁。僅在一個半月內，美國與加拿大已有超過 1,000 萬人建立了 Muse 個人代理人。成長仍然強勁，我們幾乎每天都在 App Store 排名第一。

Engagement and retention are also off to a strong start. About 25% of people who have set up Muse use it on any given day. For our earliest adopters, the longer that they use Muse, the better that retention seems to get. So to put this in perspective, this is more than twice the level that Thread started at or where we believe that other AI apps started at as well.

互動與留存也有一個強勁的開局。在已建立 Muse 的人之中，約有 25% 在任一給定日會使用它。對於最早期的採用者而言，他們使用 Muse 的時間越長，留存似乎越好。因此，從這個角度來看，這個水準是 Threads 起步時的兩倍以上，也高於我們認為其他 AI 應用程式的起步水準。

The most common use case for Muse is shopping. With more than a quarter of people who are using Muse engaging in this with an average purchase size of over $200, Plaid told us that they hadn't seen activity like they're seeing with their connector on any other service before. And in the first week, we had to work with Stripe to raise credit limits since the volumes were above what any of us expected.

Muse 最常見的使用情境是購物。在使用 Muse 的人之中，超過四分之一會進行此類互動，且平均客單價超過 200 美元；Plaid 告訴我們，他們從未在任何其他服務上，看到其連接器出現像現在這樣的活動量。而在第一週，我們就必須與 Stripe 合作提高信用額度，因為交易量超出我們任何一方的預期。

Beyond shopping, the most common connectors are for personal productivity and connecting Muse to your other services like e-mail and calendar. Now, this shows the importance of the Muse Secure VM that we've built to provide state-of-the-art privacy and security. And we are looking forward to following up soon with the Muse Confidential VM, which will make it even Meta cannot see your content.

除了購物之外，最常見的連接器是個人生產力相關，以及將 Muse 連接到你其他服務（如電子郵件與行事曆）。這也顯示出我們所打造的 Muse Secure VM 的重要性，它提供最先進的隱私與安全。我們也期待很快推出 Muse Confidential VM，屆時甚至連 Meta 都無法看到你的內容。

We've also seen that Muse Wonder improves quality, engagement and retention further, which suggests that as we continue to improve intelligence, Muse will perform better and better over time. Now that Muse has clear product market fit, we are entering a new phase and a more operational phase that is focused on scaling it. The goals for this next phase play to many of Meta's strengths. We need to do three things; scale the product, grow revenue and optimize compute costs.

我們也看到 Muse Wonder 進一步提升了品質、互動與留存，這顯示隨著我們持續提升智慧程度，Muse 的表現將隨時間越來越好。現在 Muse 已明確達到產品市場契合（product-market fit），我們正進入一個新階段——更偏營運的階段——聚焦於擴大規模。下一階段的目標也符合 Meta 的多項強項。我們需要做三件事：擴大產品規模、提升營收、並最佳化算力成本。

We expect to grow Muse to serve billions of people. This is both our mission and our strategy. It's our mission in that we believe in putting the power of personal superintelligence in everyone's hands. We believe that that is the path to ensuring a positive future for everyone with individual empowerment. Empowerment is the source of prosperity and balance of power is the foundation for safety.

我們預期將把 Muse 擴展到服務數十億人。這既是我們的使命，也是我們的策略。這是我們的使命，因為我們相信應將個人超級智慧的力量交到每個人手中。我們相信，這是確保每個人都能擁有正向未來、並實現個人賦權的道路。賦權是繁榮的來源，而權力平衡是安全的基礎。

On a values level, we believe that delivering this capability widely is the best thing that we can be doing. This is also our strategy because we think that billions of Muses in a network at scale will be able to get more done for people and businesses by working together. So we'd like to create a large-scale Muse network as quickly as possible. From a business perspective, the average revenue per American user for our existing Muse users -- is sorry -- for our existing family of apps users is several hundreds of dollars annually and we expect that Muse will reach an even higher level over time due to the amount of commerce that we already see taking place.

在價值觀層面，我們相信廣泛交付這項能力，是我們能做的最正確的事。這同時也是我們的策略，因為我們認為在規模化的網路中，數十億個 Muse 能透過彼此協作，為個人與企業完成更多事情。因此，我們希望盡快建立一個大規模的 Muse 網路。從商業角度來看，我先前提到的平均營收——是抱歉——我們現有應用程式家族使用者的美國用戶平均營收，每年為數百美元；而我們預期 Muse 隨時間推進將達到更高水準，因為我們已看到大量商務活動正在發生。

This will take some time, but we're starting to work on this now. Our business model will have a few components. For most people, the product should be free and we will build commerce tools so we get paid a fee based on the transactions that we help facilitate. We expect this will be paid for by businesses. For people who want the most advanced models or to use extra tokens, they subscribe directly and pay.

這需要一些時間，但我們現在已開始著手推進。我們的商業模式將包含幾個組成部分。對大多數人而言，產品應該是免費的；我們將建立商務工具，並依據我們協助促成的交易收取費用。我們預期這將由企業端支付。對於想要使用最先進模型或使用額外 tokens 的人，他們將直接訂閱並付費。

For business owners who want additional features to use Muse to grow their businesses or for companies that want people to use Muse for work, they will be able to subscribe directly and pay as well. And for those who want Muse to help improve the personalization and quality of their content and ads across Meta, they will be able to connect to those experiences as well.

對於希望使用 Muse 來成長其業務、並需要額外功能的商家，或希望員工在工作中使用 Muse 的公司，他們也可以直接訂閱並付費。而對於希望 Muse 協助提升其在 Meta 各平台內容與廣告的個人化程度與品質的人，他們也能連接到這些體驗。

Just to clarify, the average revenue that I was talking about before is the family of apps revenue for our existing Muse users.

補充說明一下，我先前談到的平均營收，是指我們現有 Muse 使用者在應用程式家族上的營收。

On the compute side, we are building out the capacity to serve more than 1 billion people over the next few years. In the near term, Muse is very compute intensive to run, but we expect to improve its cost efficiency by more than 10x in the next year, which will enable it to be profitable once the revenue lines are at scale. If compute efficiency continues improving quickly for another few years, which we think is highly likely, then Muse will be highly profitable over multiple years.

在算力方面，我們正在擴建產能，以在未來幾年內服務超過 10 億人。短期內，Muse 的運行非常耗費算力，但我們預期在未來一年將其成本效率提升超過 10 倍，這將使其在營收規模化後能夠實現獲利。如果算力效率在接下來幾年仍持續快速提升——我們認為這非常可能——那麼 Muse 將在多年期間具備高度獲利能力。

In the near term, the strength of our core business enables us to scale the Muse network before then, and we believe that we are the best positioned company to pursue this strategy. One other note on compute economics is that since training is a large fixed cost, now that we have leading models, we want to serve as much high margin inference demand as possible. That is why we are building the Meta Enterprise platform led by CJ Desai.

短期內，我們核心業務的強勁表現使我們能在那之前擴大 Muse 網路的規模，而我們相信我們是最有利位置來推動這項策略的公司。關於算力經濟性的另一點是，由於訓練是一項龐大的固定成本，既然我們已擁有領先的模型，我們希望盡可能承接更多高毛利的推理需求。這也是為什麼我們正在打造由 CJ Desai 領導的 Meta Enterprise 平台。

Muse Wonder and even more advanced models that we're training can serve additional high margin services beyond the Muse network, including our API, Muse code, and other enterprise services. A fundamental feature of our business is that we have many good uses for this compute. It is difficult to forecast the exact growth rates for the Muse network, for our enterprise platform and for how Muse Wonder and beyond will accelerate our core business.

Muse Wonder 以及我們正在訓練的更先進模型，除了 Muse 網路之外，還能提供更多高毛利服務，包括我們的 API、Muse Code，以及其他企業服務。我們業務的一個根本特徵是：我們對這些算力有許多很好的用途。要精準預測 Muse 網路、我們的企業平台，以及 Muse Wonder 及後續模型將如何加速我們核心業務的確切成長率，是很困難的。

But through building up multiple ways to deploy these advanced models, we increase the chances that one or more of them significantly outperforms our expectations. Beyond serving other businesses, we have not yet found the limit of how effectively we can apply compute to accelerating our own core business. We have implemented an eval with Muse Wonder to improve how effectively it can autonomously improve our recommendations and ad systems.

但透過建立多種部署這些先進模型的方式，我們提高了其中一種或多種方式顯著超出我們預期的機率。除了服務其他企業之外，我們尚未找到能多有效地將算力用於加速我們自身核心業務的上限。我們已使用 Muse Wonder 實作一套評估（eval），以提升其自主改進我們推薦與廣告系統的效果。

As our upcoming models get even more advanced, I expect there (technical difficulty) rooms. And we're going to see an increasing rate of improvement in these systems.

隨著我們即將推出的模型變得更加先進，我預期那裡會有（技術難度）空間。而且我們將看到這些系統的改進速度持續提高。

All right, let's talk about the models now. Muse Wonder is state-of-the-art across many dimensions that matter for personal superintelligence. This validates the importance of training models ourselves to deliver the best experience. In addition to Muse, we have also seen that engagement per person in Meta AI has more than doubled since April when we started rolling out our new models.

好，現在來談談模型。Muse Wonder 在許多對個人超級智慧而言重要的面向上都達到最先進水準。這驗證了由我們自行訓練模型以提供最佳體驗的重要性。除了 Muse 之外，我們也看到自從四月開始推出新模型以來，Meta AI 的人均互動度已經增加了一倍以上。

While Muse Wonder has been our most important release. I've been very pleased with our pace of execution here. In the last few months, we've shipped Muse Spark 1.2 and 1.3, Muse Code to open weights models with Muse Glimmer and Muse Spark Open and also Muse Voice.

Muse Wonder 一直是我們最重要的發布。我對我們在這裡的執行速度感到非常滿意。在過去幾個月裡，我們推出了 Muse Spark 1.2 和 1.3、Muse Code（用於開放權重模型，包含 Muse Glimmer 與 Muse Spark Open），以及 Muse Voice。

Going forward with the field advancing quickly, we plan to focus on both pushing the frontier of intelligence and distilling those models into much smaller and more efficient product models that will be optimized for personal agents. My view is that we will be able to build super intelligence through scaling. So we are methodically working our way up the ladder there. We are already working on larger models after Muse Wonder, and they're going to be very impressive and capable. We are also working on new smaller models that are coming out soon that will deliver Muse Wonder level intelligence more efficiently.

