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Good morning, ladies and gentlemen, and thank you for standing by for Kingsoft Cloud's first quarter 2026 earnings conference call. At this time, all participants are in a listen only mode. After management's prepared remarks, there will be a question and answer session. As a reminder, today's conference call is being recorded. I will now turn the meeting over to your host for today's call, Mr. Wayne Wang, Investor Relations of Kingsoft Cloud. Please proceed, Wayne.

Thank you, operator. Hello, everyone. Thank you for joining us today. Kingsoft Cloud's first quarter 2026 earnings release was just built earlier today and is available on our website at ir.ksyun.com, as well as on PR Newswire services. On the call today from Kingsoft Cloud, we have our Chairman and CEO, Mr. Tao Zou, CFO, Ms. Yi Li, Senior Vice President, Mr. Tao Liu, Senior Vice President, Mr. Kaiyan Tian, Vice President, Mr. Wang Zhenzheng, and Joint Company Secretary, Mr. Bo Tian. Mr. Joe will discuss our business strategies, operations, and other company highlights, followed by Ms. Li, who will discuss the financial performance. They will be available to answer your questions during the Q&A session that follows. There will be consecutive interpretations. All interpretations are for your convenience and reference purposes only. In case of any discrepancy, management statement in the original language will prevail.

Before we begin, I would like to remind you that this conference call contains forward-looking statements within the meaning of Section 21E of the Securities Exchange Act of 1934 as amended, and as defined in the U.S. Private Securities Litigation Reform Act of 1995. These forward-looking statements are based upon management's current expectations and current market and operating conditions, and relate to events that involve known and unknown risks, uncertainties, and other factors, all of which are difficult to predict, and many of which are beyond the company's control, which may cause the company's actual results, performance, or achievements to differ materially from those in the forward-looking statements. Further information regarding this and other risks, uncertainties, or factors are included in the company's filings with the U.S. SEC.

The company does not undertake any obligation to update any forward-looking statement as a result of new information, future events, or otherwise, except as required under applicable law. Finally, please note that unless otherwise stated, all financial figures mentioned during this conference call are denominated in RMB. It is now my pleasure to introduce our Chairman and CEO, Mr. Zou. Please go ahead.

Hello, everyone. Welcome to Kingsoft Cloud's first quarter 2026 earnings call. I am Kingsoft Cloud CEO Tao Zou. Since 2026, with the further popularization of AI coding and the explosion of AI intelligent agents, AI has truly started to transition from chat-oriented to action-oriented, driving both model inference and training demands to soar, further opening up the ceiling for the cloud computing industry. This quarter, Kingsoft Cloud continues to firmly push forward its high-quality, sustainable development strategy. On one hand, we have strengthened our computing, cloud infrastructure, and training and promotion platform capabilities. On the other hand, we have deeply rooted in industry vertical scenarios and are fully committed to driving changes in the AI-generated world. First, the company has maintained a trend of high-quality growth. In terms of revenue scale, this quarter we achieved revenue of RMB 270 million, a year-on-year increase of 37.2%.

Both public cloud and industry cloud saw year-on-year growth, with public cloud revenue reaching RMB 200 million, a year-on-year increase of 47.5%. In terms of profitability, this quarter the company achieved adjusted net profit of RMB 350 million, a year-on-year increase of 8.6%. Adjusted EBITDA of RMB 750 million, a year-on-year increase of 134.7%. Adjusted EBITDA margin of 27.6%, an increase of 11.4 percentage points year-on-year. Second, computing continues to drive business growth. This quarter, computing business gross revenue reached RMB 100 million, a year-on-year increase of 90.1%, accounting for the first time over half of public cloud revenue, reaching 50.1%. token business revenue growth was particularly strong, 26 times that of January to April 2026. Third, ecosystem partnerships deepened. This quarter, revenue from Xiaomi and Kingsoft ecosystems reached RMB 840 million, a year-on-year increase of 68.9%, accounting for 31% of total revenue.

With Xiaomi enhancing investments in the human-home-car ecosystem and AI fields, bringing more business opportunities, we have revised the continuous related transaction cap with Xiaomi. Within the 2025 to 2027 three-year framework, Xiaomi-Kingsoft continuous related revenue cap reaches RMB 142 billion.

Good evening, everyone, and welcome to Kingsoft Cloud's first quarter 2026 earnings call. I am Tao Zou, CEO of Kingsoft Cloud. Since the beginning of 2026, the continued adoption of AI coding, together with the rapid rise of AI agents, have driven AI to evolve from chat-oriented to action-oriented use cases.

This shift is fueling concurrent growth in both model inference and training demand, further expanding the ceiling of the cloud computing industry. This quarter, Kingsoft Cloud remains firmly committed to our high-quality and sustainable development strategy. We strengthened our AI cloud infrastructure and enhanced our training inference platform capabilities. In the meantime, we also further deepened our presence in industry-specific use cases, fully embracing AI's transformative role in reshaping the world. First, we sustained our momentum of high-quality growth. In terms of revenue, we recorded a total revenue of RMB 2.7 billion this quarter, representing a year-over-year growth of 37.2%. Both public cloud and enterprise cloud services achieved year-over-year growth. Among them, public cloud revenue reached RMB 2.0 billion, a year-over-year increase of 47.5%. In terms of profitability, our adjusted gross profit reached RMB 351 million, up 8.6% year-over-year.

Adjusted EBITDA was RMB 748 million, representing a year-over-year increase of 134.7%, with adjusted EBITDA margin reaching 27.6%, a significant year-over-year improvement of 11.4 percentage points. Second, AI cloud continued to drive the company's business growth. This quarter, AI cloud gross billings reached RMB 1.0 billion, a year-over-year increase of 90.1%, accounting for over half of public cloud revenue for the first time, reaching 50.1%. Notably, our token services delivered exceptionally strong growth, with April 2026 revenue skyrocketing to 53 times that of January. Third, ecosystem cooperation continued to strengthen. This quarter, revenue from Xiaomi and Kingsoft ecosystem reached RMB 838 million, a year-over-year increase of 68.9%, accounting for 31.0% of total revenue. As Xiaomi reinforces its investment in the human-car-home smart ecosystem and AI advancements, it brings forth more business opportunities for us. We plan to revise the annual caps for the continuing connected transactions with Xiaomi.

Following the adjustments, the revised annual caps with Xiaomi and Kingsoft for the continuing connected transactions under the three-year framework from 2025 to 2027 will reach RMB 14.2 billion.

