Kingsoft Cloud Holdings Ltd (KC) 2026 Q2 法說會逐字稿

Good morning, ladies and gentlemen, and thank you for standing by for Kingsoft Cloud's second quarter 2026 earnings conference call. (Operator Instructions) Please note that today's call is being recorded. I will now turn the call over to Mr. Jacky Zuo, Senior Director of Capital Markets at Kingsoft Cloud. Jacky, please go ahead.

各位女士、先生，早安，感謝您撥冗參加金山雲 2026 年第二季度業績電話會議。（接線員指示）請注意，今天的電話會議將被錄音。現在我把電話交給金山雲資本市場高級總監左傑奇先生。傑奇，請開始。

Thank you, operator. Hello, everyone, and thank you for joining us today. Kingsoft Cloud's Second Quarter 2026 earnings release was issued earlier today and is available on our IR website and through PR Newswire. Joining us today are Mr. Zou Tao, Chairman and CEO; Ms. Li Yi, CFO; Mr. Liu Tao, Senior Vice President; Mr. Kaiyan Tian, Senior Vice President; [Ms. Yu Jun], Vice President; [Mr. Zhu Rilong], Associate Vice President; and [Mr. Kuang Jian], Board Secretary and Associate Vice President. Mr. Zou will discuss our business performance and key developments, followed by Ms. Li with a review of our financial results. Management will then take your questions. Consecutive interpretation will be provided for convenience and for reference only.

謝謝接線員。各位好，感謝大家今天加入我們。金山雲 2026 年第二季度業績新聞稿已於今日稍早發布，可於我們的投資者關係網站及 PR Newswire 查閱。今天與會的有：董事長兼首席執行官鄒濤先生；首席財務官李怡女士；高級副總裁劉濤先生；高級副總裁田開顏先生；[于君]女士，副總裁；[朱日龍]先生，副總裁助理；以及[匡健]先生，董事會秘書兼副總裁助理。鄒先生將介紹我們的業務表現與重點進展，隨後由李女士回顧財務結果。之後管理層將回答各位提問。為方便起見將提供交替傳譯，僅供便利與參考。

In the event of any discrepancy, management's statements in the original language will prevail. Before we begin, I would like to remind you that today's call contains forward-looking statements made under the safe harbor provisions of US Private Securities Litigation Reform Act of 1995. These statements involve risks and uncertainties, and actual results may differ materially from those expressed or implied by the forward-looking statements. Additional information concerning factors that would cause actual results to differ materially is included in the company's filings with the US SEC. The company undertakes no obligation to update any forward-looking statements, except as required by applicable law. Unless otherwise stated, all financial figures discussed on today's call are denominated in renminbi. With that, it is my pleasure to turn the call over to our Chairman and CEO, Mr. Zou.

如有任何差異，以管理層使用原語言所作陳述為準。在開始之前，我想提醒各位，今天的電話會議包含根據 1995 年《美國私人證券訴訟改革法案》安全港條款所作的前瞻性陳述。此等陳述涉及風險與不確定性，實際結果可能與前瞻性陳述所明示或暗示者存在重大差異。關於可能導致實際結果出現重大差異之因素的更多資訊，已載於公司向美國證券交易委員會（SEC）提交的文件中。除適用法律要求外，公司不承擔更新任何前瞻性陳述之義務。除非另有說明，今天電話會議中討論的所有財務數據均以人民幣計值。接下來，我很高興把電話交給我們的董事長兼首席執行官鄒先生。

Mr. Zou, please go ahead.

鄒先生，請開始。

(interpreted) Hello, everyone, and welcome to Kingsoft Cloud's Second Quarter 2026 Earnings Call. I am Zou Tao, CEO of Kingsoft Cloud. This quarter, we saw further evolution in the AI cloud market. The rapid growth of the open source model ecosystem is creating significant opportunities for neutral cloud providers. At the same time, our long-held vision of bringing AI to every industry is becoming a reality through a combination of Model as a Service, Agent as a Service and FTE services. Against this backdrop, Kingsoft Cloud remains committed to technology leadership and high-quality sustainable growth. We are accelerating the development of our AI cloud, MaaS and FTE businesses with encouraging progress. First, AI continues to drive strong revenue growth. Total revenue reached a record of RMB3.07 billion, up 31% year-over-year. AI cloud gross billings increased 82% to RMB1.33 billion and accounted for 56% of public cloud revenue. MaaS revenue also grew strongly with Q2 revenue up more than 12 times from the Q1 level.