展望未來，隨著領域快速進展，我們計畫同時專注於推進智慧的前沿，並將這些模型蒸餾成更小、更高效率的產品模型，以針對個人代理（personal agents）進行最佳化。我的看法是，我們將能透過擴展（scaling）來打造超級智慧。因此我們正有條不紊地沿著這個階梯向上推進。我們已在 Muse Wonder 之後著手更大型的模型，它們將會非常令人印象深刻且能力強大。我們也在開發新的更小型模型，將在不久後推出，能以更高效率提供接近 Muse Wonder 等級的智慧。

Moving on, our work on personal superintelligence is now also the focus of Reality Labs. Muse is coming to Meta Glasses starting next month, and that will be an important step towards this. People already love many features of the glasses already, music, calling, capturing moments, hearing assistance and more. But over time, we expect Muse and having your personal superintelligence with you throughout the day will be the most important part of the experience.

接下來，我們在個人超級智慧上的工作如今也成為 Reality Labs 的重點。Muse 將從下個月開始登上 Meta 眼鏡，這將是朝向此目標的重要一步。人們已經很喜歡眼鏡的許多功能，例如聽音樂、通話、捕捉精彩時刻、助聽等。但隨著時間推移，我們預期 Muse，以及你整天隨身帶著的個人超級智慧，將成為體驗中最重要的部分。

Muse is also central to the business model for the glasses. Again, our mission and strategy are to serve everyone here. We believe in putting the power of this technology in everyone's hands. So we have priced our devices not to make a large profit on the hardware, but to build a large software and super intelligence business on top of them over time.

Muse 也是眼鏡商業模式的核心。再次強調，我們的使命與策略是服務所有人。我們相信應把這項技術的力量交到每個人手中。因此，我們為裝置定價並非為了在硬體上取得高額利潤，而是為了隨時間在其上建立龐大的軟體與超級智慧業務。

Glasses sales continue to grow rapidly. And now with Muse, we expect that paid subscriptions will increase and that this business will begin improving meaningfully from here. I also shared at Connect that we are changing our approach to virtual reality to only shift new devices when we have major breakthroughs like we had with the Meta VR glasses this year, which of course are the first VR experience ever in a pair of glasses.

眼鏡銷售持續快速成長。而現在有了 Muse，我們預期付費訂閱將增加，這項業務也將從此開始出現有意義的改善。我也在 Connect 上分享過，我們正在改變對虛擬實境的做法：只有在出現重大突破時才會推出新裝置，就像我們今年推出的 Meta VR 眼鏡一樣——那當然是史上第一次在一副眼鏡中提供 VR 體驗。

I continue to believe that the path to delivering holographic experience of bringing together the physical and digital worlds in everyday glasses will come through VR first. But we will pace this aspect of our investment more to focus on delivering personal superintelligence first.

我仍然相信，要在日常眼鏡中提供把實體與數位世界融合在一起的全像（holographic）體驗，其路徑會先從 VR 開始。但我們會更調整這部分投資的節奏，以優先聚焦於先交付個人超級智慧。

So with these factors combined, we expect that the P&L of Reality Labs to improve from here with operating loss coming down to around $15 billion next year and trending towards profitability from there.

因此，綜合這些因素，我們預期 Reality Labs 的損益表（P&L）將從此開始改善，營運虧損在明年降至約 150 億美元，並從那之後朝向獲利趨勢發展。

Before we conclude. I want to spend a moment on the sheer velocity that we are seeing. An important part of our approach has always been to move fast so we can learn quickly and serve people better at scale, but recently things have accelerated. In the last year, we shipped Edits. Edits it has already passed 50 million actives. New apps like Forum and Cellar were built by small teams and are scaling quickly to serve power users. Muse went from an idea on a whiteboard to a successful product in just about eight months.

在我們結束之前。我想花點時間談談我們所看到的驚人速度。我們的方法中一個重要部分一直是快速行動，以便快速學習並以規模更好地服務人們，但最近事情加速了。在過去一年，我們推出了 Edits。Edits 的活躍用戶已經超過 5,000 萬。像 Forum 和 Cellar 這樣的新應用由小型團隊打造，並正快速擴張以服務重度使用者。Muse 從白板上的一個想法到成功的產品，只用了大約八個月。

And we're about to ship Muse Charm, which will have gone from concept to a hardware device in people's pockets in less than a year.

而我們即將推出 Muse Charm，它將在不到一年的時間內，從概念變成一款放進人們口袋裡的硬體裝置。

I am proud of what we are building. People have all kinds of different opinions about the future, but at Meta, we believe that the future is for everyone and that putting power in people's hands is how we get there. I think that this matters. There needs to be a company out there that represents these ideas. But this isn't just about ideas, it's also about execution. So I am grateful for everyone who is working so hard to deliver all of this to billions of people around the world.

我為我們正在打造的一切感到自豪。人們對未來有各式各樣的看法，但在 Meta，我們相信未來屬於每一個人，而把力量交到人們手中就是我們抵達那裡的方式。我認為這很重要。需要有一家公司能代表這些理念。但這不只是理念，也關乎執行。因此，我感謝每一位如此努力工作、把這一切帶給全球數十億人的同仁。

And as always, thank you to everyone who was on this journey with us, and now here's Susan.

也一如既往，感謝所有一路與我們同行的人，接下來交給 Susan。

Thanks, Mark, and good afternoon, everyone. Let's begin with our segment results. All comparisons are on a year-over-year basis unless otherwise noted. Q3 total Family of Apps revenue was $64.2 billion, up 26%. Q3 Family of Apps ad revenue was $63.1 billion, up 26% on both a reported and constant currency basis.

謝謝你，Mark，各位下午好。我們先從各業務分部的業績開始。除非另有說明，所有比較皆以年對年為基礎。第三季（Q3）Family of Apps 總營收為 642 億美元，年增 26%。第三季 Family of Apps 廣告營收為 631 億美元，無論按報告口徑或固定匯率口徑計算，皆年增 26%。

In Q3, the total number of ad impressions served across our services increased 10%. Impression growth was healthy across all regions, driven by growth in engagement and users, as well as ad load optimizations. The global average price per ad increased 14% year over year, driven by ad performance gains and improvements in macro conditions relative to Q3 of last year. This was partially offset by strong impression growth, particularly from lower monetizing surfaces and regions.

在第三季，我們各項服務投放的廣告曝光總量增加了 10%。在互動度與用戶成長，以及廣告載入量（ad load）最佳化的帶動下，各地區的曝光成長都很健康。全球平均每則廣告價格年增 14%，主要由廣告成效提升，以及相較去年第三季宏觀環境改善所帶動。這部分被強勁的曝光成長所部分抵銷，尤其是來自變現能力較低的版位與地區。

Family of Apps other revenue was $1.1 billion and grew 59%, driven primarily by WhatsApp paid messaging and subscriptions revenue. Within our Reality Lab segment, Q3 revenue was $443 million, down 6% due to lower Quest headset sales, which were partially offset by continued strong growth in AI glasses revenue.

Family of Apps 其他營收為 11 億美元，年增 59%，主要由 WhatsApp 付費訊息與訂閱營收帶動。在我們的 Reality Labs 分部中，第三季營收為 4.43 億美元，年減 6%，原因是 Quest 頭戴式裝置銷售較低；但這部分被 AI 眼鏡營收持續強勁成長所部分抵銷。

Moving now to our consolidated results. Q3 total revenue was $64.6 billion, up 26% on both a reported and constant currency basis. Q3 total expenses were $51.6 billion, up 68% compared to last year and included a $9.9 billion charge related to the August 2026 multi-state attorneys general agreement. Year-over-year growth was primarily driven by legal-related costs, infrastructure costs and third-party AI token costs.

現在轉到我們的合併業績。第三季總營收為646億美元，以申報口徑及固定匯率口徑計算皆年增26%。第三季總費用為516億美元，較去年增加68%，其中包含與2026年8月多州檢察長協議相關的99億美元費用。年對年成長主要由法律相關成本、基礎設施成本以及第三方AI token成本所帶動。

The growth in infrastructure cost was driven by higher third-party cloud spend, depreciation and data center operating costs. We ended Q3 with over 66,000 employees, down 12% from Q2 following the May 2026 headcount reduction. Third quarter GAAP operating income was $13 billion, representing a 37% decline year over year and a 20% operating margin. Excluding the Q3 legal charges related to the aforementioned legal settlement, our third quarter operating income would have increased 11% year over year.

基礎設施成本的成長主要由較高的第三方雲端支出、折舊以及資料中心營運成本所驅動。第三季末員工人數超過66,000人，因2026年5月裁員而較第二季下降12%。第三季GAAP營業利益為130億美元，年減37%，營業利益率為20%。若排除第三季與前述法律和解相關的法律費用，我們第三季營業利益將年增11%。

Our tax rate for the quarter was 24%, above our outlook range, primarily driven by the non-deductible portion of legal expenses. Net income was $9.9 billion or $3.83 per share. Capital expenditures, including principal payments on finance leases, were $34.9 billion driven by investments in servers, data centers, and network infrastructure. Free cash flow was negative $2.1 billion. We ended the quarter with $82.4 billion in cash and marketable securities and $83.7 billion in debt.

本季稅率為24%，高於我們的展望區間，主要受法律費用中不可扣抵部分所影響。淨利為99億美元，或每股3.83美元。資本支出（包含融資租賃的本金償付）為349億美元，主要由伺服器、資料中心與網路基礎設施投資所帶動。自由現金流為負21億美元。季末現金及有價證券為824億美元，負債為837億美元。

Turning now to the business performance. 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.

接著談業務表現。影響我們營收表現的主要有兩項因素：我們為社群提供引人入勝體驗的能力，以及我們隨時間將這些互動有效變現的能力。

On the first, we continue to see significant gains from our content recommendation initiatives. On Instagram, global time spent per user reached an all-time high and grew double-digits year over year in Q3 with strength across both Reels and feed. On Facebook, Reel's time spent reached all-time highs both globally and in the US, with both growing double-digits year-over-year. Threads also continue to scale with time spent per user growing over 20% year-over-year.