下面我向大家具体介绍2026年第一季度的业务进展。公有云方面，本季度实现收入20亿元，同比增长47.5%。首先，我们继续紧跟小米金山生态内大体量高可见的云计算需求，促进长期全球战略合作，精心规划，持续打磨，打造具有长期竞争力的产品与解决方案。其次，我们获得生态外客户的广泛认可，凭借扎实的产品技术力、丰富的案例经验和良好的口碑，快速拓展客户覆盖的广度和业务合作深度。本季度，我们前五大生态外客户收入同比增长达66%，保持强劲的增长势头。我们为某独角兽自动驾驶客户提供智算服务，实现快速交付和运维响应，助力其海量数据处理和端到端神经网络的高效训练迭代，从而抢占市场先机。我们也凭借StarFlow平台卓越的资源调度、弹性扩缩容和模型场景能力，强力保障多家顶级互联网企业的token需求，抓住了推理业务爆发式增长的市场机遇。第三，我们实现了客户结构的显著优化。随着推理应用落地，我们的智算业务已覆盖了包括互联网、AI企业、智驾、物流、金融科技、游戏、音视频等在内的广泛行业，客户结构更加均衡。本季度，我们深度赋能某AI for Fin领域头部客户，全面保障客户新业务的快速发展与平台的稳定运行。我们还成功支持某头部物流科技企业开展大模型代码开发项目，通过灵活调用多个模型，为客户技术团队赋能，驱动研发效率与创新能力双提升。正是这种多样化的客户结构与业务布局，不仅带来收入规模的提升，也使我们能更灵活地错峰调度算力，提升资源利用率和盈利能力。

Now let me walk you through our business highlights for the first quarter of 2026. In terms of public cloud services, revenue reached RMB 2.0 billion this quarter, representing a year-over-year increase of 47.5%. First, we continued to closely align with the large-scale and highly visible cloud computing demand within the Xiaomi and Kingsoft ecosystem. With a long-term and global strategic perspective, we are carefully planning and continuously refining our offerings to build products and solutions with sustainable competitive advantages. Second, we earned broad recognition from customers outside the ecosystem, leveraging our solid product and technology capabilities, extensive project experience, and strong market reputation. We rapidly expanded both our customer coverage and the depth of business cooperation. This quarter, revenue from our top five non-ecosystem customers increased by 66% year-over-year, maintaining strong growth momentum.

We provided AI cloud services to a leading autonomous driving unicorn, enabling rapid deployment and responsive operations. This supported large-scale data processing and efficient end-to-end neural network training iterations, helping the customer capture early market opportunities. Through our StarFlow training and inference platform, with best-in-class resource scheduling, elastic scalability, and model deployment capabilities, we effectively supported the token demand of many top-tier internet companies, capturing the surge in inference-driven demand. Third, we achieved a meaningful optimization of our customer mix. As inference applications continue to scale, our AI business now spans a wide range of industries, including internet, AI companies, autonomous driving, logistics, fintech, gaming, and video streaming, resulting in a more balanced customer mix. This quarter, we deeply empowered a leading AI plus finance customer, ensuring its rapid business growth and stable platform operations.

We also supported a top logistics technology company in executing large-scale co-development projects, enabling its engineering teams through flexible multi-model utilization and significantly improving R&D efficiency and innovation capability. This diversified customer mix and business portfolio not only drive revenue growth, but also enable us to schedule computing resources more flexibly in off-peak periods, improve resource utilization, and enhance profitability. In terms of enterprise cloud services, revenue reached RMB 710 million this quarter, representing a year-over-year increase of 14.7%. In the public services sector, we launched the State-Owned Cloud platform in Shenzhen, focusing on the core needs of state-owned enterprises for high security, strong compliance, and strict data confidentiality, and fully enabling the digital and intelligent upgrade of office, business, and management use cases.

Leveraging Kingsoft Cloud's technology foundation, we adopted an integrated architecture that is provincial platform plus multi-prefecture and county platforms to build a supply chain public information platform in Hubei, enabling resources efficiency, data interoperability, and business collaboration, and have now supported the scaled migration of multiple municipal and county level platforms to the cloud. We also partnered with a leading domestic chip manufacturer to build a full stack intelligent computing service system spanning from underlying chips to upper layer applications, advancing the large scale commercial deployment of domestically developed intelligent computing cloud solutions and meeting the demand for high security and highly controllable computing capabilities. In the digital healthcare sector, we collaborated with Union Hospital affiliated with Tongji Medical College of Huazhong University of Science and Technology, one of the top-ranked hospitals in China on the Data Governance Project.

Through a systematic data management framework, we helped the hospital transition from fragmented management to standardized governance, setting a benchmark for the intelligent transformation of large medical institutions. We also signed a contract for a large-scale medical consortium platform project. Based on the Data Middle Platform, this project highlights our end-to-end professional capabilities in planning, designing, construction, and operation within the medical consortium space, laying the foundation for large-scale replication and rollout across healthcare institutions. In the enterprise services sector, we delivered a green energy operational platform for a leading clean energy service provider, enabling effective intensive management of large heavy-duty truck fleets. We further extended into the broader green and low-carbon industrial chain, exploring digital solutions for solid waste management and driving large-scale business deployment.

In terms of product and technology, we continue to stay committed to a technology-driven approach closely aligned with AI cloud demands and have comprehensively upgraded our products and services. During the quarter, in response to increasingly diverse model requirements, our StarFlow platform significantly expanded its model ecosystem. We added new API services for speech recognition and speech synthesis, expanded image and video generation models, and delivered a more refined user management experience. To address growing demand for AI agents, we launched Agent Engine, enabling customers to efficiently develop, deploy, and manage agents. We also introduced one-click agent deployment on our cloud hosts, supporting mainstream agent applications such as OpenClaw and Hermes, achieving deployment within five minutes and significantly lowering the barrier to adoption. For AI training and inference use cases, KS3 cache accelerator now delivers stable millisecond-level low latency, balancing performance and cost efficiency.

To meet the rising demand for private deployment of AI across industries, our Galaxy Stack platform reached a key milestone, adding StarFlow and security modules and completing a full stack closed-loop private deployment solution for AI cloud, covering cloud infrastructure, integrated training and inference, token services, and security guardrails. In terms of product and technology, we continue to stay committed to a technology-driven approach closely aligned with AI cloud demands and have comprehensively upgraded our products and services. During the quarter, in response to increasingly diverse model requirements, our StarFlow platform significantly expanded its model ecosystem. We added new API services for speech recognition and speech synthesis, expanded image and video generation models, and delivered a more refined user management experience. To address growing demand for AI agents, we launched Agent Engine, enabling customers to efficiently develop, deploy, and manage agents.

We also introduced one-click agent deployment on our cloud hosts, supporting mainstream agent applications such as OpenClaw and Hermes, achieving deployment within five minutes and significantly lowering the barrier to adoption. For AI training and inference use cases, KS3 cache accelerator now delivers stable millisecond-level low latency, balancing performance and cost efficiency. To meet the rising demand for private deployment of AI across industries, our Galaxy Stack platform reached a key milestone, adding StarFlow and security modules and completing a full stack closed-loop private deployment solution for AI cloud, covering cloud infrastructure, integrated training and inference, token services, and security guardrails. Overall, in this wave of AI innovation, from text generation to multi-modal capabilities, from training to inference, from chatting to real-world task execution, and from agents to claws, the pace of innovation and deepening applications continues to reinforce our conviction that AI will fundamentally reshape industries across the board.

Kingsoft Cloud will continue to uphold its strategy of high quality and sustainable development, increase investment, deepen its focus on core products and solutions, and continuously enhance profitability, creating greater long-term value for customers, shareholders, employees, and society. Next, I will hand over to our CFO, Ms. Li Yi, who will walk you through our first quarter financial results. Thank you.