（傳譯）各位好，歡迎參加金山雲 2026 年第二季度業績電話會議。我是金山雲首席執行官鄒濤。本季度，我們看到 AI 雲市場進一步演進。開源模型生態的快速成長，正在為中立雲服務商創造重大機遇。同時，我們長期以來「讓 AI 走進每個行業」的願景，正透過 Model as a Service、Agent as a Service 與 FTE 服務的組合逐步成為現實。在此背景下，金山雲仍將堅持技術領先與高品質、可持續成長。我們正加速推進 AI 雲、MaaS 與 FTE 業務發展，並取得令人鼓舞的進展。第一，AI 持續帶動收入強勁成長。總收入達到創紀錄的人民幣 30.7 億元，同比增長 31%。AI 雲總開票額（gross billings）增長 82% 至人民幣 13.3 億元，佔公有雲收入的 56%。MaaS 收入亦強勁成長，第二季度收入較第一季度水準提升超過 12 倍。

Second, profitability improved significantly. Adjusted gross margin rose to 15.4%, up 2.4 percentage points quarter-over-quarter. Operating profit turned positive for the first time with adjusted operating margin reaching a record high of 4.0%. This reflects our continued efforts to capture AI opportunities, improve revenue quality and drive greater operating efficiency. Third, our customer mix continued to improve with stronger momentum both within and outside our ecosystem. Revenue from the Xiaomi and Kingsoft ecosystem reached RMB810 million, up 28% year-over-year and accounting for 26% of total revenue. Revenue from our top five non-ecosystem customers grew 51% -- our AI cloud business now serves a broad range of sectors, including Internet services, frontier AI labs, embodied AI, autonomous driving, AI for science, fintech, gaming and online video, to name a few. This diversified customer base supports continued growth while allowing us to allocate computing resources more flexibly and strengthen our pricing power and business resilience.

第二，盈利能力顯著改善。經調整毛利率提升至 15.4%，環比上升 2.4 個百分點。經調整經營利潤首次轉正，經調整經營利潤率達到創紀錄的 4.0%。這反映了我們持續把握 AI 機遇、提升收入品質並推動更高營運效率的努力。第三，客戶結構持續優化，生態內外動能均更為強勁。來自小米與金山生態的收入達人民幣 8.10 億元，同比增長 28%，佔總收入的 26%。我們前五大非生態客戶收入增長 51%——我們的 AI 雲業務目前服務於廣泛行業，包括互聯網服務、前沿 AI 實驗室、具身智能、自動駕駛、AI for science、金融科技、遊戲與線上視頻等。多元化的客戶基礎既支撐持續成長，也使我們能更靈活地配置算力資源，並強化定價能力與業務韌性。

Now let me walk you through our business progress in the second quarter of 2026. In Public Cloud, revenue reached RMB2.36 billion, up 45% year-over-year. First, Xiaomi continues to expand AI across its Human x Car x Home ecosystem, while WPS AI continues to advance. As the only strategic cloud platform for the Xiaomi and Kingsoft ecosystem, we see substantial AI-driven growth opportunities. In June, our shareholders approved a further increase in the annual caps for connected transactions with Xiaomi. The combined caps for 2026 and 2027 now total RMB10 billion, 39% higher than before the adjustment.

下面我將介紹我們在 2026 年第二季度的業務進展。在公有雲方面，收入達人民幣 23.6 億元，同比增長 45%。第一，小米持續在其「人 × 車 × 家」生態中擴展 AI 應用，同時 WPS AI 也在持續推進。作為小米與金山生態唯一的戰略雲平台，我們看到顯著的 AI 驅動成長機會。6 月，我們的股東批准進一步提高與小米關聯交易的年度上限。2026 年與 2027 年合計上限現為人民幣 100 億元，較調整前提高 39%。

In the first half, public cloud revenue from Xiaomi and Kingsoft grew 54% year-over-year. Second, we further strengthened the MaaS capabilities of our StarFlow platform. StarFlow now supports 120 models with major new models launched on the platform in sync with their market release and serves more than 230 enterprise customers. Third, we deepened cooperation with leading customers in emerging sectors. We delivered large-scale computing clusters to leading embodied AI and autonomous driving customers, supporting rapid model iteration and expanded our cooperation with a leading AI for science customer to support the growth of this new business. In Enterprise Cloud, revenue reached RMB710 million, -- in public services, we signed an agreement with the Nanjing Communications Administration of the Yangtze River to build Yanghai Cloud, a dedicated digital infrastructure platform for Yangtze River Shipping.

上半年，小米與金山帶來的公有雲收入同比增長 54%。第二，我們進一步強化了 StarFlow 平台的 MaaS 能力。StarFlow 目前支援 120 個模型，並可與其市場發布同步在平台上線主要新模型，服務超過 230 家企業客戶。第三，我們加深了與新興領域頭部客戶的合作。我們向領先的具身智能與自動駕駛客戶交付大規模算力集群，支持其快速模型迭代；並擴大與一家領先 AI for science 客戶的合作，以支持該新業務的成長。在企業雲方面，收入達人民幣 7.10 億元，——在公共服務領域，我們與長江南京通信管理局簽署協議，共建「揚海雲」，作為服務長江航運的專用數位基礎設施平台。

We also formed a strategic partnership with the Wuhan Municipal Data Bureau and Wuhan Cloud across computing resource interconnection, digital governance, intelligent computing applications and ecosystem development. In digital health, we are leading a project under the National Key R&D program on biology and information integration to develop a cloud-based virtual surgery platform, which has been deployed in more than 30 hospitals nationwide. In enterprise services, we deepened our cooperation with Yunshang Gansu to jointly build and operate the Gansu Provincial Public Services Cloud under an integrated investment construction and operations model. In products and technology, we continued to upgrade our full stack AI capabilities for intelligent computing and AI application deployment. This quarter, we further optimized the model deployment on [StarFlow MaaS] for high concurrency inference, significantly improving throughput for several core models and enabling more granular access usage and model level management.