在第一項方面，我們持續看到內容推薦計畫帶來顯著進展。在Instagram上，每位用戶的全球使用時間創下歷史新高，且第三季年增達雙位數，Reels與動態消息（feed）皆表現強勁。在Facebook上，Reels的使用時間在全球與美國皆創新高，且兩者年增皆達雙位數。Threads也持續擴張，每位用戶使用時間年增超過20%。

Engagement gains across our services continue to be driven by improvements we're making to the relevance, personalization, and timeliness of the content we recommend. Investments into our recommendations engine across retrieval and ranking have continued to yield positive results on Instagram and Facebook. For instance, on Instagram Reels, our relevance launches in Q3 increased Reels time spent by over 4%, driven in part by our upgraded model architecture that ranks sequences of Reels at a time instead of evaluating each Reel independently, as well as improvements we made to add richer watch time signals.

我們各項服務的互動提升，持續來自於我們在所推薦內容的相關性、個人化與即時性方面所做的改進。我們在檢索（retrieval）與排序（ranking）兩方面對推薦引擎的投資，持續在Instagram與Facebook上帶來正面成果。例如，在Instagram Reels上，我們第三季的相關性更新使Reels使用時間提升超過4%；部分原因在於我們升級的模型架構可一次對一串Reels進行排序，而非獨立評估每支Reel，並且我們也改進以加入更豐富的觀看時長訊號。

On Facebook feed and reels, we completed the global launch of a new generative retrieval architecture, which, inspired by LLMs, labels pieces of content with semantic representations and generates potential recommendations, helping our systems surface relevant new posts before they've accumulated significant engagement. This new architecture is now rolled out to roughly one quarter of unconnected feed views and half of Reels views and increased Reels watch time by 1%.

在Facebook動態消息與Reels上，我們完成了新一代生成式檢索架構的全球上線；該架構受LLM啟發，會以語意表徵為內容加上標籤並生成潛在推薦，協助系統在貼文累積大量互動之前，就能呈現相關的新貼文。此新架構目前已部署至約四分之一的非好友動態消息瀏覽量，以及一半的Reels瀏覽量，並使Reels觀看時長提升1%。

Our recommendations work is also helping us deliver fresher and more personalized content. Nearly 45% of (technical difficulty) -- processing costs by more than 80% across Instagram threads, Facebook and ads. Beyond improving quality, owning more of this stack gives us greater flexibility to develop models around the signals that matter the most for personalization.

我們的推薦工作也在幫助我們提供更新鮮且更個人化的內容。近45%的（技術困難）——在Instagram、Threads、Facebook與廣告等產品上，將處理成本降低了80%以上。除了提升品質之外，掌握這個技術堆疊的更多環節，也讓我們能更有彈性地圍繞對個人化最重要的訊號來開發模型。

Turning to the second driver of our revenue performance, increasing monetization efficiency. We see significant opportunity to continue improving performance for the businesses who use our services. Within our ad systems, we are continuing to drive performance gains as we deploy more predictive models that understand users more deeply and deliver ad experiences better aligned with their unique preferences while also making our infrastructure more efficient.

接著談影響我們營收表現的第二項驅動因素：提升變現效率。我們看到仍有很大的機會，持續為使用我們服務的企業提升成效。在我們的廣告系統中，隨著我們部署更多能更深入理解用戶、並提供更符合其獨特偏好的廣告體驗的預測模型，同時也讓基礎設施更有效率，我們持續推動成效提升。

Last quarter we introduced Meta Generative Recommender, which uses LLMs to reason across ad content and user preferences to predict the best ad for each person. In Q3, we launched this approach to generative retrieval on Facebook feed, driving a nearly 2% increase in conversions across targeted segments. In addition, we expanded our Gem model for ads ranking to additional surfaces, driving a 1% -- 1.7% increase in conversions for off-site conversion campaigns and a 9.6% increase in app ad conversions. And we continue to scale our retrieval systems efficiently.

上季我們推出Meta Generative Recommender，利用LLM在廣告內容與用戶偏好之間進行推理，以預測每個人最合適的廣告。第三季，我們在Facebook動態消息上推出這種生成式檢索方法，使特定目標區隔的轉換率提升近2%。此外，我們將用於廣告排序的Gem模型擴展到更多版位，使站外轉換活動的轉換率提升1%—1.7%，並使App廣告轉換提升9.6%。我們也持續有效率地擴大檢索系統的規模。

In Q3, improvements to Andromeda, such as scaling model complexity and throughput, increased conversions by 1.4% on Facebook. We're also leveraging AI to make it easier for businesses to manage campaigns, develop, creative, and act on performance opportunities. Meta AI Business Assistant is becoming a more proactive and capable partner for advertisers. We estimate that advertisers who adopted its recommendations drove almost 5% more conversions at the same cost per conversion and increased their advertising investment by 9% compared with similar non-adopters.

第三季，Andromeda的改進（例如提升模型複雜度與吞吐量）使Facebook上的轉換提升1.4%。我們也運用AI讓企業更容易管理活動、開發創意，並把握成效機會。Meta AI Business Assistant正成為對廣告主更主動且更有能力的合作夥伴。我們估計，採用其建議的廣告主在相同的每次轉換成本下，轉換量幾乎多了5%，且相較於類似但未採用者，其廣告投資增加了9%。

We are rolling out additional capabilities, including creative insights, stronger business contexts, and more agentic actions. These features will allow marketers to plan, create, and optimize campaigns as well as schedule tasks and alerts through a conversational experience with approvals and previews that keep them in control.

我們正在推出更多功能，包括創意洞察、更強的商業情境理解，以及更具代理式（agentic）的行動能力。這些功能將讓行銷人員能透過具備核准與預覽、並保持其掌控權的對話式體驗，來規劃、製作與最佳化活動，同時也能排程任務與提醒。

I'll share one example of how Meta AI Business Assistant is empowering our advertisers. Simply Organic Maple, a family-run maple syrup producer in Vermont, used Meta AI Business Assistant to improve its campaign messaging. After the business assistant recommended testing longer, more descriptive advertising copy, the business saw a 57% increase in purchases and a 36% reduction in cost per purchase. Its strongest revised ad delivered a 3x return on ad spend, a 52% improvement from the original.

我分享一個Meta AI Business Assistant如何賦能廣告主的例子。Simply Organic Maple是一家位於佛蒙特州的家族經營楓糖漿生產商，使用Meta AI Business Assistant來改善其活動訊息。在商業助理建議測試更長、更具描述性的廣告文案後，該企業的購買量提升57%，每次購買成本降低36%。其表現最強的修訂版廣告帶來3倍的廣告投資報酬率（ROAS），較原始版本提升52%。

Adoption of our generative AI ad creative tools also continues to scale. In Q3, nearly 10 million advertisers used at least one of these tools. Advertiser adoption of our video generation features grew 25% quarter over quarter, driven in part by ready-made videos that reduced generation time to just a few seconds from a single image upload. We're also expanding the opportunity at the intersection of creators and advertising.

我們的生成式AI廣告創意工具的採用也持續擴大。第三季，近1,000萬名廣告主使用了至少一項這些工具。廣告主對我們影片生成功能的採用率季增25%，部分受益於可直接套用的現成影片，讓生成時間從單張圖片上傳後縮短至僅需數秒。我們也在擴大創作者與廣告交會處的機會。

Partnership ads, which allow advertisers to run ads with creators, brands, and other businesses, continue to scale rapidly in Q3. Our Partnership Ads product grew over 97% year-over-year and surpassed $15 billion in annual revenue run rate. In Q3, we also completed the global rollout of Creator Marketing Hub to all advertisers, bringing creator discovery, content organization, and partnership ad activation into one place with more than 10 million creators now discoverable.

合作夥伴廣告（Partnership ads）讓廣告主能與創作者、品牌及其他企業共同投放廣告，第三季持續快速擴張。我們的Partnership Ads產品年增超過97%，年化營收運行率（run rate）突破150億美元。第三季，我們也完成Creator Marketing Hub對所有廣告主的全球推廣，將創作者探索、內容整理與合作夥伴廣告啟用整合到同一處，目前可被探索的創作者已超過1,000萬名。

We are integrating Meta AI Business Assistant into the Hub so advertisers can conversationally search for creators, identify content to use in partnership ads, and get guidance across their creator marketing workflows.

我們正把Meta AI Business Assistant整合進Hub，讓廣告主能以對話方式搜尋創作者、找出可用於合作夥伴廣告的內容，並在其創作者行銷工作流程中獲得指引。

Outside of ads, we are also building out additional ways to monetize engagement across our ecosystem. In September, we announced the global expansion of Meta One, our unified subscription service for consumers, creators and businesses. Meta One is rolling out gradually with more than 50 features across Instagram, Facebook, and WhatsApp, including Meta Business Agent and Meta AI, and has surpassed 15 million subscriptions and trials to date.

除了廣告之外，我們也在建立更多方式，將我們生態系中的互動加以變現。9月，我們宣布Meta One（面向消費者、創作者與企業的統一訂閱服務）在全球擴張。Meta One正逐步推出，涵蓋Instagram、Facebook與WhatsApp上的50多項功能，包括Meta Business Agent與Meta AI，迄今訂閱與試用數已超過1,500萬。

The core experience across our apps and Meta AI will remain free, while subscriptions offer more specialized capabilities and expanded AI usage. And beyond monetizing engagement across our existing services, we are building new experiences and revenue streams around consumer agents.

我們各款應用程式與 Meta AI 的核心體驗將維持免費，而訂閱方案則提供更專業的能力與更高的 AI 使用量。此外，除了在既有服務中將互動變現之外，我們也正在圍繞消費者代理（consumer agents）打造新的體驗與營收來源。

Mark highlighted the impressive early momentum with Muse. Users have found many reasons to use Muse, with the top three categories being shopping, personal productivity, and creativity. We're encouraged by the breadth of use cases, with shopping in particular being used by over 25% of Muse weekly actives.