Thank you, Tao Zou and class, and thank you all for joining the call today. I will now discuss the first quarter financial results using RMB as currency. Before we walk through the details of financial results for the first quarter, I would like to highlight the following aspects. First, our revenue has been consecutively achieved year-over-year growth for eight quarters, reaching RMB 2,704 million this quarter. For the first time, our AI business became the majority revenue driver, contributing over 50% of our public cloud services revenue and marking a pivotal structural shift in our growth mix. This quarter, our AI business revenue increased 91% year-over-year, amounting to RMB 998 million. Second, our adjusted gross profit was RMB 351 million, increased by 7% year-over-year, despite all our supply chain challenges.

Our adjusted EBITDA margin was 28%, increased by 11 percentage points year-over-year, thanks to our AI revenue growth. Third, in light of strong demand across diverse sectors, we remain steadfast in investing in our infrastructure. Our capital expenditures and leased assets obtained in combination grew 38% year-over-year to CNY 3 billion this quarter. We expect to continue to invest to facilitate further business expansion throughout the year. Now I will walk you through our financial results for the first quarter of 2026. This quarter, total revenues were CNY 2,704 million. Of this, revenues from public cloud services were CNY 1,996 million, up 46% from CNY 1,353 million in the same quarter last year. Revenues from enterprise premium services reached CNY 707 million, up 50% from CNY 616 million in the same quarter last year.

Total cost of revenues was RMB 2,358 million, up 43% year-over-year, which was mainly due to our investment into AI computing resources. IT cost increased by 26% year-over-year from RMB 723 million to RMB 911 million this quarter. The increase was mainly due to increase of rack services, which served the expanding AI business. Depreciation and amortization costs increased from RMB 379 million in the same quarter of 2025 to RMB 890 million this quarter. The increase was mainly due to the depreciation of newly acquired and leased servers and network equipment, which were mainly related to AI business. Solution development and services costs increased by 40% year-over-year from RMB 505 million in the same quarter of 2025 to RMB 575 million this quarter. The increase was mainly due to the solution personal expansion of Camelot. Financing cost and other cost was RMB 251 million this quarter.

Our adjusted gross profit for the quarter was CNY 351 million, increased by 7% year-over-year, and decreased by 24% quarter-over-quarter. Adjusted gross margin decreased from 70% last quarter to 30% this quarter. The decrease was mainly due to the higher cost of server along with expansion of our AI business, as well as upfront cost incurred for future revenue-generating activities with certain customers. On the expense side, excluding share-based compensation expenses, our total adjusted operating expenses were CNY 455 million, remaining stable compared with the same quarter last year and last quarter, of which our adjusted R&D expenses were CNY 184 million, decreased by 8% from the same quarter last year. Adjusted selling and marketing expenses were CNY 112 million, increased by 4% year-over-year. Adjusted general and administrative expenses were CNY 151 million, increased by 34% year-over-year.

Our adjusted operating loss was RMB 60 million, increased by 7% from adjusted operating loss of RMB 56 million in the same period last year. The improvement was mainly due to the expansion of revenue scale. Adjusted operating loss margin decreased from 3% in the same period last year to 2% this quarter, representing a decrease of 0.6 percentage points. Our non-GAAP EBITDA profit was RMB 748 million, increased by 135% from RMB 390 million in the same quarter last year. Our non-GAAP EBITDA margin achieved 28%, compared with 16% in the same quarter last year. It was mainly due to our strong commitment to AI cloud computing development and strategic adjustment of business structure. This quarter, our capital expenditures, including those financed by third parties and right of use assets obtained in exchange for financially settled leases, were RMB 2,985 million.

Looking ahead, we aim to capitalize on the explosive growth in demand by further investing in infrastructure, enhancing service stability, managing liquidity risk, and improving operating efficiency. We remain focused on AI-driven strategies, providing customers with high-value-added cloud services. That's all for the introduction of our operational and financial results. Thank you all.

This concludes our prepared remarks. Thank you for your attention. We are now happy to take your questions. Please ask your questions in both Mandarin and English if possible. Operator, please go ahead.

Thank you. We will now begin the question and answer session. If you wish to ask a question, please press star 11 on your telephone and wait for your name to be announced. To withdraw your question, please press star 11 again. We will take our first question, and the question comes from Liping Zhao from CICC. Please go ahead. Your line is open.

周总、李总晚上好，恭喜公司获得非常好的业绩。然后我这边有两个问题，第一个问题是关于我们StarFlow MaaS平台的，因为刚刚周总提到说StarFlow的收入的话，4月份比1月份同比提升了53倍，这个增长还是非常强的。那想请周总说一说目前这块业务大概我们的想法是怎么样的，它的收入体量和利润率水平如何？未来怎么看整个业务的一个收入规模，我们怎么展望它的想做到什么样的一个水平吧。然后第二个问题是想问一下关于我们公有云里面AI的这部分收入，因为我们也都知道上游无论是芯片和存储的价格都是上浮了不少，那同时下游的这个需求也是非常的旺盛，那么和去年这个Q4相比，我们看到今年的Q1和Q2新签的订单的情况，平均价格是否有了一些提升？那么这个提升的幅度如何？我自己翻译一下。Good evening, Tao Zou and Ms. Li.

Thanks for taking my questions and congrats on another strong quarter. I have two questions. The first one is relating to your StarFlow MaaS platform. Tao Zou mentioned that the revenue of the MaaS platform increased 53 times from January to April. Could you share the current revenue scale and margin levels? What's management's outlook on this business? The second question is about the AI pricing. Compared to the fourth quarter of 2025, have there been increases in the average pricing for the newly signed public cloud contracts in the first quarter and second quarter of this year? If so, by how much? Thank you.

丽萍你好，因为今天两个分管的SVP都在场，这两个问题我就请他们来回答一下。第一个问题请刘涛回答一下。

好的，丽萍，我来说一下。StarFlow实际上我们从去年年底开始做这个业务，确实是启动的基数是比较小的，所以其实到今年年初开始的时候，我们那个基数相对还是一个比较小的数据。但是我们公司因为其实一直以来是在服务规模以上的客户，所以其实我们从年后回来开始，我们结合了agent的这个需求爆发，我们接到了大量的顶级互联网客户和各行业客户的这种by coding的场景，以及agent的场景。所以这个量暴起来，就是每个客户的量级都是比较大的。实际上我们现在是受限于交付资源的原因，所以其实没有完全充分释放这个业务的潜力。但是在这种相对有限的条件下，业务还是得到了一个巨大的增长。但是因为这里面的不确定性也比较高，所以你让我们对全年做这个业务的展望，其实我们现在只能说还是一个比较乐观的增长状态。所以这个我们可能在运行一两个季度才能看到更明确的这个状态。另外，从利润率角度来讲，这个业务相比于我们传统的云计算业务，以及我们传统的算力业务来讲，它的毛利水平是相对高的，并且它是一个随着我们的技术进步，毛利水平会有优化的过程。所以我们自己在过去的一个多月里，也经历了我们自己的算子和算法的优化带来的巨大效率提升和毛利率的提升，我们也见得到，包括它的运营模式上的利润优化空间也相对比较多。所以整体来说，我们对于后续的毛利维持在相对高的水平是相对乐观，但是因为业务也是有各种各样的变数，所以我们还是不做完整长期的预测。谢谢。

Okay, quickly translation. Our token business actually started off at a relatively small base, let's say end of last year and beginning of this year. However, traditionally we have already maintained a very strong customer base of very large scale leading customers. At the beginning of this year, we're starting to meet huge demands coming from such customers in light of the surge of agent demand, the surge of by coding demand in such use cases. Obviously the demand was huge and very strong. In a way our business was restricted by the underlying resources that is available to us. I would say that obviously we are optimistic about the growth of this business.