我們亦與武漢市數據局及武漢雲建立戰略合作夥伴關係，合作範圍涵蓋算力資源互聯互通、數位治理、智算應用與生態建設。在數位健康方面，我們牽頭承擔國家重點研發計畫中「生物與資訊融合」方向的一個項目，開發基於雲端的虛擬手術平台，已在全國 30 多家醫院部署。在企業服務方面，我們加深與雲上甘肅的合作，採用投建運一體化模式，共同建設並運營甘肅省政務公有雲。在產品與技術方面，我們持續升級面向智算與 AI 應用部署的全棧 AI 能力。本季度，我們進一步優化了 [StarFlow MaaS] 上的模型部署以支援高併發推理，顯著提升多個核心模型的吞吐量，並實現更細粒度的存取用量與模型層級管理。

We also launched AgentKit, providing secure sandbox, knowledge and memory management, and evaluation and governance tools to help enterprises build production-grade AI agents. At the same time, we are making general purpose cloud products such as database and storage easier for agents to access and use. We enhanced the StarFlow training and inference platform with more flexible resource scheduling, sharing and allocation for training and fine-tuning workloads, improving utilization and reducing development and operating costs. For private deployment of domestic AI infrastructure, our Galaxy Stack platform completed deep integration and full life cycle visual management for multiple mainstream domestic AI chips.

我們也推出了 AgentKit，提供安全的沙箱、知識與記憶管理，以及評估與治理工具，協助企業打造可用於生產環境的 AI 代理。同時，我們正讓資料庫與儲存等通用雲端產品更容易被代理存取與使用。我們強化了 StarFlow 訓練與推理平台，為訓練與微調工作負載提供更彈性的資源排程、共享與配置，提升資源使用率並降低研發與營運成本。針對國產 AI 基礎設施的私有化部署，我們的 Galaxy Stack 平台已完成對多款主流國產 AI 晶片的深度整合與全生命週期可視化管理。

Looking ahead, we will continue to capture opportunities both within and outside our ecosystem, improve the operating efficiency of our computing assets and strengthen our profitability and cash generation capability amid AI industry tailwinds. We remain committed to creating long-term sustainable value for our customers, shareholders and society.

展望未來，我們將持續把握生態系內外的機會，在 AI 產業順風之下提升算力資產的營運效率，並強化獲利能力與現金創造能力。我們仍致力於為客戶、股東與社會創造長期且可持續的價值。

With that, I will hand the call over to our CFO, Li Yi, who will review our second quarter financial results. Thank you.

接下來，我將把電話會議交給我們的財務長李毅，他將回顧我們第二季的財務業績。謝謝。

Thank you, Mr. Zou and Mr. Tian, and thank you all for joining the call today. I will now discuss the second quarter financial results used RMBas currency. Before we walk through the details of the financial results for the second quarter, I would like to highlight the following aspects. First, our quarter revenue reached over RMB3 billion for the first time in our company's history, up year-over-year for the ninth consecutive quarter. In particular, our AI cloud gross billing increased 82% year-over-year to RMB1.33 billion, accounting for over 43% of our total revenue versus 31% a year ago. This reflects a continued structural shift in our business mix towards AI. Second, our profitability has improved.

謝謝鄒先生與田先生，也感謝各位今天參與本次電話會議。接下來我將以人民幣作為貨幣單位，說明第二季財務業績。在我們逐項說明第二季財務結果之前，我想先強調以下幾點。第一，我們本季營收首次在公司歷史上突破人民幣30億元，並已連續第九個季度實現年增。尤其是，我們的 AI 雲端總開票金額（gross billing）年增 82% 至人民幣13.3億元，占總營收比重超過 43%，高於一年前的 31%。這反映出我們的業務組合持續朝 AI 方向結構性轉移。第二，我們的獲利能力有所改善。

Our adjusted gross margin was 15.4%, up 2.4 percentage points quarter-over-quarter and 0.5 percentage points year-over-year. Our adjusted EBITDA margin reached 36%, up from 17% in the same quarter last year and 28% last quarter. Notably, we returned to breakeven at operating income level this quarter and recorded an adjusted operating profit margin of 4%. This outcome validates our ability to turn strong AI business demand into healthy profit growth. Third, we continue to invest to accelerate the build-out of our AI compute capacity. Capital expenditures together with right-of-use assets obtained through third-party financing and finance leases reached RMB3.3 billion this quarter versus RMB2.9 billion in last quarter and RMB2.8 billion in the same quarter last year.