Mark 強調了 Muse 令人印象深刻的早期動能。使用者已找到許多使用 Muse 的理由，前三大類別分別是購物、個人生產力與創意。我們對使用情境的廣度感到鼓舞，尤其是購物用途，已被超過 25% 的 Muse 每週活躍使用者採用。

While our near-term priority is to grow adoption and expand Muse's reach, we see multiple paths to monetization beginning with subscriptions. We also see a significant opportunity to extend Muse to small businesses. Based on a recent user survey, we estimate that at least 500 million self-identified small businesses use Meta's family of apps to reach customers and generate revenue. Muse could help these businesses acquire customers and operate more efficiently while helping people complete transactions.

雖然我們的短期優先事項是提升採用率並擴大 Muse 的觸及範圍，但我們看到多條變現路徑，其中以訂閱為起點。我們也看到將 Muse 延伸至小型企業的重大機會。根據近期使用者調查，我們估計至少有 5 億家自我認定為小型企業的商家，使用 Meta 的應用程式家族來觸及客戶並創造營收。Muse 可協助這些企業獲取客戶並更有效率地營運，同時也幫助人們完成交易。

Over time, consumer and business agents could connect and transact directly, creating opportunities around paid usage, commerce, and business services.

隨著時間推進，消費者與企業代理可能會直接連結並進行交易，從而在付費使用、商務與企業服務等方面創造機會。

Alongside growth, we are focused on building sustainable unit economics. Muse's compute intensity means that expanding its user base will require significant investment, and we expect total serving costs to rise. At the same time, we expect to improve compute cost efficiency by more than tenfold over the next year, driven by better utilization of off-peak capacity, more efficient models, and inference optimization. As revenue scales, these efficiency gains give us confidence in our ability to build a highly profitable business over time.

在推動成長的同時，我們也專注於建立可持續的單位經濟效益。Muse 的運算密集特性意味著，擴大其使用者基礎將需要大量投資，我們預期整體服務成本將上升。同時，我們預期在未來一年內，受益於離峰產能更佳利用、更高效率的模型與推論最佳化，運算成本效率將提升超過十倍。隨著營收規模擴大，這些效率提升讓我們對長期打造高獲利事業的能力更具信心。

Moving now to our financial outlook. We expect fourth quarter 2026 total revenue to be in the range of $73 billion to $76 billion. Our guidance assumes foreign currency is an approximately 1% headwind to year-over-year total revenue growth based on current exchange rates.

接下來談我們的財務展望。我們預期 2026 年第四季總營收將介於 730 億至 760 億美元。我們的指引假設以目前匯率計算，外匯因素對總營收年增率約造成 1% 的逆風。

Turning to the expense and CapEx outlooks, we are raising our expense outlook to incorporate the $9.9 billion charge related to legal proceedings recognized in Q3. We now expect full year 2026 total expenses to be in the range of $175 billion to $179 billion.

談到費用與資本支出（CapEx）展望，我們上調費用展望，以納入第三季認列、與法律程序相關的 99 億美元費用。現在我們預期 2026 全年總費用將介於 1,750 億至 1,790 億美元。

Excluding the Q3 legal charge, we continue to expect 2026 operating income to be above 2025 operating income. At a segment level, we now expect Reality Labs losses to decline compared to 2025 to a range of $18 billion to $19 billion. We anticipate 2026 capital expenditures, including principal payments on finance leases, to be in the range of $135 billion to $145 billion, narrowed from our prior outlook of $130 billion to $145 billion.

若排除第三季的法律費用，我們仍預期 2026 年營業利益將高於 2025 年營業利益。以部門層級來看，我們現在預期 Reality Labs 的虧損將較 2025 年縮小，落在 180 億至 190 億美元區間。我們預期 2026 年資本支出（包含融資租賃的本金償付）將介於 1,350 億至 1,450 億美元，較先前 1,300 億至 1,450 億美元的展望區間有所收斂。

Absent any changes to our tax landscape, we expect our fourth quarter 2026 tax rate to be between 15% and 17%. Additionally, we continue to monitor active legal and regulatory matters that could significantly impact our business and financial results. For example, we continue to see scrutiny on youth-related issues in several markets and have a number of youth-related trials scheduled in the coming months in the United States.

在稅務環境未發生任何變化的前提下，我們預期 2026 年第四季稅率將介於 15% 至 17%。此外，我們持續關注仍在進行中的法律與監管事項，這些事項可能對我們的業務與財務結果造成重大影響。例如，我們在多個市場仍面臨對青少年相關議題的審視，且未來數月在美國將有多起與青少年相關的審判排程。

Looking beyond 2026, we are still developing our budget and capacity plans for next year, but we expect to continue investing aggressively to support both our core business and emerging AI initiatives. Our current capacity and what is scheduled to come online gives us the flexibility to allocate resources across model training, core business growth, and the development and support of new products.

展望 2026 年之後，我們仍在制定明年的預算與產能規劃，但我們預期將持續積極投資，以同時支持核心業務與新興 AI 計畫。我們目前的產能以及已排程上線的產能，讓我們能彈性地在模型訓練、核心業務成長，以及新產品的開發與支援之間配置資源。

Our AI investments are already delivering substantial incremental advertising revenue through stronger engagement, better recommendations and more efficient monetization. Building on this progress, our MSL investments are creating the technology and infrastructure needed to unlock significant new revenue opportunities and strengthen capabilities across the business. While these investments will take longer to generate returns than those in our core business, the breadth of monetization opportunities and internal efficiencies gives us confidence in their long-term potential.

我們的 AI 投資已透過更強的互動、更好的推薦，以及更有效率的變現，帶來可觀的增量廣告營收。在此進展基礎上，我們對 MSL 的投資正在打造所需的技術與基礎設施，以釋放重大的新營收機會，並強化全公司各項能力。雖然這些投資產生回報所需時間將比核心業務投資更長，但變現機會的廣度與內部效率提升，讓我們對其長期潛力充滿信心。

Looking ahead, although we are not providing a full year 2027 revenue outlook, the benefits our AI investments are delivering to the core business, combined with emerging opportunities from model advances and product launches, position us to sustain strong overall revenue growth throughout 2027.

展望未來，雖然我們不提供 2027 全年營收展望，但 AI 投資為核心業務帶來的效益，加上模型進展與產品上市所帶來的新興機會，使我們有條件在 2027 年全年維持強勁的整體營收成長。

Separately, we remain focused on improving Reality Labs' profitability. As Mark mentioned, we expect losses to narrow next year to around $15 billion as we reallocate investment toward other priority areas, primarily AI.

另外，我們仍專注於提升 Reality Labs 的獲利能力。如 Mark 所提到，我們預期明年虧損將收斂至約 150 億美元，因為我們會將投資重新配置到其他優先領域，主要是 AI。

Finally, today we announced plans to create a new class of non-voting capital stock, which will be distributed to all existing shareholders through a stock dividend. For each existing share held, stockholders will receive one share of the new non-voting stock, effectively resulting in a two-for-one stock split. We expect trading to begin in late January 2027.

最後，我們今天宣布計畫創設一個新的無表決權普通股類別，並將透過股票股利分配給所有現有股東。股東每持有一股現有股票，將獲配一股新的無表決權股票，實質上等同於 1 拆 2 的股票分割。我們預期將於 2027 年 1 月下旬開始交易。

In closing, our business momentum continued in Q3 with strong execution across our core ads and engagement initiatives, and we're also excited by our progress towards bringing personal superintelligence to everyone.

總結來說，我們在第三季的業務動能持續，核心廣告與互動相關計畫執行強勁；同時，我們也對朝著讓每個人都能擁有個人超級智慧（personal superintelligence）的目標所取得的進展感到振奮。

With that, Christa, let's open up the call for questions.

接下來，Christa，我們開放提問。

Thank you. We will now open the lines for a question-and-answer session. (Operator Instructions)

謝謝。我們現在將開放電話線進行問答環節。（接線員指示）

Brian Nowak, Morgan Stanley.

Morgan Stanley 的 Brian Nowak。

Thanks for taking my questions. I have two, one on Muse, one on Enterprise. Maybe congrats on the success of Muse. But as you analyze the user behavior and the product, can you talk with us a little bit about any of the constraints to the slope of forward user growth that you're most focused on addressing, whether it's capabilities, model efficiency, capacity, et cetera, just so we understand what are the limiting factors to forward user growth that you want to address?

謝謝讓我提問。我有兩個問題，一個關於 Muse，一個關於企業（Enterprise）。也許先恭喜 Muse 的成功。但當你們分析使用者行為與產品時，能否跟我們談談你們目前最專注要解決、可能限制未來使用者成長斜率的因素有哪些？不論是能力、模型效率、產能等等，讓我們理解你們想要解決的未來使用者成長限制因素是什麼？

And the second one is on Enterprise. Mark, can you just sort of walk us through your vision for the Meta enterprise product offering and the key value drivers you hope to provide for the enterprises adopting the service?

第二個問題是關於企業（Enterprise）。Mark，你能否帶我們梳理一下你對 Meta 企業產品方案的願景，以及你希望為採用該服務的企業提供的關鍵價值驅動因素？

Yeah, I think I can talk about both of those and then Susan can jump in with anything else. All right, so right now for Muse, we are -- One of the things I pointed out is we have more than 10 million people in the US and Canada who have set it up. But I think one of the biggest constraints so far is that because this is a compute-intensive service to run, we have not launched it globally yet. That's partially because of wanting to optimize it for each place, and there's some workaround connectors for that. But it's partially that we want to make sure that we do this efficiently.

好的，我想這兩個我都可以回答，然後 Susan 也可以補充其他內容。好，那就先談 Muse。目前我們——我先前提到的一點是，在美國與加拿大，已經有超過 1,000 萬人完成設定。但到目前為止，其中一個最大的限制是，因為這是一項運算密集的服務，我們尚未在全球推出。部分原因是我們希望針對各地進行最佳化，這方面也有一些替代性的連接器（connectors）可用。但另一部分原因是我們想確保能以高效率的方式來做。

So there's pros and cons there. The pro, of course, is that that just makes it even more impressive that you have 10 million people using it and signing up to use it in the first six weeks because those are all kind of Americans and Canadians in a small number of markets. So if we actually did roll it out more broadly, then you would expect that number to be significantly larger than what we're seeing today.