However, due to that uncertainty we just mentioned, we would like to, let's say, see a couple more quarters before disclosing more details to the market of how that business grows. Secondly, in terms of margin levels, I would say that the margin levels for this token business, inference business in general is higher than traditional cloud computing business. We do see a lot of improvements in margin from certain perspective, for example, coming from technology advancement, coming from the optimization of algorithms, coming from optimizing that algorithms with the relevant models, and also optimization and improvement coming from operating models. I would say we are cautiously optimistic about the margin. Again, due to still currently in a quickly expanding phase, it's not in a static phase, we will not at this stage, talk more about the specific margin numbers. Thank you.

第二个问题，我们请田开研回答一下。

第二个问题我来回答。那么从我们目前看到的情况来讲，从下游的客户的需求来讲，应该是在Q1呈现一个激增的状态。那么同时的话，我们的上游供应上的价格其实也在一个激增，不管是从部件，还是从整机，还是到原材料，其实都在上涨的一个过程里面。所以大家其实都共同认为，这个增长的趋势可能在今年Q2甚至更长的时间内还会再延续。所以尽管价格出现了上升，但是我们客户依然认为，现在尽快地买入相应的服务来满足他们的生产和研发的需求，应该还是一个不错的时机。所以在现在这个阶段，我们的上游的涨价基本上完全可以被下游的客户的买单所覆盖掉。所以整体来讲的话，我们的AI的租赁合同的平均价格是有明显提升的。谢谢。

In relation to the second question about the selling and purchasing price in relation to our business. Yes, as widely recognized, the demand for our cloud computing services has been surging tremendously. Is the pricing from our upstream, which includes from components to holistic servers to other raw materials. The current consensus of the market, including our customers, is that the price hiking, the price surge trend will actually continue on, not only already happened in Q1, but also will continue in Q2 and maybe some quarters to follow. They would believe that the current time point to secure more computing power is actually the right moment to do so. Because of that, the pass through of the price of the cost pressure coming from our upstream is actually doable and would not negatively affect our margin levels in this current market situation.

Thank you.

好的，谢谢刘总，还有田总的回答。

Thank you. We will take our next question. Your next question comes from the line of Wenting Yu from CLSA. Please go ahead. Your line is open.

刘总，各位管理层晚上好。感谢给我提问的机会。我公司是公司非常强烈的业绩啊。我这边有两个问题想请教一下，第一个是关于我们一季度的这个毛利率，我们看到这个同比还是有一点下降，想请教一下这个背后主要的影响因素，以及其中是不是已经体现在了我们这个产品长大给我们毛利率的一个正常的影响。第二个问题是关于这个行业竞争格局的问题。如果我们有关注到近期可能在这个行业高端算力supply紧缺的这种情况下，大模型公司此时它采取了更灵活的这个算力配置，在公有云厂商之外，跟上游这个算力租赁公司以及电信运营商加大合作。那管理层会怎么去看金山云在其中的这个竞争定位跟优势？I'll translate the question.

The first question is regarding the gross margin in Q1. We noticed that the gross margin dropped a bit in Q1, and what are the main reasons? Has the positive effects of the product price increase been factored in already? The second question is, with the ongoing high demand for computing power, large model companies are adapting their resource allocation and forming partnerships beyond public cloud vendors to GPU rental companies and telcos. How does management think of cloud competitive position and advantages in this landscape? Thank you.

Thank you for your question. For the first quarter of the margin, we can see a 3% percentage decrease. I think the first factor is the seasonal factor, because there is a 30% revenue come from the enterprises cloud. That is the first reason. The second one is the upfront cost incurred for future revenue generate activities with certain customers. For the coming quarters, we expect the gross margin will recover to nominal level. Thank you.

第二个问题我先回答一下，那等下看看刘总给您的补充。实际上你这是一个非常好的问题，我们也注意到了

到了智算云，尤其是进入到去年下半年开始，应该是从去年开始，你会发现整个的市场格局发生了一个很有意思的现象，就是有些过去竞争关系的，现在是合作伙伴了。我就不讲具体的企业的名字，反正有些以前可能是不是上下游的，现在也变成上下游的。有些以前是不同地盘上的，我们是民营企业，那有些是国有企业的，进入到智算时代也是个紧密合作。其实是这样的，我觉得这个现象的背后说明几个问题。我觉得第一个其实是一种能力的互补，当然也可以说是一种制度的互补。其实这个我自己在刚才业绩会上也就谈过，我说其实这个可能很多，不要以竞争对手去看待。我觉得无论从体质还是从能力上，它都是一个合作伙伴。结果到了智算时代，这个已经非常明显了。第二个其实也说明本身现在整个算力市场的需求的旺盛以及供给的不足这个矛盾。所以大家要联合起来，大家抱团在一起，去把这个客户服务好。所以我知道你刚才谈这个问题，更像是一种竞争的角度去看这个问题。但我们体会下来，感受到的其实更多的是一种面临一个蓬勃发展的时代，我们都有能力的短板，我们也都有制度的短板，当然也包括其他资源的短板。我们今天反而是放弃过去的门户之见，其实是一起在积极拥抱这个时代，并且一起是在共赢的这么一个时期。所以这就是我们的理解，这本质上其实就是能力的互补，然后资源的互补。我们不是竞争，我们反而是更多的合作。过去打得头破血流的对手，现在也放在一起前进。过去井水不犯河水的，境域分明的这种竞争区域，现在也逐渐在一些融合。好吧。

This is a very interesting question. It is a very good question. In fact, we observe a relatively interesting change in market landscape starting the second half of 2025. That is some of the used to be competitors are actually becoming cooperation partners in this wake of strong AI demand. What you mentioned in your question, it also exemplifies the close cooperation between private enterprises and state-owned enterprises. We think that this demonstrates a couple of things. Number one, this is fundamentally a complementary capabilities from, or I would say, complementary institutions coming from different backgrounds of enterprises, which we have mentioned back in the general computing, CPU computing age. This is actually manifesting itself again in this new AI for intelligent cloud era.