我們的調整後毛利率為 15.4%，較上季提升 2.4 個百分點，較去年同期提升 0.5 個百分點。我們的調整後 EBITDA 利潤率達到 36%，高於去年同期的 17% 與上季的 28%。值得注意的是，我們本季在營業利益層面回到損益兩平，並錄得 4% 的調整後營業利潤率。這一結果驗證了我們能將強勁的 AI 業務需求轉化為健康的利潤成長。第三，我們持續投資以加速建置 AI 算力產能。本季資本支出加上透過第三方融資與融資租賃取得的使用權資產合計達人民幣33億元，較上季的人民幣29億元及去年同期的人民幣28億元有所增加。

Now let me walk you through our financial results for the second quarter of 2026. This quarter, total revenue were RMB3,072 million, up 31% year-over-year or 40% quarter over quarter -- of this revenues from public cloud services were RMB2,358 million, up 45% from RMB1,625 million in the same quarter last year. Revenues from enterprise cloud services reached RMB714 million compared with RMB724 million in the same quarter last year, down slightly by 1% year-on-year. Total cost of revenues was RMB2,606 million, representing a 30% year-over-year increase, mainly due to a continued investment in AI cloud infrastructure. IDC costs increased by 23% year-over-year from RMB803 million to RMB990 million this quarter. The increase was mainly due to the increase of rack services. Depreciation and amortization costs increased by 75% year-over-year from RMB552 million in the same quarter of 2025 to RMB964 million this quarter, largely due to the depreciation of newly acquired AI infrastructure, including servers and network equipment.

接下來我將帶各位回顧 2026 年第二季的財務結果。本季總營收為人民幣3,072百萬元，年增 31%，或季增 40%——其中，公有雲服務營收為人民幣2,358百萬元，較去年同期的人民幣1,625百萬元成長 45%。企業雲服務營收為人民幣714百萬元，較去年同期的人民幣724百萬元略降，年減 1%。本季營收成本合計為人民幣2,606百萬元，年增 30%，主要由於我們持續投資 AI 雲端基礎設施。IDC 成本年增 23%，由人民幣803百萬元增至本季的人民幣990百萬元；增加主要來自機櫃服務的提升。折舊與攤銷成本年增 75%，由 2025 年第二季的人民幣552百萬元增至本季的人民幣964百萬元，主要由於新取得的 AI 基礎設施（包括伺服器與網路設備）帶來的折舊。

Solution development and services costs increased by 4% year-over-year from RMB564 million in the same quarter of 2025 to RMB586 million this quarter. The modest increase was mainly due to higher costs incurred in AI transformation in solution development and delivery. Fulfillment costs and other costs were approximately RMB66 million in total this quarter versus RMB92 million in the same quarter last year. Our adjusted gross profit for the quarter was RMB472 million, increased by 35% year-over-year and 34% quarter-over-quarter. Adjusted gross margin was 15.4%, up from 14.9% in the same quarter last year and from 13% last quarter. The increase was driven by higher gross margin in public cloud business, thanks to strong AI demand tailwinds.

解決方案開發與服務成本年增 4%，由 2025 年第二季的人民幣564百萬元增至本季的人民幣586百萬元。這一溫和增幅主要來自解決方案開發與交付過程中 AI 轉型所產生的較高成本。本季履約成本及其他成本合計約人民幣66百萬元，低於去年同期的人民幣92百萬元。本季調整後毛利為人民幣472百萬元，年增 35%，季增 34%。調整後毛利率為 15.4%，高於去年同期的 14.9% 與上季的 13%。毛利率提升主要由公有雲業務毛利率提高所帶動，受惠於強勁的 AI 需求順風。

On the expense side, excluding share-based compensation expenses, our total adjusted operating expense was RMB391 million, a decrease from RMB561 million in the same quarter last year and from RMB455 million last quarter, mainly reflecting our disciplined cost and expense control, which our adjusted research and development expenses were RMB184 million, up 1% year-over-year.

在費用方面，剔除股份基礎給付費用後，我們的調整後營業費用總額為人民幣391百萬元，低於去年同期的人民幣561百萬元及上季的人民幣455百萬元，主要反映我們嚴格的成本與費用控管。其中，我們的調整後研發費用為人民幣184百萬元，年增 1%。

Adjusted selling and marketing expenses were RMB102 million, down 7% year-over-year. Adjusted general and administrative expenses were RMB105 million, down 51% year-over-year, largely due to lower credit loss expenses. Our adjusted operating profit was RMB124 million, profit from adjusted operating loss of RMB166 million in the same period last year. This improvement was primarily driven by the expansion of our revenue scale, higher gross margin and enhanced operating efficiency.

調整後銷售與行銷費用為人民幣102百萬元，年減 7%。調整後一般及行政費用為人民幣105百萬元，年減 51%，主要由於信用損失費用較低。我們的調整後營業利益為人民幣124百萬元，較去年同期調整後營業虧損人民幣166百萬元顯著改善。此改善主要由營收規模擴大、毛利率提升以及營運效率增強所帶動。

Adjusted operating profit margin was 4% this quarter compared with minus 7.1% in the same period last year and minus 2.2% last quarter. Our adjusted net loss was RMB6 million, down from RMB300 million in the same quarter last year and RMB237 million in previous quarter. Our non-GAAP EBITDA profit was RMB1,100 million increased by 171% from RMB406 million in the same quarter last year. Our non-GAAP EBITDA margin achieved 36% compared with 70% in the same quarter last year and 82% last quarter. It was mainly due to our improving gross profit as well as higher operation costs in our cost of debt as we accelerate our AI computing capacity build-out.