所以這裡有利有弊。當然，好處是：在前六週就有 1,000 萬人使用並註冊使用，這更顯得令人印象深刻，因為這些使用者基本上都來自美國與加拿大、且僅在少數市場。因此，如果我們真的更廣泛地推出，你會預期這個數字會顯著高於我們今天看到的水準。

But then on the flip side, we actually have to go do the work to bring the efficiency in line to make that make sense. And so that's a big part of it that we need to do. The compute efficiency work is going to be important on this, also because we want to make sure that we've built enough compute to be able to serve what we think is going to be 1 billion-plus people if we can achieve certain compute efficiency targets, but we obviously have a lot of work to do there as well, and that will be one of the limiting factors over the next year.

但另一方面，我們確實必須完成相關工作，把效率提升到合理水準，這樣做才有意義。因此，這會是我們需要做的很大一部分。運算效率的工作在這裡會很重要，因為我們也希望確保我們建置了足夠的運算資源，能在達成特定運算效率目標的前提下，服務我們認為可能超過 10 億人的規模；但顯然我們在這方面也還有很多工作要做，而這將會是未來一年其中一個限制因素。

We want to build out the business around it. So I talked about that. And I think doing that in tandem with bringing down the compute or increasing the compute efficiency is going to be important for getting this to work from a business perspective, which I'm optimistic about. But I think that that's one of the things that we need to do. And then there's just continuing to increase the value in the product, which I think we will largely do by continuing to develop new models. That's why I mentioned that we launched Muse first on Muse Spark, and that's what is currently the default across the free tier.

我們希望圍繞它把業務擴展起來。所以我談到了這點。我認為，同步推進這件事並降低運算成本或提升運算效率，對於從商業角度讓這件事可行將會很重要；我對此感到樂觀。但我認為這是我們需要做的事情之一。另外就是持續提升產品價值；我認為我們主要會透過持續開發新模型來做到這點。這也是為什麼我提到我們先在 Muse Spark 上推出 Muse，而目前它是免費層級的預設選項。

We rolled out Muse Wonder, and people can access that in the paid tier today. And we know that it performs a lot better, so we're working on getting a more efficient version of Muse Wonder that we'll be able to roll out more broadly, but you can imagine just as we iterate forward and two, three models into the future when you have significantly higher intelligence and capability to solve many more problems for people and the ability to deliver that at a much more affordable price point, I think that that's going to just unlock a lot more value to people. So we're very excited about that.

我們推出了 Muse Wonder，而人們今天就可以在付費層級使用它。我們知道它的表現好很多，因此我們正在著手打造更高效率版本的 Muse Wonder，以便能更廣泛地推出；但你可以想像，隨著我們持續迭代、再往前推進到未來兩、三代模型，當你擁有顯著更高的智慧與能力、能為人們解決更多問題，並且能以更可負擔的價格提供，我認為這將為人們釋放出更多價值。所以我們對此非常興奮。

Transitioning to talking about the enterprise piece, because I think these two pieces, there is some connection here in that. The main enterprise offering in the near term is going to be the model API and Muse code, and we have business agents that we've been scaling for a while, and each of those three things is growing quite quickly, so we're excited about that.

接著談到企業端的部分，因為我認為這兩個部分之間確實有一些關聯。短期內主要的企業產品將會是模型 API 與 Muse code；此外我們也有一段時間一直在擴展的商務代理（business agents）。這三項都成長得相當快，所以我們對此很興奮。

Over time, we would like to make it, so that we have a whole kind of business network of Muse agents as well. There's the business agent, which we've talked about on previous earnings calls for businesses to help out with sales and customer support. But what we see is a lot of people are actually using Muse today to help run especially small businesses. And we think that there's both an opportunity to help, create an agent that people use to really enable them to automate and do a lot of the parts of spinning up a small business that are just kind of difficult and time-consuming but aren't the core thing that a person is trying to do.

長期來看，我們希望也能建立一整套由 Muse 代理組成的商務網路。其中有商務代理，我們在先前的財報電話會議中談過，能協助企業處理銷售與客服支援。但我們看到的是，現在其實有很多人正在使用 Muse 來協助經營、特別是小型企業。我們認為這裡有機會去協助打造一個代理，讓人們用它來真正賦能，協助他們自動化並完成許多創辦小型企業時那些困難且耗時、但又不是一個人真正想做的核心工作的環節。

So we think that's a big deal. And then making a version of Muse that people can bring into different corporate environments and work there we think is going to be a big deal. And then beyond that, building what I refer to as the Muse Network, which is making it so that Muse is not just a kind of single player game where you have your Muse, but making it so that your Muses can work with your friends and your families and if you want to buy something, it's not just navigating to that business's website, it's talking to their agent. I think that getting that all to work well together is going to unlock tremendous value at scale.

所以我們認為這很重要。另外，我們也認為，打造一個版本的 Muse，讓人們可以把它帶進不同的企業環境並在那裡工作，也會是一件大事。再往後，就是建立我所稱的 Muse Network：讓 Muse 不再只是某種單人遊戲——你只有你自己的 Muse——而是讓你的 Muse 能與你的朋友與家人一起協作；如果你想買東西，不再只是導向那家企業的網站，而是與他們的代理對話。我認為，讓這一切能夠良好地協同運作，將在規模化時釋放出巨大的價值。

So i'm very excited about all of that. I think the enterprise use is going to be a big part of it, but it's also going to kind of have this very valuable boost in the utility for consumers too. So i'm very excited about both of those.

所以我對這一切都非常興奮。我認為企業端的使用會是其中很大的一部分，但它也會在消費者端的效用上帶來非常有價值的提升。所以我對這兩者都非常期待。

I'll add on to Mark's comments on Enterprise AI is creating huge amounts of disruption in enterprise today. And we don't -- from what we can see, we really don't believe that traditional enterprise companies have this lockdown. And in fact, some of the leading companies in this space today didn't exist a few years ago. Those companies made large investments in model development and we've done the same and we have increasingly competitive models to bring to bear for the benefit of all of our users, including small businesses and including enterprises.

我補充一下 Mark 對企業 AI 的評論：企業 AI 正在為當今的企業帶來巨大的顛覆。而且就我們所見，我們並不認為傳統企業公司已經把這件事「鎖死」了。事實上，今天在這個領域的一些領先公司，幾年前根本還不存在。那些公司在模型研發上投入了大量資金；我們也做了同樣的事，並且我們擁有越來越具競爭力的模型，能為所有使用者帶來效益，包括小型企業與大型企業。

And already today, we have 500 million businesses using our products. So we really believe that AI is going to reshape how businesses operate, we expect that businesses of all sizes are going to use AI agents across software development and productivity, sales, marketing, customer service, etc. We have differentiated assets to serve this market, bringing together models, infrastructure, global distribution and long-standing relationships with businesses.

而且就在今天，已有 5 億家企業在使用我們的產品。因此我們確信 AI 將重塑企業的運作方式；我們預期各種規模的企業都會在軟體開發與生產力、銷售、行銷、客服等領域使用 AI 代理。我們擁有可服務此市場的差異化資產，能把模型、基礎設施、全球分發能力，以及與企業長期建立的關係整合在一起。

And it's our hope that this will be able to be a new diversified recurring revenue stream for us that will be able to support multiple business models, including subscriptions and usage-based API and messaging and other revenue lines. So we expect that this will be an opportunity that will develop over multiple years and we intend to scale our investment behind demonstrated customer demand and product market fit in this area.

我們希望這能成為一條新的、多元化的經常性收入來源，並能支援多種商業模式，包括訂閱制、按用量計費的 API 與訊息服務，以及其他收入線。因此我們預期這將是一個需要多年發展的機會；我們也打算在此領域依據已被證實的客戶需求與產品市場契合度（product-market fit）來擴大投資規模。

Eric Sheridan, Goldman Sachs.

Eric Sheridan，高盛。

Thanks so much for taking the questions. Maybe just the first one building on Brian's question. When you think about the friction points around agentic commerce, how do you guys as a company think about solving for friction that's rising where there are aggregators or suppliers that don't want agents to interact with their platforms or their services? And how do you think about lowering that friction or creating the right balance between the existing services that consumers access today relative to how this might all be changed or altered by agentic behavior over the medium to long-term.

非常感謝讓我提問。第一個問題可能延續 Brian 的問題。當你們思考代理式商務（agentic commerce）周邊的摩擦點時，若出現聚合平台或供應商不希望代理與其平台或服務互動、導致摩擦上升，你們公司會如何思考解決這些摩擦？以及你們如何看待降低摩擦，或在消費者目前可使用的既有服務，與中長期可能因代理行為而被改變或重塑的方式之間，建立適當的平衡？

And the second one would be with the announcement of the new class of shares tonight with earnings. Any updated thoughts broadly about how you think about sources of capital and optimizing your capital structure to make sure you invest the proper amounts to capitalize on the opportunities that AI are presenting in the next couple of years? Thanks so much.

第二個問題是，今晚隨著財報公布了新的股份類別。關於資金來源以及最佳化資本結構，以確保你們投入適當的資金規模、把握未來幾年 AI 所帶來的機會，你們是否有任何更新的想法？非常感謝。

I can answer the first one. So, okay, so the question, what -- sorry, what was the first question there?

我可以回答第一個。所以，好，這個問題是——抱歉，第一個問題是什麼來著？

Friction points around agentic commerce.

代理式商務的摩擦點。

Got it, all right. Yeah, right now what we're seeing is that overwhelmingly businesses are very excited about enabling this because they recognize that it's going to be a new opportunity for them, not only to increase the sales and the quality of the experience for existing customers, but also potentially to bring in new customers. So now I mean, across the whole business ecosystem, different people will kind of adopt this at different paces. And how our strategy evolves on that to develop the ecosystem will depend on how that goes.

了解，好。是的，目前我們看到的是，絕大多數企業都非常興奮、也很願意啟用這件事，因為他們認知到這將是新的機會：不僅能提升既有客戶的銷售與體驗品質，也可能帶來新客戶。所以在整個商業生態系中，不同的人會以不同的速度採用。而我們在這方面的策略如何演進、如何發展生態系，將取決於事情的進展。

But overall, I would say we've been very positively surprised by how quickly I think a huge amount of businesses have wanted to not only figure out how to make it so that Muse can use their services more effectively, but have reached out to us to integrate around it. So I view that as a very good sign. And obviously not everyone wants to be an early adopter, that's fine. We'll work with folks on the terms that make sense for them. But I do think that overtime time, this is going to be quite valuable for everyone to work well, and I think we're on a good trajectory on that so far.