Secondly, we would think that this fundamentally reflects the strong discrepancy between, or the strong gap or the big gap between supply and demand in today's market. Everybody actually needs to come together and to overcome shortcomings that each one of us have to form holistic and overall solutions to serve the end customers. Again, your question is more from a competition perspective, but from our understanding and experience, we're actually seeing a more kind of cooperative perspective of the story. Everybody has its shortcomings and we work together to serve the needs of the end customers. Thank you.

Thank you. We will take our next question. Your next question comes from the line of Daley Lee from Bank of America Securities. Please go ahead. Your line is open.

各位管理层大家晚上好，感谢接受我的提问。我这边可能请教两个问题，这可能也是相关的。第一个就是关于这个客户的需求这方面，我们一季度这个增长还是非常快的，然后想管理层分享一下，我们看到二季度或者未来下半年那个需求展望，哪些类型的客户可能比较强，其中这个推理跟训练的占比的趋势大概是怎么样的？第二个问题是关于可能这个一个小细节问题，就是说我们跟客户现在签的合同的期限大概是多久的？这个是否因为现在一些价格，可能这个上游的价格变化，这个期限可能变缩短或者做一些调整？就这两个问题，那我这边简单翻译一下。Assessment management taking my question.

I have two questions here. First question about the demand outlook for the public cloud. The one key result is pretty strong. How do we see the demand trend in Q2 and the second half this year? Regarding the demand mix, how's the trend for inferencing and model training? My second question is about the contract term with our clients. As the upstream costs are in a rising trend, are we taking a shorter term contract, any change in terms of the contract terms? Thank you.

我是刘涛，这个问题我来回答一下。第一是说关于二季度的展望。首先就是刚才我们在前面的内容里也提到过，我们的需求是极端旺盛的。目前在公司过会的backlog的队列里，排着的需求是非常大，但受限于供应链的变化，所以可能还是需求是极端旺盛的。另外从行业上来看，哪些客户和行业，其实还是很丰富的，既有互联网的客户，也有比如说具体的AI公司，也有包括像自动驾驶的客户需求也在爆发，包括机器人行业的需求也在爆发。所以整体来看，多个行业线的需求都在爆发式地增长。那么这里面看哪些是推理，哪些是训练呢？可以看到像自动驾驶、机器人明显是训练的需求为主，包括为训练而准备的数据处理的需求。那么对于一些公司来说，我们还是看到了有一些新进市场的训练的玩家正在进入市场。同时，来自于大模型公司和互联网公司的推理，以及比如来coding带来的推理需求也是在增长的。所以这是个增长。另外从合约角度来看，因为现在的供给还是比较紧张的，所以在我们作为供给侧来说是有比较大的选择权的。我们会和客户签订一个对我们来说风险又比较小，然后现金流回收又比较快的一个合约周期。就这些。

In terms of AI demand, as we mentioned, it's exceedingly strong. Looking at the second quarter, we currently actually have a very long list of backlog, which is mainly subject to the supply chain restrictions. For the sectors that drive this growth, we're currently covering quite a few sectors, which we have all seen simultaneously having explosively strong demand. Starting from the internet, from large language model, AI labs, from autonomous driving, and from robotics. I would say that out of which the autonomous driving and robotics generally tend to have very strong model training requirements and demand. Particularly for robotics, and also autonomous driving, actually, they have also a lot of data processing or data treatment requirements, demands for the training of their models.

For the inference side of the story, we have the internet companies and large language model companies coming from their demands for AI coding and agents, such use cases. This is the general overview of the demand side of things. Since you also mentioned about the contract period, we had relatively standard contract periods in the past, now in light of this new supply chain, the price surge, we currently have more flexible kind of contract period arrangements, which maximizes our profit and benefits. Thank you.

感谢刘总，还有Tian总的回答，谢谢。Thank you.

Thank you. We will take our final question. Your final question comes from the line of Timothy Zhao from Goldman Sachs. Please go ahead. Your line is open.

好的，感谢管理层接受我的提问，也再次恭喜非常强劲的一个一季度的业绩。那我这边有两条问题，第一条问题是关于我们小米和金山的生态的收入。那我看到在这个季度的同比的增速，其实相比于去年四季度，在对于小米和金山的收入的增速有一些加速的趋势。那想请问一下，我们在小米今年以来的MiMo大模型，特别是MiMo V2.5发布以来，公司看到小米对金山云的资源，包括训练和推理的使用量有哪些变化？那我们也宣布了在2026、2027年和小米的关联交易的额度，想请教一下，我们对整个额度的使用率相对于2025年是怎么去判断的？这个是第一条问题。那第二条问题是关于我们的资本支出和我们的租赁的资产。那我看到在一季度我们整体是大概花了RMB 30亿左右，想请管理层更新一下，我们对于今年整体资本支出或者是资本支出当量的全年的展望是怎样的？那我很快翻译一下。Thank you management for taking my question and congrats on the very strong results.

My first question is regarding your revenue from Xiaomi and the Kingsoft Cloud and Kingsoft ecosystem. I noticed that the revenue growth accelerated compared to the fourth quarter of last year. Just wondering is there a way to show me after the MiMo large language model launch and especially MiMo V2.5, have you observed any specific change on the demand for Kingsoft Cloud resources and the breakdown between training and inferences? After you announced the revenue related party transaction revenue cap with Xiaomi for this year and next, just wondering how do you think about the utilization rate versus last year? My second question is regarding your CapEx and also lease assets. I noticed that the total amount spent was around CNY 3 billion in the first quarter. Just wondering if you can provide us an update on how you think about this total CapEx number for this year.

Thank you.

好，第一个问题我来回答一下，我是刘涛。首先是我们和小米的训练和推理的相关事项，因为绝大部分的训练工作都是在我们家来展开的，我们也可以看到，包括其实你们也从业界上看到了，训练带来的资源的需求还是在增长的。另一方面就是推理的业务，尤其在V2发布以后，在这个整个集群里面，有不少的算力会被转换成推理的资源去用，然后再通过更新换代，就换新一代的资源去做训练。所以推理的需求也增长得很快。当然这里面你要预测推理的增长能有多大，这个东西不好说，它决定于小米的业务的回报。如果它的回报是正向很好的话，它其实会放开了去推，那个需求就不太好预测了。所以其实我们还是第一，需求的增长的趋势是比较乐观的；第二，就是我们会线性地根据业务发展来去做一个额度的预测。好。

On the training side, the vast majority of those resource demands come from Kingsoft Cloud. We continue to see a growing demand in that respect. In inference demand, especially since the launch of MiMo V2, a lot of underlying resource has been reallocated to do the training for that, to do the inference for that model. In terms of the prediction for future growth of inference coming from MiMo, we are relatively optimistic. However, it's ultimately subject to the return on Xiaomi's side. Probably we don't have personal comment on that, but we generally remain optimistic about that.

For CapEx in future, actually the AI era present huge opportunities for us. Fortunately, we launched our intelligent computing business back in 2023. We have well established our supply chain capabilities, and our supply network is in place now. As Mr. Tao Liu has mentioned, we have seen a certain demand from our strong customer demand. We have to admit, the supply chain capacity is the primary limiting factor for the capital spending for the 2026. We estimate that our best estimate to say for the 2026 is around CNY 15 billion-CNY 20 billion at this moment. Thank you.