本季調整後營業利潤率為 4%，相較去年同期為負 7.1%，上季為負 2.2%。本季調整後淨虧損為人民幣6百萬元，較去年同期的人民幣300百萬元及前一季的人民幣237百萬元大幅收窄。我們的非 GAAP EBITDA 利潤為人民幣1,100百萬元，較去年同期的人民幣406百萬元成長 171%。非 GAAP EBITDA 利潤率為 36%，相較去年同期的 70% 與上季的 82% 有所下降，主要由於毛利改善的同時，為加速建置 AI 算力產能，我們的債務成本所帶來的營運成本上升。

As of June 30, 2026, our cash and cash equivalents totaled RMB4,674 million compared with RMB4,904 million as of March 31, 2026. The modest decrease was mainly due to our continued investment in AI infrastructure to support business growth. Looking ahead, we aim to capitalize on the explosive growth in AI demand by further investing in infrastructure, expanding our product and service offerings, managing credit and liquidity risk and improving operating efficiency. We remain committed to our AI strategy and continue to deliver high-quality growth to our shareholders. Thank you all.

截至 2026 年 6 月 30 日，我們的現金及現金等價物合計為人民幣4,674百萬元，較 2026 年 3 月 31 日的人民幣4,904百萬元略有下降。這一小幅下降主要由於我們持續投資 AI 基礎設施以支持業務成長。展望未來，我們將透過進一步投資基礎設施、擴大產品與服務供給、管理信用與流動性風險並提升營運效率，來把握 AI 需求爆發式成長的機會。我們將持續堅定推進 AI 策略，並為股東帶來高品質成長。謝謝各位。

So this concludes our prepared remarks. We will now begin the Q&A session. If possible, please ask your questions in both Mandarin and English. So operator, please proceed.

以上為我們事先準備的發言，至此告一段落。我們現在開始問答環節。如可行，請以中文與英文各提問一次。那麼請接線員開始。

(Operator Instructions)

（接線員指示）

Liping Zhao, CICC.

趙麗萍，中金公司。

(spoken in foreign language) I got two questions on your MaaS business. First, how will improvements in open source model capabilities affect the company's MaaS business? Based on your observations, what's the current usage growth trend and which use cases are driving it most? And second, given the payback period for the MaaS business might be shorter, will the company allocate more resources to it?

（以外語發言）我有兩個關於你們 MaaS 業務的問題。第一，開源模型能力的提升將如何影響公司的 MaaS 業務？根據你們的觀察，目前使用量的成長趨勢如何，主要由哪些使用情境（use cases）在驅動？第二，鑑於 MaaS 業務的回收期可能較短，公司是否會投入更多資源到該業務？

(interpreted) So just to quickly translate. So this answer comes from our SVP, Mr. Liu Tao. So in relation to your first question, the development in open source large language models have mainly three impacts, number one is that we're seeing very big demand coming from (inaudible). Traditionally, foreign models have been taking the lead in this area. However, once we have seen the launch of GLM and K3, this kind of high-performance models, we're seeing increasingly users from Mainland China adopting and using this Made in China large language model.

（口譯）我先快速翻譯一下。以下回答來自我們的資深副總裁劉濤先生。針對第一個問題，開源大型語言模型的發展主要帶來三個影響：第一，我們看到來自（聽不清）的需求非常強勁。過去在這個領域通常是海外模型領先；但在 GLM 與 K3 這類高效能模型推出後，我們看到越來越多中國大陸用戶開始採用並使用這些「中國製造」的大型語言模型。

And secondly, the increasing use of agentic scenarios also brought change to our business. And with that, we have launched, as mentioned in the prepared remarks, the agentic product to satisfy such needs. And thirdly, it is worth mentioning that in terms of day-to-day routine tasks and workloads, the choice usually is the price for value kind of models, which are essentially the Chinese models. So that is why this development of open source large language model is actually beneficial for our business.

第二，代理式（agentic）場景的使用增加也為我們的業務帶來變化。基於此，我們如同在事先準備的發言中所提到的，推出了代理式產品以滿足相關需求。第三，值得一提的是，在日常例行任務與工作負載方面，客戶通常會選擇性價比（price-for-value）更高的模型，而這些本質上多為中國模型。因此，開源大型語言模型的發展其實對我們的業務是有利的。

And your second question regarding the balance between MaaS business and the computing power. So we basically have different business models for these two business. For computing power business, essentially, once we sell the computing power, the utilization is by nature 100%, and we usually come with long-term contracts to secure the utilization throughout a prolonged period of time, and therefore, it's relatively safe, so to speak. But for the MaaS business, it is subject to quite a few factors, including the fluctuation of the token price, the launching of new models, which the customers might prefer to use and also the operating efficiency that we're able to achieve in doing MaaS business.