但整體而言，我會說我們對於大量企業想要採用的速度感到非常正向的驚喜：他們不僅想弄清楚如何讓 Muse 更有效地使用他們的服務，也主動聯繫我們、希望圍繞此進行整合。所以我把這視為非常好的訊號。當然，不是每個人都想當早期採用者，這也沒關係。我們會以對他們有意義的條件與方式來合作。但我確實認為，隨著時間推進，讓這一切能順暢協作對每個人都會很有價值；而到目前為止，我認為我們的進展軌跡相當不錯。

Yeah, I would add to that. And I will also answer your second question and just say, I think agents are going to be an important part of how reality evolves. And I think everyone is going to have to adapt to what that means, the new age of agentic commerce. We obviously have had a lot of businesses were very excited to partner with us. There are also businesses that are understandably focused on protecting customer relationships.

是的，我也補充一下。我也會回答你的第二個問題：我認為代理將會是現實演進方式中的重要一環。我認為每個人都必須去適應這代表什麼——代理式商務的新時代。顯然，我們有很多企業非常興奮地想與我們合作。同時，也有一些企業可以理解地更專注於保護客戶關係。

And we expect the market, I think, ultimately to evolve away from agents attempting to navigate every digital experience like a human, and I think over the long run, this will move toward more permissioned structured interactions. And that will include authenticated APIs, approved agent partnerships, or direct communications between a consumer's personal agent and a business's own agent. And we're helping establish the standards needed to support that model.

我們預期市場最終會從讓代理嘗試像人類一樣去導覽每一個數位體驗的模式演進開來；我認為從長期來看，這將轉向更具授權機制的結構化互動。這將包括經驗證的 API、經核准的代理合作夥伴關係，或是消費者的個人代理與企業自有代理之間的直接通訊。而我們正在協助建立支援該模式所需的標準。

Earlier this month, we previewed the personal agent protocol and open standard across Muse and Meta business agents that we are developing with industry partners like Sierra, Walmart, Stripe, Shopify, et cetera, the protocols intended to define how a consumer's personal agent can interact securely and rely on the business's agent and preserve appropriate controls for both the business and customer.

本月稍早，我們預覽了個人代理協定，以及我們正與 Sierra、Walmart、Stripe、Shopify 等產業夥伴共同開發、適用於 Muse 與 Meta 企業代理的開放標準；這些協定旨在定義消費者的個人代理如何能夠安全互動、信賴企業的代理，並為企業與客戶雙方保留適當的控管機制。

So again, I think adoption will likely be uneven and will take time. And in the near term, we expect any experience -- many experiences will remain AI assisted rather than fully autonomous. But as trusted integrations develop and agents demonstrate that they can generate incremental value and demand and operate safely, we expect that more and more businesses will be excited to participate.

所以再說一次，我認為採用情況很可能不均衡，且需要時間。而在短期內，我們預期任何體驗——許多體驗——仍將是 AI 輔助，而非完全自主。但隨著可信的整合逐步成熟，且代理證明它們能夠創造增量價值與需求並安全運作，我們預期會有越來越多企業樂於參與。

Your second question was about the announcement of the new class of shares. So I should say, we created this new class of shares with the purpose of creating a publicly traded non-voting stock usable for capital raising, employee compensation, acquisitions, other general corporate purposes while preserving the voting power of existing Class A and B shareholders.

你的第二個問題是關於新股類別的公告。我應該說，我們設立這個新股類別的目的，是創造一種可公開交易、無表決權的股票，用於募資、員工薪酬、併購及其他一般公司用途，同時保留現有 A 類與 B 類股東的表決權。

We believe the share class will maintain our founder-led structure. It will expand our funding tools and give us flexibility to invest behind the unprecedented momentum we're seeing across every part of our business driven by AI. We don't have any specific financing plans to announce at this time, but we thought it was prudent to establish the appropriate capital structure framework to ensure that we have access to a diverse pool of funding sources.

我們相信這個股類將維持我們由創辦人主導的治理架構。它將擴充我們的資金工具，並讓我們能更有彈性地投入資源，以承接我們在 AI 驅動下於各業務面向所看到的前所未有動能。我們目前沒有任何具體的融資計畫要宣布，但我們認為建立適當的資本結構框架是審慎之舉，以確保我們能接觸到多元的資金來源。

Douglas Anmuth, JPMorgan.

Douglas Anmuth，摩根大通。

Great. Thanks for taking the questions. I have two. First, just wanted to follow-up on your last comment, Susan, just around as Muse evolves and more businesses adopt agents, just wanted to get your sense of how things kind of change and shift as you go to more permission-based and agent-to-agent transactions? And what does that really unlock over time?

很好。謝謝讓我提問。我有兩個問題。第一個是想追問你剛才最後的評論，Susan，關於隨著 Muse 演進、更多企業採用代理，當你們走向更以授權為基礎、以及代理對代理的交易時，你對整體如何改變與轉移有何看法？而這在時間推移下究竟會解鎖什麼？

And then secondly, just on kind of expenses and CapEx, thinking about '27, I know you're not really there yet. But if I go back to some previous comments, you've talked about maximizing compute in '26 and '27 and then having more flexibility in '28. A year ago, you talked about kind of notably larger dollar increase in '26 and '25, and then you've also used kind of growing operating income on an annual basis as well. So just curious if there's any of those that you can kind of tie or help us think about '27?

第二個是關於費用與資本支出（CapEx），思考到 2027 年，我知道你們還沒到那一步。但如果我回顧一些先前的評論，你們談到在 2026 與 2027 年最大化算力，然後在 2028 年有更大的彈性。一年前你們提到 2026 與 2025 年的美元增量會顯著更大，另外你們也提過營業利益會逐年成長。所以想請教，這些說法中是否有任何一點可以連結起來，或協助我們思考 2027 年？

Thanks, Doug. So on your first question about how the agentic ecosystem evolves. I wish I could sort of predict that more perfectly. And I think it will take some time. And again, I think it will be a little uneven. But I definitely think that when I use Muse today, it's clear that there are a lot of parts of the experience that would be even better if Muse was able to interact more seamlessly with business agents on the other side. For example, if Muse has to call business on my behalf, I think it would be easier for the business if that call was handled by business agents that were representing it.

謝謝，Doug。關於你第一個問題：代理生態系如何演進。我希望我能更精準地預測。我認為這會需要一些時間。而且再說一次，我認為會有些不均衡。但我確實認為，當我今天使用 Muse 時，很明顯體驗中有很多部分，如果 Muse 能更無縫地與另一端的企業代理互動，會變得更好。例如，如果 Muse 必須代表我致電企業，我想若該通話由代表企業的企業代理來處理，對企業而言會更容易。

And I think also one of the things that is really distinctive about Muse and one of the things that makes the product experience so great is the degree of proactivity that it exhibits on my behalf. If I can give it a task and Muse is going to go execute against that task for me, even as it encounters some obstacles or can't quite find the right thing and needs to chart a new path to helping me look for the thing I want.

我也認為，Muse 非常獨特、且讓產品體驗如此出色的一點，是它代表我展現出的主動性程度。如果我交付它一個任務，而 Muse 會替我去執行該任務，即使在過程中遇到一些障礙，或一時找不到正確的東西、需要重新規劃路徑來協助我尋找我想要的東西。

And so I think that sort of dimension of proactivity exhibited by either consumer agents or business agents, I think are going to enable more transactions to happen or more activity to happen broadly than happens today where, when things are -- when more actions are taken primarily, when like the latent demand expresses itself versus, things where I can have Muse searching for things for me on an ongoing basis, giving me regular updates on things I'm looking for, sending me 10 new books a month and agents should be doing similar things for businesses.

因此我認為，無論是消費者代理或企業代理所展現的那種主動性維度，將使更多交易得以發生，或更廣泛地讓更多活動發生；相較於今天多數行動主要是在潛在需求自行浮現時才被觸發——相對地，如果我能讓 Muse 持續替我搜尋、定期更新我在找的東西、每月寄給我 10 本新書，而代理也應該為企業做類似的事情。

And I think that creates sort of opportunities again for a new, more proactive sort of framework for what agent and agent interactions look like over time.

我認為這再次創造了機會，讓代理與代理之間的互動框架，隨時間推移走向一種新的、更主動的模式。

On your second question, which is about 2027, we are quite early in developing our budget and capacity plans for next year. So we are, I would say, at the point where we are both investing, sorry, evaluating a lot of investment proposals that have attractive return profiles over different time horizons, and we want to figure out how we can fund as many of those as possible within the construct of our overall budget and financial goals. But it's very dynamic, and it's still pretty early, and so we don't have anything more specific or quantitative to share until we get to the Q4 call, which is typically when we share guidance for the next year.

至於你的第二個問題，也就是關於 2027 年，我們目前仍在非常早期的階段制定明年的預算與產能規劃。所以我會說，我們目前一方面在評估許多在不同時間跨度上具有吸引人報酬特性的投資提案，並希望在整體預算與財務目標的框架內，找出如何為其中盡可能多的提案提供資金。但這非常動態，而且仍相當早期，因此在我們到第四季電話會議（通常我們會在那時提供下一年的指引）之前，沒有更具體或量化的內容可以分享。

Justin Post, Bank of America.

Justin Post，美國銀行。

Great, thanks. One for Mark, one for Susan. Mark, you've got this powerful new model on your hands and it seems like there's a lot you could do internally besides externally. But specifically to the ad business, you re-architected your systems around AI. How much room is there for improvement as you deploy that new model? How are you thinking about that?

很好，謝謝。一個問題給 Mark，一個給 Susan。Mark，你手上有這個強大的新模型，看起來除了對外，你在內部也有很多可以做的事。但具體到廣告業務，你們已經圍繞 AI 重新架構了系統。當你部署這個新模型時，還有多大的改善空間？你們是怎麼思考這件事的？

And then for Susan, you mentioned strong revenue growth next year. Just wondering if that's advertising or does that incorporate some incremental AI revenues hitting next year? Thank you.