Thank you.

Thank you. This concludes today's question and answer session. I will now hand back for closing remarks.

Thank you, operator. Thank you everyone for joining us today. If you have any further questions, feel free to contact us. Looking forward to speaking with you again next quarter. Have a nice day.

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

Good day, and thank you for standing by. Welcome to the Kingsoft Cloud's Fourth Quarter and Full Year 2025 Earnings Conference Call. [Operator Instructions] Please be advised that today's conference is being recorded. I would now like to hand the conference over to your speaker today, Nicole Shan, IRD of Kingsoft Cloud. Please go ahead.

Thank you, operator. Hello, everyone, and thank you for joining us today. Kingsoft Cloud's fourth quarter and fiscal year 2025 earnings release was distributed earlier today and is available on our IR website at ir.ksyun.com as well as on PR Newswire services. On the call today from Kingsoft Cloud, we have our Chairman and CEO, Mr. Zou Tao; CFO, Li Yi; Senior Vice President, Mr. Liu Tao; Senior Vice President, Mr. Tian Kaiyan; Vice President, Ms. [indiscernible]; and Associate Vice President, Mr. [indiscernible]. Mr. Zou will review our business strategies, operations and other company highlights, followed by Ms. Li, who will discuss the financial performance. We will be available to answer your questions during the Q&A session that follows. We will be conducting an interpretation. Our interpretation are for your convenience and reference purpose only. In case of any discrepancy, management statement in our original language will prevail. Before we begin, I'd like to remind you that this conference call contains forward-looking statements within the meaning of Section 21E of the Securities Exchange Act of 1934 as amended and as defined in the U.S. Private Securities Litigation Reform Act of 1995. These forward-looking statements are based upon management's current expectations and current market and operating conditions and relate to events that involve known or unknown risks, uncertainties and other factors, all of which are difficult to predict and many of which are beyond the company's control, which may cause the company's actual results, performance or achievements to differ materially from those in the forward-looking statements. Further information regarding these and other risks, uncertainties or factors are included in the company's filings with the U.S. SEC. The company does not undertake any obligation to update any forward-looking statements as a result of new information, future events or otherwise, except as required under applicable law. Finally, please note that unless otherwise stated, all financial figures mentioned during this conference call are denominated in RMB. It's now my pleasure to introduce our Chairman and CEO, Mr. Zou. Please go ahead.

[Interpreted] Hello, everyone, and thank you, and welcome to Kingsoft Cloud's Fourth Quarter and Fiscal Year 2025 Earnings Call. I am Zou Tao, CEO of Kingsoft Cloud. Since the beginning of 2025, the global AI industry has reached a series of milestones from the democratization sparked by the DeepSeek moment to the active competition among multimodal software models from the leap of embodied AI into the physical world to OpenCloud's closed-loop capability of understanding and execution. AI is evolving with unstoppable momentum linking across models, agents, computing power through industrial applications, reshaping every sector. As a tightly integrated component of the AI 5-layer take, cloud computing is now meeting an unprecedented surge in demand for intelligent computing. This year, we stayed committed to our high-quality and sustainable development strategy, embracing the opportunities in AI era, strengthening our capability through solid execution. We have delivered impressive results, achieving strong financial performance while forging lasting business strength. First, we recorded a historical high quarterly revenue, reaching RMB 2.76 billion, representing a year-over-year growth of 24%, among which revenues from public cloud services increased by 35% to RMB 1.9 billion. Our intelligent computing services keep driving our growth. The gross billing of AI business reached RMB 926 million, representing a 95% year-over-year and contributing 49% of our public cloud services. Second, growth in our ecosystem and external business segment is progressing hand-in-hand. On one hand, our ecosystem partnerships have remained strong and continue to deepen. This quarter, Xiaomi and Kingsoft ecosystem revenue reached RMB 804 million, a 63% year-over-year increase, accounting for 29% of total revenue. For the full year 2025, related party transactions with Xiaomi and Kingsoft ecosystem partners reached 94% of our net annual C, almost hitting the limit. On the other hand, our external customers, including leading enterprises across a wide range of high-growth industries, also shown confidence in our products and services, accounting for around 70% of total revenue. Furthermore, revenue from our top 5 non-ecosystem customers grew by 44% year-over-year, sustaining strong growth momentum. Last but not least, profitability continued to improve this quarter with adjusted gross margin increasing quarter-over-quarter to 17.1% and adjusted operating margin reaching 2.0%. We have achieved operating level profitability 2 quarters in a row, and our self-funding capability has shown sustained and significant year-over-year improvement. Now I would like to walk you through the key business highlights for the fourth quarter of 2025. In terms of public cloud services, revenue reached RMB 1.9 billion this quarter, representing a year-over-year increase of 35%. From a customer perspective, in 2025, AI continued pushing its boundaries, driving industries to fully embrace it, diversifying our customer base. Beyond leading AI enterprises and Internet giants, we now also serve automotive manufacturing, autonomous driving, embodied AI and fintech sectors, et cetera. We've solidified our cooperation within the Xiaomi and Kingsoft ecosystem while capturing new external opportunities. From a product and services perspective, we keep pushing the limits of cluster scale, supporting large-scale training and explosive inference demand. Notably in this quarter, we delivered a new inference cluster for top video streaming platform, serving over 100 million users. We also secured a major fintech customer using our token-based inference service who speak highly of our stable model and computing power services. On supply chain front, despite market uncertainties, our well-established and resilient supply chain built through years of experience allowed us to plan ahead strategically and stock key components dynamically to ensure sustainable business growth. Now in terms of enterprise cloud, revenue reached RMB 859 million this quarter, a significant quarter-over-quarter increase of 18%. Driven by the AI Plus policy, industrial intelligence solutions have become a key growth driver. The demand for specialized vertical models, real-world applications and strict data compliance makes cloud services more essential than ever in advancing industrial intelligence. The AI business of enterprise cloud is paving the way for steady long-term growth, not only representing a $1 trillion market opportunity, but also playing a critical role in driving the technological leap across industries. As a B2B cloud service provider with solid technology expertise and enterprise service capabilities, we are well positioned to capture these industrial transformation opportunities. In the area of enterprise services, we achieved key breakthroughs in high-end manufacturing industry. We provided stable and high-performance computing service to the top enterprises to support their process in intelligent manufacturing, industrial vision and AI R&D. In health care space, we launched a data agent-based AI application in health care intelligent operation process, marking a paradigm shift from digitalization to intelligence. This analysis through natural dialogue platform enables natural language insights into DRG cost control, moving hospital management from retrospective statistics to proactive intervention. While significantly lowering the barrier to data application, we have further solidified our technical moat and differentiated competitive advantages in high-value medical AI scenarios. In public services area, we partnered with telecom operators to provide sustainable and stable high-performance computing clusters for the public services sector, successfully entering key markets like Shanghai. We believe that by leveraging Kingsoft Cloud's deep vertical expertise and enterprise service experience, intelligent computing opportunities in the enterprise cloud segment represents a massive industrial frontier, generating synergies with our public cloud business. In terms of products and technology, we are building a next-generation computing services system for LLM training, inference and industrial intelligence, offering full stack capabilities from computing services to model as a service. Our technology upgrades from basic cloud computing to an AI-first AI-native cloud architecture contributing for digital and intelligent transformation across sectors. We focused on the technologies catering to model training and inference scenarios, aiming to provide highly stable, highly efficient and ready-to-use intelligent computing services. This quarter, our StarFlow platform keep upgrading with the launch of MCP, aka model context protocol cloud, process optimization and AI search features to help enterprises develop and deploy AI agents through a unified platform, gradually building a new ecosystem centered around agent-based operations. For enterprises with private deployment demand, our Galaxy Stack provides heterogeneous GPU management, rookie network and intelligent container scheduling capabilities. We also feature full stack localization with indigenous adaptation to empower intelligent transformation across verticals. Standing at a new starting point, looking ahead, we're truly excited by the limitless possibilities that lie before us. We will remain committed to our high-quality and sustainable development strategy by embracing the immense opportunities presented by the AI era, developing along with the industry and refining our core technologies. We will continue to capture the market opportunities, both within and beyond our ecosystem, optimizing the operations of our assets to enhance profitability and thereby create value for our customers, shareholders, employees and society. I will now pass the call to our CFO, Ms. Li Yi, to go over our financials for the fourth quarter and fiscal year 2025. Thank you.