至於第二個問題，關於 MaaS 業務與算力業務之間的平衡：這兩項業務本質上採用不同的商業模式。對算力業務而言，一旦我們售出算力，其利用率在本質上就是 100%，而且通常會搭配長期合約，以確保在較長期間內的利用率，因此相對而言較為「安全」。但 MaaS 業務則會受到多項因素影響，包括 token 價格波動、新模型的推出（客戶可能更偏好使用新模型），以及我們在經營 MaaS 業務時能達到的營運效率。

So therefore, we generally balance these two business models and hope to have each one of them complement the other one. So we generally dynamically evaluate these two business and try to decide how much resources to allocate.

因此，我們通常會在這兩種業務模式之間做平衡，並希望兩者能相互補充。我們會動態評估這兩項業務，並據此決定資源配置的比例。

Thank you, Taozong. That's very helpful.

謝謝濤總，這些資訊非常有幫助。

Wenting Yu, CLSA.

俞文婷，里昂證券（CLSA）。

(spoken in foreign language) The first question is that since June, how has the chip procurement progressed in recent months? And what's your latest full-year CapEx guidance? And the second question is about the enterprise cloud. This segment of revenue has decelerated in the past two quarters. How should we think about the full-year enterprise cloud growth? And what's the AI transformation and medium-term positioning for this segment?

（以外語發言）第一個問題是，自 6 月以來，近幾個月晶片採購進展如何？你們最新的全年資本開支（CapEx）指引是多少？第二個問題關於企業雲：該分部收入在過去兩個季度有所放緩。我們應如何看待全年企業雲的成長？以及該分部在 AI 轉型與中期定位方面是什麼？

(interpreted) So allow me to quickly translate. So the answer comes from our SVP, Mr. Kaiyan Tian. So 3 points. Number one, actually, since 2023, it's been three years, and the market has always been hearing voices about the limited supply. So I would say this is actually a new norm. The such supply difficulty is actually a long-term kind of situation. But secondly, we should also be aware of the fact that despite of those constraints, financial constraints, the Chinese cloud computing or AI industry development has not been restricted or largely restricted by that. And the way that we actually tackle with such situation is that we try to increase the number of business partners that we work with. We try to increase the number of suppliers we work with. And we also work with the increasing the compatibility of Made in China chips. You are all very well -- very much aware of the -- recently, many of the Made in China chips are becoming public, and they are particularly good in use cases such as model inference.

（口譯）我先快速翻譯一下。以下回答來自我們的資深副總裁田開顏先生，主要三點。第一，其實自 2023 年以來已經三年了，市場一直在談供應受限的問題。我認為這其實已成為一種新常態，供應困難是長期狀態。第二，我們也應注意到，儘管存在這些限制與資金方面的約束，中國雲端運算或 AI 產業的發展並未因此受到限制或大幅限制。我們應對的方式是：增加合作的業務夥伴數量、增加供應商數量，並提升國產晶片的相容性。大家也很清楚，近期有許多國產晶片陸續公開亮相，且在模型推理等使用情境中特別好用。

Now number three, I would like to say that when you look at the CapEx number, from a month-to-month basis, it is usually quite volatile. And I have to say that the purchasing number because of it's usually a large chunk of money in a relatively small number of purchases. So the purchasing number, if you look at it on a monthly basis, it's actually not a linear number. So I would say that for our whole year CapEx estimate, it should still be in line with what we have been expecting. And our CFO, Li Yi, should be able to give you more details in that regard.

第三，關於 CapEx 數字，如果以月度來看通常波動很大。我也必須說，採購金額往往是以相對少數的採購筆數對應一大筆資金，因此若按月觀察，採購金額並不是線性變化。所以我認為，我們對全年 CapEx 的估計仍將與先前預期一致；我們的財務長李毅先生也可以在這方面提供更多細節。

Our CapEx [Ventra] include capitalized assets for lease arrangements, reaching RMB6.2 billion in the first half of 2026, accounting for over 75% of our full-year CapEx last year, where July data cannot fully represent the third quarter of all trend, it clearly shows tangible growth acceleration. Accordingly, we maintain our full-year CapEx base case unchanged at RMB15 billion. Thank you, Tian.

我們的 CapEx（[Ventra]）包含租賃安排的資本化資產，2026 年上半年達到人民幣 62 億元，已占我們去年全年 CapEx 的 75% 以上。雖然 7 月數據無法完全代表第三季的整體趨勢，但它清楚顯示實質成長正在加速。因此，我們維持全年 CapEx 基準情境不變，仍為人民幣 150 億元。謝謝你，田先生。

We will take our next question.

我們來進行下一個問題。

Sorry, we need to continue for another question.

抱歉，我們還需要再繼續回答一個問題。

Apologies.

抱歉。

(interpreted) Okay. So this answer comes from our VP, (inaudible). So generally, I don't think -- although we are seeing relatively slow growth in the enterprise cloud segment, I would say it is not the right way to look at it from a linear extrapolation perspective. I will give you three reasons. I think number one, just to explain why we're seeking -- looking at relative weakness in this regard is that the upstream supply pricing hike, which changed quite significantly in recent quarters, has affected the -- our prospective customers, essentially the SOE companies and also the government agencies to -- they have to frequently adjust their budgeting process, which delayed their decision-making process. So that's number one.