然後給 Susan，你提到明年營收將強勁成長。想請問那是指廣告營收，還是也包含一些明年開始貢獻的增量 AI 營收？謝謝。

I'm happy to take both of those. Great. On your first question, I think our ads business has been benefiting for now many years from our ongoing investments in both kind of what we would have called traditional AI machine learning models and then of course from the sort of more recent generation of models. I would say that there are three themes there that I think are worth outlining.

我很樂意兩個都回答。很好。關於你的第一個問題，我認為我們的廣告業務多年來一直受惠於我們持續投入——包括我們過去稱之為傳統 AI 機器學習模型的投資，當然也包括較近期這一代模型的投入。我會說其中有三個主題值得說明。

The first is just the kind of traditional roadmap of performance improvements that we have in the pipeline based -- that is what I would describe more as business as usual machine learning work that continues to be a robust and healthy pipeline. And as we are looking into 2027, again, we're not providing an outlook, but I would say that our investments and product improvements across both engagement and ads initiatives give us confidence that we have meaningful runway to grow our core business throughout 2027.

第一個主題是，我們在管線中有一條相對傳統的效能提升路線圖——我會把它描述為一如既往的機器學習工作——而這條管線仍然強健且健康。當我們展望 2027 年時，再次強調我們不提供展望，但我會說，我們在互動與廣告相關計畫上的投資與產品改進，讓我們有信心在 2027 年全年仍有相當可觀的空間來成長我們的核心業務。

That also gets to your second question also, but I should say, basically, I think the ranking and recommendations pipeline is healthy. The second theme I would say is that we are excited about some of the new research bets that we have as we move into sort of a more LLM-oriented AI infrastructure to help us more deeply reason about people's preferences, what they're interested in both across organic content and recommendations, and we expect that we'll be able to unlock -- we will be able to unlock benefits to our ranking and recommendations engine from that research too.

這也回應了你的第二個問題，不過我也應該說，基本上我認為排序與推薦的管線是健康的。第二個主題是，隨著我們轉向更以 LLM 為導向的 AI 基礎設施，我們對一些新的研究押注感到興奮，這將幫助我們更深入地推理人們的偏好、他們感興趣的事物——涵蓋自然內容與推薦——而我們預期也能從這些研究中為我們的排序與推薦引擎解鎖效益。

And then the third thing is that we expect that generative AI tools, which have already been very valuable for advertisers, will continue to grow. In terms of the features that we make available to advertisers primarily through the Advantage Plus suite, but features that make it easier for advertisers to quickly and seamlessly generate, whether it is creative or take an image and generate video or generate sound, all I think in service of making the ads. Increasingly personalized for the person that they're being served to. So I would say we feel like there is meaningful runway across all three of those things.

接著第三點是，我們預期生成式 AI 工具（這些工具對廣告主而言已經非常有價值）將會持續成長。就我們主要透過 Advantage Plus 套件提供給廣告主的功能而言，這些功能讓廣告主能更快速、無縫地生成內容——不論是創意素材，或是把一張圖片生成影片、生成聲音——我認為這一切都是為了讓廣告。能夠越來越針對被投放的個人進行個人化。所以我會說，我們覺得在這三件事上都有相當可觀的發展空間。

Your second question was about revenue growth next year. And so as I mentioned, I think we're both feeling good about the budget investments that we expect we will make in both core ads and engagement initiatives next year. We're also building several new AI businesses, and we expect that those can begin contributing incremental revenue in 2027, but more importantly, can scale meaningfully over time. And those will include monetizing our AI products through subscriptions, transactions, advertising, developing enterprise offerings, as we talked about in one of the earlier questions.

你的第二個問題是關於明年的營收成長。如我提到的，我們對於明年預期在核心廣告與互動（engagement）計畫上的預算投資都感到樂觀。我們也正在打造數個新的 AI 業務，我們預期這些業務可在 2027 年開始貢獻增量營收，但更重要的是，能隨時間顯著擴張。這些將包括透過訂閱、交易、廣告來變現我們的 AI 產品，並開發企業級方案，正如我們在先前某個問題中談到的。

So I would say while many of these opportunities remain early and our near-term focus is really on building high-quality products and achieving product market fit and scaled product market fit, I think our track record of reaching billions of people and building businesses at scale makes us feel good that AI is going to become a meaningful source of revenue diversification over time.

所以我會說，雖然這些機會中有許多仍處於早期階段，而我們短期的重點確實是打造高品質產品、達成產品市場契合（product-market fit）以及可規模化的產品市場契合，但我認為我們過去觸及數十億人並以規模化方式建立業務的紀錄，讓我們對 AI 隨時間成為有意義的營收多元化來源感到樂觀。

Mark Shmulik, Bernstein.

Mark Shmulik，Bernstein。

Yes, thanks for taking my questions. Mark, coming out of Connect, it kind of felt like we were ushering in the next era of the company and the business reorienting around kind of news at the center of everything. Is that a fair assessment of kind of how things are going internally? And if so, can you talk a little bit more about how some of the business mandates and outcomes may have changed?

是的，謝謝讓我提問。Mark，從 Connect 之後的感覺是，我們彷彿正在迎來公司下一個時代，而業務也正在重新定位，圍繞著某種以「新聞」作為一切核心的方向。這樣的描述是否公平，能反映內部目前的進展？如果是的話，你能否多談一些，某些業務使命（mandates）與成果（outcomes）可能有哪些改變？

And then, Susan, it was interesting to kind of see the launch cadence where enterprise announcements kind of preceded some of the small business ones. Appreciate your comments on some of what's going on there around the SMB agents opportunity, but can you just share more details on kind of the work required to serve and scale the offerings to SMBs?

另外，Susan，看到發布節奏很有意思：企業端的公告似乎先於一些小型企業端的公告。我很感謝你對 SMB 代理（agents）機會的評論，但你能否分享更多細節，關於要服務並擴大面向 SMB 的方案，所需要投入的工作大概有哪些？

Yeah, I mean, I can talk briefly about the first one. I mean, look, it was more than a year ago that I think I wrote the letter about personal superintelligence as the North Star for the work that we're doing here. And it basically, it fits with this line of work that we've done for more than 20 years at the company that is focused on empowering individuals, giving people a voice, giving people the tools to connect in the ways that they want.

好的，我先簡短談一下第一個問題。你看，我想在一年多前我就寫過那封信，把「個人超級智慧」（personal superintelligence）作為我們在這裡所做工作的北極星。而這基本上也符合我們公司二十多年來一直在做的工作脈絡：專注於賦能個人、讓人們有發聲的管道、提供工具讓人們以他們想要的方式連結。

And when you extend that to the work around AI now, we think that the most important thing that we can be building for this next generation of technology is basically putting the power of this technology in everyone's hands, which is the personal superintelligence vision. So we've been working on this for a while. And this is when we did the reboot around MSL and building the lab. A lot of it was this idea that we need to build models specifically to be good as personal agents, that we'd be able to build the best experience by owning and building and designing ourselves the end-to-end technology that includes the models and then the agents.

當你把這延伸到現在的 AI 工作時，我們認為，對於下一代科技而言，我們最重要能打造的事情，就是把這項技術的力量交到每個人手上——這就是個人超級智慧的願景。所以我們已經投入這件事一段時間了。而這也是我們圍繞 MSL 進行重啟並建立實驗室時的核心。其中很大一部分是這個想法：我們需要打造特別適合做個人代理（personal agents）的模型；而要提供最佳體驗，我們必須自己掌握、建構並設計端到端的技術，包含模型以及代理。

And this has kind of been in the works for a while. I mean, the vision around the glasses has also been this. We've wanted to build the next generation of hardware platforms so that we can deliver the best end-to-end experiences to people. And I think that that's starting to come together as well and I think will even more over the coming years. I mean, these are long-term bets. I feel like this is what we're here to do is make long-term technology bets and design the best experiences end-to-end that we can for billions of people around the world.

而這其實已經醞釀一段時間了。我意思是，眼鏡相關的願景也一直是如此。我們希望打造下一代硬體平台，讓我們能把最佳的端到端體驗交付給人們。我認為這也開始逐步成形，並且在未來幾年會更加明顯。我的意思是，這些都是長期押注。我覺得我們來這裡要做的，就是進行長期的科技押注，並為全球數十億人設計我們所能做到的最佳端到端體驗。

And I think as long as we continue to do that, then over time, the business takes care of itself as long as we continue executing well, which I'm really proud of the team for how we're doing on that.

我認為只要我們持續這麼做，那麼隨著時間推進，只要我們持續把執行做好，業務自然會水到渠成；我也為團隊在這方面的表現感到非常自豪。

Thanks, Mark. Your second question was around Muse for small business. So we launched that, which you can think of as an expansion for Muse in late September. And rather than a separate product, it's kind of a set of new skills and connectors inside the existing Muse app aimed at helping SMB owners run operations, find new customers, it connects to a businesses, for example, Instagram account analytics or Facebook pages or Meta ad accounts and a few clicks along with dozens of third-party connectors that businesses already run on like Shopify, QuickBooks, Canva, et cetera.

謝謝，Mark。你的第二個問題是關於面向小型企業的 Muse。我們在 9 月下旬推出了它，你可以把它視為 Muse 的一個擴展。它不是一個獨立產品，而是在既有 Muse 應用程式內新增的一組技能與連接器（connectors），目標是協助 SMB 業主經營營運、尋找新客戶；它可以連接到企業的資料，例如 Instagram 帳號分析、Facebook 粉絲專頁或 Meta 廣告帳戶，只需幾次點擊，並且也支援數十種企業已在使用的第三方連接器，例如 Shopify、QuickBooks、Canva 等等。

It already understands what businesses sell, its brand voice. What customers are asking for, Muse can take actions, including analyze ad and content performance, draft campaigns, customer responses, flag issues. And we are actively listening to our SMB users to understand what their top use cases are. We are seeing them use it for ads optimization, for direct message organizing, use it to expand their sales footprint, to keep their website current based on things like inventory and new products, to deal with employee load balancing.