Thank you, Mr. Zou and [indiscernible], and thank you all for joining the call today. Before we walk through the details of financial results for the fourth quarter and fiscal year 2025, I would like to highlight the following aspects. First, our revenue has achieved record high, RMB 2,761 million this quarter, representing a year-over-year growth rate of 24%. Within that, revenue from public cloud services was RMB 1,902 million, increased by 35% from RMB 1,410 million in the same quarter last year. Unprecedented explosive demand for our AI business drove a 95% year-over-year billing growth, which totaled RMB 926 million. Second, profitability has seen substantial improvement. Driven by shift in our revenue structure, our adjusted gross margin continued its upward trend, rising to 70% from 60% in the previous quarter. Adjusted EBITDA margin reached 28%, up 12 percentage points from 60% in the same quarter last year, though down from 33% last quarter. The year-over-year growth was fueled by a large contribution from AI-related business, where [indiscernible] represents the primary cost component. The sequential decrease was mainly due to a nonrecurring subsidiary received last quarter, which established a high baseline. Notably, we have achieved adjusted operating profit for 2 consecutive quarters, reaching RMB 55 million this quarter, which was a 2% margin. These results validate our ability to monetize intelligent cloud opportunities and our strategic focus on high-quality enterprise services. Third, our cash and cash equivalents achieved RMB 6,018 million, strengthening our ability to further support the investment into AI business. Now I will walk you through our financial results for the fourth quarter of 2025. This quarter, total revenue were RMB 2,761 million. Of this, revenues from public cloud services were RMB 1,902 million, up 35% from RMB 1,410 million in the same quarter last year. Revenues from enterprise cloud services reached RMB 859 million during this seasonally strong quarter, which was characterized by a high volume of project completion. Total cost of revenues was RMB 2,296 million, up 27% year-over-year, which was mainly due to our investment into infrastructure to support intelligent cloud business growth. IDC costs increased by 30% year-over-year from RMB 725 million to RMB 812 million this quarter. The increase was mainly due to the increasing needs of [indiscernible], which serves the expanding AI business. Depreciation and amortization costs increased from RMB 323 million in the same quarter of 2024 to RMB 741 million this quarter. The increase was mainly due to the depreciation of newly acquired and leased servers and network equipment, which were mainly allocated to our AI business. Solution development and service costs increased by 50% year-over-year from RMB 557 million in the same quarter of 2024 to RMB 642 million this quarter. The increase was mainly due to the solution personnel expansion. Fulfillment costs and other costs were RMB 40 million and RMB 61 million this quarter. Our adjusted gross margin for the quarter was RMB 471 million, increased to 10% year-over-year and 20% quarter-over-quarter. It was mainly due to the expansion of our revenue scale, the enlarged contribution from AI business and the cost control of IDC racks and servers. Adjusted gross margin increased from 60% last quarter to 70% in this quarter, which was mainly due to the high contribution from enterprise cloud. On the expense side, excluding share-based compensation costs, our total adjusted operating expenses were RMB 459 million, increased by 3% year-over-year and increased 9% quarter-over-quarter, of which our adjusted research and development expenses were RMB 181 million, increased by 7% from same quarter last year. Adjusted selling and marketing expenses were RMB 111 million, increased by 3% year-over-year. Adjusted general and administrative expenses were RMB 168 million, decreased 1% year-over-year. Our adjusted operating profit was RMB 55 million, increased by 124% from adjusted operating profit of RMB 24 million in the same period last year. The improvement was mainly due to the expansion of our revenue scale and gross profit as well as the expense control. The total expense as a percentage of revenue keeps decreasing. Adjusted operating profit margin increased from 1% in the same period last year to 2% this quarter. Our non-GAAP EBITDA margin was RMB 785 million, increased by 180% from RMB 360 million in the same quarter last year. Our non-GAAP EBITDA margin achieved 28% compared with 60% in the same quarter last year. It was mainly due to our strong commitment to AI cloud computing development, strategic adjustment of business structure, strict control over costs and expenses. This quarter, our capital expenditure, including those financed by third parties and right-of-use assets obtained in exchange for finance lease liabilities were RMB 496 million. For the full year 2025, our total revenue achieved RMB 9,559 million, increased by 23% from RMB 7,785 million in 2024, among which revenues from public cloud services were RMB 6,634 million, increased by 33% year-over-year. Revenues from enterprise cloud services were RMB 2,925 million, increased by 5% year-over-year. Adjusted gross profit was RMB 1,542 million, increased by 40% from RMB 1,358 million last year. Adjusted gross margin was 60%, decreased from 70% last year, which was mainly due to the high cost for servers and other hardware equipment. Adjusted operating loss was RMB 152 million, narrowed significantly from RMB 431 million. Adjusted operating profit margin was minus 1.6% narrowed from minus 12.5% last year. Adjusted EBITDA profit was RMB 2,336 million, increased by 266% from RMB 639 million last year. The adjusted EBITDA margin was 24%, improved by 60% from 8% last year. Looking ahead, we aim to capitalize on the explosive growth in demand by further investing in infrastructure, enhancing service stability, managing liquidity risk and improving operating efficiency. We remain focused on AI-driven strategy, providing customers with high value-added cloud services. That's all for the introduction of our operational and financial results. Thank you all.

Thank you, operator. This concludes our prepared remarks. We are now happy to take your questions. Please ask your question in both Chinese and English, if possible. Operator, please go ahead.

[Operator Instructions] Our first question comes from the line of Liping Zhao from CICC.