（口譯）好的。以下回答來自我們的副總裁（聽不清）。整體而言，雖然我們看到企業雲分部的成長相對較慢，但我認為不應以線性外推的方式來看待。我提供三個原因。第一，解釋我們為何看到相對疲弱：上游供應端的價格上調在近幾個季度變化很大，影響了我們的潛在客戶——主要是國有企業以及政府機構——他們不得不頻繁調整預算流程，從而延後了決策進程。這是第一點。

And number two, you're all quite aware that the seasonality in enterprise cloud business is quite strong. Usually, the delivery and revenue recognition are concentrated in the second half of every year. So we have actually quite a strong pipeline to deliver in the second half of the year. And thirdly, this is actually a result of a proactive adjustment of our business structure, namely proactively from the project-based business model to operating-based business model where operating business model from a financial reporting perspective is automatically classified into public cloud. So this is not simply as it as a weakening of the enterprise cloud business. So that's the 3 points I would like to offer.

第二，大家都很清楚企業雲業務的季節性很強，通常交付與收入確認集中在每年的下半年。因此，我們在下半年其實有相當強的交付管線（pipeline）。第三，這其實是我們主動調整業務結構的結果，也就是主動從以專案為主的商業模式轉向以營運為主的商業模式；而從財務報表分類角度，營運型業務會自動被歸類到公有雲。因此，不能簡單把它視為企業雲業務走弱。以上是我想補充的三點。

Timothy Zhao from Goldman Sachs.

高盛的 Timothy Zhao。

(spoken in foreign language) My first question is regarding the MaaS business. Just wondering compared to the peers in the market, how do you think about the Kingsoft Cloud competitive advantage in the MaaS services in terms of the application scenarios, et cetera? And could you share more about the revenue recognition and the profitability profile of the MaaS service business?

（以外語發言）我的第一個問題是關於 MaaS 業務。想請教相較於市場上的同業，您如何看待金山雲在 MaaS 服務方面的競爭優勢，例如應用場景等？另外，能否多分享一些 MaaS 服務業務的收入確認方式以及獲利能力輪廓？

And second question is regarding the overall pricing trend in the AI cloud business. Just wondering if you can share what is the latest trend over the past couple of months? And what have you heard from the customers after you announced certain price hikes or discount reduction over the past few months and whether you are able to quantify the impact from the price hike to your overall AI cloud revenue growth?

第二個問題是關於 AI 雲業務的整體定價趨勢。想請教您能否分享過去幾個月最新的趨勢？以及在過去幾個月您宣布某些漲價或減少折扣之後，從客戶端聽到的回饋是什麼？另外，您是否能量化漲價對整體 AI 雲收入成長的影響？

(interpreted) So in relation to your question about the positioning, we do have a unique positioning in the MaaS business. Mainly, we're different from some of the full-stack cloud providers, which they have their in-house proprietary models. We do not have such models. And therefore, correspondingly, we do not have to sell those large language models that our affiliated companies have to offer. And as a result, we're able to actually sell and we actually encourage our sales team to sell the models that our customers like the most, for example, the GLM, et cetera. So that's number one.

（口譯）關於您提到的定位問題，我們在 MaaS 業務上確實有獨特的定位。主要是我們不同於一些全棧雲服務供應商，他們擁有自研的專有模型；我們沒有這類模型。因此，相應地，我們也不需要去銷售我們關聯公司所提供的大語言模型。結果是，我們實際上能夠銷售，並且也鼓勵我們的銷售團隊去銷售客戶最喜歡的模型，例如 GLM 等。這是第一點。

And secondly, it's quite important in today's market to have your proprietary or your own computing power, which is the only way that you can actually secure a significant profitability in this business.

第二點，在當前市場中，擁有專有或自有的算力非常重要，因為這是你在這個業務中實際上能夠確保顯著獲利能力的唯一方式。

So in relation to your question about the price hike, so there are basically two products or solutions that we have employed increasing price. Number one, that is storage and number two, that is computing power. So I'll talk about them separately, respectively. So in terms of storage, storage is usually the incremental amount of storage actually comes with the intelligent computing demand. That is a relatively small portion of the intelligent computing overall ticket size. And therefore, in the vast majority of the customers that we negotiate with, they are relatively easily accepted such price hike. In which case, as a result, we're actually able to not only -- in some cases, not only pass through the increase in our cost, but also increasing our profitability in that scenario.

關於您提到的漲價問題，我們基本上對兩類產品或解決方案採取了提價。第一是儲存，第二是算力。我會分別說明。就儲存而言，儲存通常是隨著智算需求而帶來的增量儲存，佔智算整體客單價的比例相對較小。因此，在我們與絕大多數客戶的談判中，他們相對容易接受這樣的漲價。在這種情況下，我們不僅能在部分案例中轉嫁成本上升，還能提升該情境下的獲利能力。

Number two, in terms of computing power, because of our specific capabilities, including PaaS capabilities as well as the operating maintenance and network capabilities, again, we are able to pass through that cost hike into our customers. In some of the cases, we also increased our profitability. And in this quarter, we have also some projects which we are doing managed services, which is an asset-light business model, and we look forward to seeing more of that coming to and reflect in the financial statements.