它已經能理解企業在賣什麼、其品牌語氣。也能理解客戶在詢問什麼；Muse 可以採取行動，包括分析廣告與內容表現、起草行銷活動、撰寫客戶回覆、標記問題。我們也在積極聆聽 SMB 使用者，以了解他們最主要的使用情境。我們看到他們用它來做廣告最佳化、整理私訊、擴大銷售觸及範圍、依據庫存與新品等資訊維持網站內容更新，以及處理員工工作量平衡。

So we're pretty closely following how businesses use Muse to make sure that we are being thoughtful about new features that we release in Muse to make it maximally useful and productive for SMBs. I'd also say we have unique touch points to, again, I mentioned in my opening remarks, 500 million self-identified small businesses. And we think that many of the investments that we make in consumer products are going to carry over to help power those businesses.

因此我們非常密切追蹤企業如何使用 Muse，以確保我們在 Muse 中推出的新功能是經過深思熟慮的，讓它對 SMB 來說盡可能有用且提升生產力。我也想說，我們擁有獨特的觸點——如我在開場談話中提到的——有 5 億家自我認定的小型企業。我們認為，我們在消費者產品上的許多投資，也會延伸過來，協助驅動這些企業。

Also, we have multiple excellent channels to surface those opportunities to small businesses globally. So this is a place where we feel like we have an existing extremely strong platform, and we're very excited about it. And we also believe the transition to AI has broadly unlocked enterprise as a new opportunity for us as well.

此外，我們也有多個非常優秀的管道，能在全球向小型企業呈現這些機會。所以在這一塊，我們覺得自己已經擁有一個既有且極其強大的平台，我們對此非常興奮。我們也相信，向 AI 的轉型也在更廣泛的層面上，為我們解鎖了企業端作為一個新的機會。

Ross Sandler, Barclays.

Ross Sandler，Barclays。

Great. Mark, you touched on this earlier, but could you elaborate a little bit on maybe some high-level metrics around the per user cost structure of Muse today and then how you kind of see that cost curve coming down as you go forward and what are some of the things you're doing to bring that cost curve down? Thank you.

很好。Mark，你先前有提到這點，但你能否再多談一些，關於目前 Muse 的每位使用者成本結構（per-user cost structure）的一些高層次指標，以及你如何看待未來這條成本曲線會如何下降？另外，你們正在做哪些事情來讓這條成本曲線下降？謝謝。

I'm happy to answer that, and Mark, you should add anything that you feel like I'm missing. We don't have sort of specific numbers to share around the cost structure of Muse today, but of course it is, as Mark said, pretty compute expensive and making sure that we are focused on compute efficiency is going to be one of the key vectors towards being able to both scale Muse and grow it into the business that we want.

我很樂意回答這個問題，Mark，如果你覺得我有漏掉什麼也請補充。我們目前沒有可分享的、關於 Muse 成本結構的具體數字；但當然，如 Mark 所說，它在算力上相當昂貴，而確保我們聚焦在算力效率，將會是能同時擴大 Muse 規模並把它發展成我們想要的業務形態的關鍵方向之一。

I think there are a couple of dimensions of achieving that efficiency. I think some of the more nearer term pieces include things like leveraging off-peak or spare computing capacity to run some sets of jobs, using smaller models. There's a lot of work to be done across different inference efficiency initiatives, like, all in service effectively of higher GPU utilization and other product efficiency work we can do also. And I think over the longer-term, I think this is the place where we expect that we're going to be able to, over time, as LLMs scale, get more tasks done with fewer tokens and also rely on AI models themselves to help us improve the efficiency of the software that we use to run the models.

我認為要達成這種效率有幾個面向。較接近短期的部分包括：利用離峰或閒置的運算容量來跑某些工作集、使用較小的模型。在不同的推論效率（inference efficiency）計畫上還有大量工作要做，例如——本質上都是為了提高 GPU 使用率，以及我們也能做的其他產品效率工作。而從更長期來看，我認為這是我們預期能做到的地方：隨著 LLM 規模擴大，逐步用更少的 token 完成更多任務，並且也依賴 AI 模型本身來協助我們提升用來運行模型的軟體效率。

So I think it's a place where we both feel like there is a lot more work on our efficiency roadmap that is going to help us bend the curve here. And we also expect that the sort of arc of how these sort of AI-driven technological advances are going to apply here will also help us achieve larger savings over time.

所以我認為，這是一個我們雙方都覺得在效率路線圖上還有很多工作要做、而且將有助於我們在這裡讓曲線趨緩的領域。我們也預期，這些由 AI 驅動的技術進展將如何在此應用的整體走勢，也會幫助我們隨時間推移實現更大的節省。

Mark Mahaney, Evercore ISI.

Mark Mahaney，Evercore ISI。

Okay, thanks. Two questions. There's a bit of a playbook or there has been at Meta over the years when you knew surfaces and you know you build up the user growth engagement then you layer in monetization you think it's sort of a similar playbook here or it has does it have to be a little bit faster with Muse just given that the costs associated with it are materially greater arguably than launching those surfaces in the past.

好的，謝謝。兩個問題。多年來 Meta 那邊有一套劇本，當你推出新的介面/版位時，你會先把用戶成長與互動拉起來，然後再疊加變現。你認為這裡也是類似的劇本嗎？還是說，考量到 Muse 相關成本實質上（可以說）比過去推出那些介面更高，因此必須更快一些？

And then just a clarification on that commerce data point that you provided about 25% of users and the $200 or greater ASP. Are you including in commerce travel purchases or is that just a retail data point? Thank you.

另外，想釐清你提到的那個電商數據點：大約 25% 的用戶，以及 200 美元或以上的 ASP（平均售價）。你們在電商中是否包含旅遊購買，還是那只是零售的數據點？謝謝。

My guess, I think that we are going to work on monetization somewhat sooner on this than our normal playbook for a couple of reasons. One is just the size of the numbers that we're talking about in terms of both the costs and the opportunity I think make it kind of important to make progress on that in order to be able to scale it. The other is just that such a large part of what people are doing is commerce. And to your question, that does include travel too.

我猜想，我認為我們會比我們一般的劇本更早一些著手變現，原因有幾個。其一是我們談到的數字規模，不論是成本或機會，我認為都使得在這方面取得進展變得相當重要，才能夠擴大規模。另一個原因是，人們在做的事情中有很大一部分是電商。而就你的問題而言，這也包含旅遊。

I think we might consider travel a different case, but travel is actually one of the other top use cases for Muse, is basically people planning that out and planning different kinds of things that they would get and they might get through our family of apps. So I think that this is going to be an important thing for us to work on to deliver the consumer value that people want. And in doing so, I think we will be able to build a model where we get a percent of the value that we are helping to create for people.

我想我們可能會把旅遊視為不同的案例，但旅遊其實也是 Muse 的另一個主要使用情境之一，基本上是人們在規劃行程、規劃各種他們會購買的東西，而這些可能會透過我們的應用程式家族取得。所以我認為，這會是我們需要著力的一個重要方向，以提供人們想要的消費者價值。而在這麼做的同時，我認為我們將能建立一個模式，讓我們取得我們協助為人們創造之價值的一定比例。

So it's going to be very important to kind of get the math on all of this to work out so that way we can continue the compute build out that we want to build in order to get this to reach everyone at scale. And in addition to everything that Susan said in response to the last answer, I would also just add that like we just see this trend that, year over year, I just expect that we will be able to deliver the same intelligence that we have now in Muse Wonder or frankly any of the current frontier models at a fraction of the cost in a smaller model a year from today.

因此，讓所有這些的數學能夠成立將非常重要，這樣我們才能持續進行我們想要推進的算力建置，以便把這項服務以規模化方式推向所有人。此外，除了 Susan 在上一題回覆中提到的一切之外，我也想補充：我們確實看到這個趨勢——逐年來看，我預期從現在起一年後，我們將能以更小的模型、用目前成本的一小部分，提供與現在在 Muse Wonder（坦白說也包括任何當前前沿模型）相同的智慧水準。

So to the extent that that represents some kind of baseline level that people seem to -- that kind of sufficient for product market fit for Muse, I think that we will just continue through kind of continued model development, make progress on that efficiency. The thing that is and of course less clear is that I don't think in a year from now most people are going to want to use the current model level of intelligence. Because that's also going to make progress. So I think we're going to need to work on all of these things, both the revenue pieces of it and scaling the different aspects of that as well as progressing on the model development and all the efficiency in order to be able to both fund and support the compute build out and reach billions of people, which again, we want to get to that as soon as possible.

因此，若那代表某種基準水準——人們似乎認為那對 Muse 的產品市場契合（product-market fit）已足夠——我認為我們將透過持續的模型開發，繼續在效率上取得進展。當然，較不明確的是：我不認為一年後大多數人會想使用目前這個模型等級的智慧。因為那也會進步。所以我認為我們需要在所有這些事情上努力：一方面是營收端的各個部分與其不同面向的擴張，另一方面是推進模型開發與各項效率提升，才能同時為算力建置提供資金並加以支撐，進而觸及數十億人——而這也是我們希望盡快達成的。

Part of the reason why we're not just charging everyone upfront to use this is we want to establish this Muse network and we think that it's going to be more valuable for people at scale when there are a lot of people and businesses using Muse so that way they can collaborate and work together. I think that that's really a very important state to get to and one that we're quite excited about. And again, I don't think that there are many companies in the world that are well situated to be able to do that in the way that we are. I think we are very well situated to do that, and we plan to push on that quite aggressively.

我們之所以不是一開始就向所有人收費來使用，是因為我們想建立這個 Muse 網路；我們認為，當有大量的人與企業使用 Muse、使他們能夠協作並一起工作時，對人們而言在規模化情況下會更有價值。我認為那真的是一個非常重要、而且我們相當興奮要達到的狀態。而且再說一次，我不認為世界上有很多公司能像我們一樣具備良好條件，以我們的方式做到這件事。我認為我們非常具備條件，我們也計畫在這方面相當積極地推進。

And that does conclude our question-and-answer session. Mr. Bevegni, I would like to turn the call back over to you.

以上為我們的問答環節。Bevegni 先生，我想把電話會議交回給您。

Thank you for joining us today, and we look forward to speaking with you again soon.

感謝您今天加入我們，我們期待不久後再次與您交流。

And ladies and gentlemen, this does conclude today's conference call. Thank you for your participation.

各位女士、先生，今天的電話會議到此結束。感謝各位的參與。