Congrats for the very good 4Q results. I have 2 questions here. First, Xiaomi recently launched the MiMo-V2 series models, which have received positive market feedback. How should we view our role and positioning within Xiaomi's AI strategy? And what strategies will be implemented around Xiaomi and Kingsoft service going forward? And secondly, how does the management view the current pricing uptrend in the cloud service industry? Has the company already adjusted prices for AI computing services? Or are there any related plans in place? To what extent are those price adjustments driven by demand or driven by the upstream procurement cost pass-through?

[Interpreted] The answer comes from our CEO, Mr. Tao Zou. So a little bit of background. So back in 2024, I think that was in August, we had an internal discussion around the development of AI and models for the whole Xiaomi and Kingsoft ecosystem. So the idea was that the whole Xiaomi and Kingsoft ecosystem will form a [indiscernible] portfolio of solutions where -- a whole system where Kingsoft will stay disciplined and not really developing our own large language models, which is left to -- for Xiaomi to develop. So the MiMo model and its widely recognized performance is actually an implementation and manifestation of our overall AI strategy within the Xiaomi and Kingsoft ecosystem. And secondly, back in 2025, so 1 year later from the internal discussion session, from a KC perspective, we formed a strategy that's called 1+N. So the 1 here actually refers to the Xiaomi MiMo model, which is the key to KC's inference strategy. So in the future, we will continue to adhere to this strategy, which essentially means that within the ecosystem, we will continue to serve the Xiaomi and Kingsoft ecosystem. And for external customers, we will also try to monetize our model as-a-service capabilities, thereby not only in the training area that we were able to make our revenue and profits, but also we will make our contribution in the inference era that is approaching.

[Interpreted] So the answer comes from our SVP, Mr. Liu Tao. So as a bit of background again. So in the Q3 last year, we had anticipated the significant pricing increase from the supply chain side. And therefore, we had dynamically and strategically stocked up some of the key components. So we did have -- so we were actually prepared for this -- what's unfolding today. Now in terms of the price hike that you were asking, so we stick to 2 principles. Number one, if we already -- for some of the customers and business where we already have contracts in place and where we have the stocking of the underlying resources, we tend to not increase the pricing. However, for some of the new customers, new contracts, especially with significant increase of usage, there's going to be significant price hiking in these kind of scenarios. Now also in terms of profitability, one thing is that we will actually try to pass through some of the upstream cost increases to our customers. And secondly, for -- we also -- depending on the demand, right, we also try to increase some of the price to reflect and increase our profit.

Our next question comes from the line of Wenting Yu from CLSA.

The first question is that some of your cloud service partners have announced they will shift their cloud business more towards [indiscernible] from the traditional server rental and also the subscription model. Will KC adopt a similar strategy? And how do you view the impact of this trend on industry competition and long-term profit margins? And the second question is regarding the impact from the [indiscernible] engine. It is adopting a relatively low price strategy. And how do you view the impact on the industry and also on potentially our business this year?

[Interpreted] Okay. So regarding your question on the shifting to model as a service strategy, we have noted some of the other peer companies who released their results earlier than us mentioning it. However, my view is that this is not actually some new concept. It is actually one of the inevitable stage of the development of AI as well as large language models from the training that we do to create them to a certain stage that they become applicable and workable in our day-to-day work and life. So in relation to our own inference-related work, model as a service work, we actually launched the StarFlow platform, as we mentioned in the prepared remarks last year. And because we are a neutral platform, we were able to host essentially all of the open source models, including also the model coming from Xiaomi to provide model as-a-service business, where this is essentially actually the fastest-growing business in the history of the company. Actually, so we talked about the Xiaomi MiMo model earlier, the way that we're providing services for Xiaomi MiMo model is also a model as-a-service business. And also for some of the large language model customers that we used to -- and we're still providing training services to them, we also provide model as-a-services business to them as well to cater to their inference needs. Now as to your second question about the price change for [indiscernible], I haven't really noticed that particular piece of news. However, the general market dynamics today is that on one hand, we're seeing explosive growth on the demand side. And we're seeing a particularly high price hiking from the supply chain side. So I do not personally think that under such circumstances, changing price to a lower level would actually be implementable and applicable in the real world. Now what I have focused more is the price hiking information from, for example, AliCloud. We have worked with them together. We have been in the industry together for many years, and this is the first time that we've seen them hiking their price. And also an addition from our SVP, Mr. Liu Tao, is that there is a difference between the catalog price and the actual price that the companies that offer as cloud players and our customers engage into. So the change in catalog price is more of a marketing kind of purpose, and it does not necessarily mean the actual price that companies enter into business.

Our next question comes from the line of Timothy Zhao from Goldman Sachs.

My first question is on your financial outlook. Just wondering if you can share some color on how we should think about the revenue, EBITDA, operating profit growth outlook for this year? And also on the capital expenditure plan, what is your thought and considering the balance sheet and also the prepayment from certain customers, do you think it's possible to further raise your CapEx plan given the rising AI demand? And secondly is regarding the third-party revenue in the AI outlook. Just wondering if you can share more detailed color on your -- what specific product or what type of customers are driving the third-party AI growth? And also what is the breakdown and outlook between the mix of AI training versus AI inferences?

All right. I will take the CapEx first. For 2026, we expect total CapEx and control assets to exceed RMB 10 billion, representing expansion from 2025 level. On funding structure, we expect approximately half of our CapEx is targeted to be covered by customer prepayment arrangements, which will significantly reduce safe funding requirements. Additionally, we plan to access more assets through short- and long-term leases with payment structure and operating cash flows to minimize upfront capital encumbrance. For the funding position and financing needs, we currently have no equity finance plans. 2026 capital expenditure are secured through 4 channels. First, proceeds from our 2025 financing; and second, customer operating receipts; and third, the strategic customer prepayments; and the fourth, the commitment credit facilities from banks and financial institutions. Incremental resource requirement will be made primarily through leasing to preserve balance sheet flexibility. For the guidance for the 2026, we expect our growth rate will accelerate and the EBITDA rate will improve much in 2026 as well.

[Interpreted] So if you look at the past results as described -- as discussed in the prepared remarks, the -- for the top 5 non-ecosystem customers combined revenue for year-over-year basis revenue growth was 44%, which is really strong growth. So those would include Internet companies, autonomous driving and robotics. And then in terms of looking forward into the year of 2026, we do see extremely large demand coming from outside of the ecosystem. And to some extent that such demand is actually higher than the demand from our ecosystem. So the final revenue or financial results coming from that demand will actually be determined -- will actually be dependent on how much resources we're able to secure and deliver to such customers. Now from the perspective of products and solutions, we have -- we're actually seeing more than half of the potential demand coming in for inference versus training. And then for the StarFlow platform, which we discussed earlier, it's growing really fast for that business, and we're seeing better profit margin coming from that particular business. And this is a result, of course, from the very good application, very good application and increasing penetration for agents and core applications. Thank you.

Thank you. Due to time constraint, this concludes our Q&A session. Thank you once again for joining us today. If you have any other questions, please feel free to contact us. Look forward to speaking with you again next quarter. Have a nice day. Thank you all.

This concludes today's conference call. Thank you for participating. You may now disconnect. [Portions of this transcript that are marked [Interpreted] were spoken by an interpreter present on the live call.]