第二，就算力而言，由於我們具備特定能力，包括 PaaS 能力以及運維與網路能力，我們同樣能將成本上升轉嫁給客戶。在部分案例中，我們也提升了獲利能力。此外，本季度我們也有一些專案在做託管服務（managed services），這是一種輕資產的商業模式，我們期待看到更多此類業務落地並在財務報表中反映出來。

Wei Xiong, UBS.

瑞銀的 Wei Xiong。

(spoken in foreign language) Congrats on a solid quarter. Considering the proprietary models and user ecosystem of other cloud providers, how should we think about our long-term positioning in the cloud market and the sustainable margin level down the road?

（以外語發言）恭喜本季表現穩健。考量其他雲服務供應商的自研模型與用戶生態系，我們應如何看待公司在雲市場的長期定位，以及未來可持續的利潤率水準？

(interpreted) So we believe that a MaaS or cloud AI cloud service provider, it is important to be able to offer the top models, which the customers like and also stable services to our customers. So as mentioned, as a neutral cloud player, we are able to be in good relations with all of the top model providers, large language model labs and be able to provide the best model according to our customers' demands. And also, we're able to -- based on our technology capabilities, we're able to provide highly available and high reliable services to them based on -- out of the SLAs that we signed with them.

（口譯）我們認為，作為 MaaS 或 AI 雲服務供應商，重要的是能夠提供客戶喜歡的頂尖模型，以及穩定的服務。如前所述，作為中立的雲端玩家，我們能與所有頂尖模型供應商、大語言模型實驗室保持良好關係，並能依據客戶需求提供最佳模型。同時，基於我們的技術能力，我們也能依照與客戶簽署的 SLA，向其提供高可用性與高可靠性的服務。

I think thirdly, in relation to the profitability question you asked, it is important to work closely with the LLM firms, labs to -- for example, to optimize the inference of those models. And that would include the -- for example, working with them based on the undisclosed weighting of the models to increase our inference, model inference efficiency. In some of the cases, we're able to get to very close level or even reach the same level of the inference efficiency coming out from the LLM companies themselves. Thank you.

第三，關於您問到的獲利能力問題，與 LLM 公司、實驗室緊密合作也很重要——例如優化這些模型的推理（inference）。這包括例如基於模型未披露的權重（weighting）與他們合作，以提升我們的推理效率。在某些情況下，我們能達到非常接近、甚至與 LLM 公司自身相同水準的推理效率。謝謝。

Yang Liu, Morgan Stanley.

摩根士丹利的 Yang Liu。

(spoken in foreign language) Let me translate my question. I would like to ask on the two business model, computing power leasing and model as a service, what is the ROIC for these two business models? And what is the marginal change for the ROIC?

（以外語發言）我來翻譯一下我的問題。我想問兩種商業模式：算力租賃與模型即服務（MaaS），這兩種模式的 ROIC 分別是多少？以及 ROIC 的邊際變化如何？

Thank you, Yang. At this stage, we don't disclose separate ROIC on MaaS and AI computing power services because ROIC varies across projects driven by CapEx cycles, gross margin, fixed assets and depreciation policies. Overall, MaaS delivers much better profitability than AI computing power services at this stage. We have seen continued improvement in operating leverage as our AI business scales up, fixed costs are steadily diluted and our trailing 12 months adjusted operating profit has turned positive, driving a gradual recovery in our overall ROIC. We adhere to demand driven and disciplined AI investment strategy with a strong focus on capital efficiency. With the continuous business structure optimization and the maturing AI commercialization, I think our overall ROIC will keep improving steadily.

謝謝你，Yang。目前我們不披露 MaaS 與 AI 算力服務的單獨 ROIC，因為 ROIC 會因專案而異，並受資本開支（CapEx）週期、毛利率、固定資產與折舊政策等因素驅動。整體而言，現階段 MaaS 的獲利能力明顯優於 AI 算力服務。隨著我們 AI 業務規模擴大，我們看到營運槓桿持續改善，固定成本穩步被攤薄；我們過去 12 個月（TTM）的調整後營業利潤已轉正，帶動整體 ROIC 逐步回升。我們堅持需求驅動且紀律嚴明的 AI 投資策略，並高度重視資本效率。隨著業務結構持續優化以及 AI 商業化日趨成熟，我認為我們的整體 ROIC 將持續穩步改善。

Thank you. There are no further questions. Apologies for question-and-answer session. I will hand back for closing remarks.

謝謝。目前沒有其他問題。問答環節到此結束，敬請見諒。我把時間交回去做結語。

Okay. Thank you all for joining us today. If you have any further questions, please contact our IR team. So have a good evening. You may now disconnect. Thank you.

好的。感謝各位今天參與。如果您還有任何問題，請聯繫我們的投資者關係（IR）團隊。祝各位晚上愉快。您現在可以斷線。謝謝。

This concludes today's conference call. Thank you for participating. You may now disconnect.

今天的電話會議到此結束。感謝您的參與。您現在可以斷線。