Thank you, operator. Hello, everyone, and thank you for joining us today.

Kingsoft Cloud's first quarter 2026 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, Ms. Li Yi; Senior Vice President, Mr.

Liu Tao; Senior Vice President, Mr. Tian Kaiyan; Vice President, Mr.

Wang Chenzheng; and Board Secretary, Mr. Clark Tian.

Mr. Zou 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's 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 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 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.

大家，大家好。欢迎参加金山云2026年第一季度业绩电话会。我是金山云CEO邹涛。2026年以来，随着AI Coding的进一步普及，叠加AI智能体的爆发，AI开始真正从能聊天走向能干活，带动了模型推理和训练需求齐头并进，进一步打开了云计算行业的天花板。本季度，金山云继续坚定推进高质量可持续发展战略。一方面，夯实智算云基础设施和训练和训推平咳能力；另一方面，深耕行业垂直场景落地，全心投入AI重塑世界的变革。首先，公司延续了高质量增长的态势。收入规模方面，本季度实现收入27.0亿元，同比增长37.2%。公有云和行业云均实现了同比增长。其中，公有云收入达20亿元，同比增长47.5%。盈利水平方面，本季度公司实现调整后毛利润毛利润3.5亿元，同比增长8.6%；调整后EBITDA 7.5亿元，同比增长134.7%；调整后的EBITDA率27.6%，同比提升11.4个百分点。其次，智算继续驱动公司业务增长。本季度，智算业务账单收入达10亿元，同比增长90.1%，占公有云收入比重首次超过一半，达50.1%。Token业务收入增长极其强劲，2026年，26年4月为1月的约53倍。第三，生态合作继续深化。本季度，来自小米和金山生态的收入达8.4亿元，同比增长68.9%，占总收入比例为31%。随着小米在人车家全生态和AI领域强化投入带来更多业务机会，我们已上调与小米持续关联交易上限。调整后，2025至2027三年框架内，来自小米金山持续关联收入上限达142亿元。

Good evening, everyone, and welcome to Kingsoft Cloud's First Quarter 2026 earnings call. I am Zou Tao, 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 remained 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 RMB2.7 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 RMB2.0 billion, a year-over-year increase of 47.5%. In terms of profitability, our adjusted gross profit reached RMB351 million, up 8.6% year-over-year.

Adjusted EBITDA was RMB748 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 RMB1.0 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 RMB838 million, a year-over-year increase of 68.9%, accounting for 31.0% of total revenue.

As Xiaomi reinforces its investments in the Human x Car x 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 RMB14.2 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%，47.5%。首先，我们继续紧紧跟小米金山生态内大体量、高可见的云计算需求，着眼长期全球战略合作，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。我们也凭借星流训推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 Science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，也使我们能更灵活的错峰调度算力，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 RMB2.0 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 a 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 for Science customer, ensuring its rapid business growth and stable platform operations. We also supported a top logistics technology company in executing large-scale code 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 drives revenue growth, but also enabled us to schedule computing resources more flexibly in off-peak periods, improve resource utilization, and enhance profitability. 行业云方面，本季度实现收入7.0亿元，同比增长14.7%。公共服务领域，我们在深圳推出国资云Cloud平台，聚焦国资国企高安全、强合规、高保密的核心诉求，全面赋能国企办公、业务、管理等场景的数字化升级。我们基于金山云技术底座，采用省平台加多区县平台一体化架构，在湖北打造供应链公共信息平台，实现资源节约、数据互通、业务协同，目前已支撑多地市、区县平台规模化上云。我们还与领军国内芯片厂商合作，构建从底层芯片到上层应用的全栈智算服务体系，落地推动国产智算云规模化商业应用，满足高安全、高可控的智算需求。数字健康领域，我们与全国名列前茅的华中科技大学同济医学院附属协和医院合作数据治理项目，通过体系化数据管控方法，助力医院实现从分散式管理向标准化治理的跨越，为大型医疗机构智能化转型树立标杆。我们还签约某大型医共体平台项目，该项目基于数据中台，彰显了我们在医共体建设领域规划、设计、建设、运营的全流程专业服务能力，为后续医疗机构以此为标杆、大规模推广上线奠定了基础。企业服务领域，我们为某领军清洁能源服务商交付绿色能源运营平台，保障大型重卡车队在途有效管理，并延伸至绿色低碳产业链，探索固废监管数字化解决方案，推动业务规模化落地。

In terms of enterprise cloud services, revenue reached RMB710 million this quarter, representing a year-over-year increase of 14.7%. In the public services sector, we launched the state-owned cloud core 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 resource 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 a 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 a 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 operation platform for a leading clean energy service provider, enabling effective in-transit 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.

产品技术方面，我们继续坚持技术立业，紧密围绕智算需求，全面升级产品服务。本季度，面向日益多样化的模型需求，我们的星流平台大幅扩充模型生态，API服务新增语音识别、语音生成类模型，扩充图片和视频生成模型，同时为用户带来更精细化的管理体验。面向智能体需求，我们上线了Agent Engine，助力客户高效完成Agent的开发、部署和运维。我们也为云主机新增Agent一键部署能力，支持OpenClaw、Hermes等主流Agent应用，实现5分钟以内部署，大幅降低使用门槛。面向AI训练场景，KS3缓存加速器性能实现毫秒级稳定低延迟，兼顾性能与成本。面向AI落地千行百业的私有化部署需求，我们的银河云平台完成了里程碑突破，新增了星流和安全模块，完成了包括云底座、训推一体、Token服务与安全护栏的全栈私有化部署智算闭环。 In terms of product and technology, we continued 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 5 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.

总体而言，纵观AI的浪潮，从文生文到多模态，从训练到推理，从聊天到干活，从Agent到龙虾，不断创新和深化，让我们更加坚信AI必将重塑千行百业的判断。金山云将继续秉持高质量可发展的战略，加大投入，深耕核心产品及解决方案，持续提升盈利能力，为客户、股东、员工和社会创造更大的长期价值。接下来请公司CFO李懿为大家介绍一季度财务业绩，谢谢。 Overall, in this wave of AI innovation, from text generation to multimodal 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.

谢谢邹总，谢谢Clark。Thank you, Mr. Zou and Clark, 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 RMB2,704 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 billings increased 91% year-over-year, amounting to RMB998 million. Second, our adjusted gross profit was RMB351 million, increased by 7% year-over-year, despite overall 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 our infrastructure, as our capital expenditures and leased assets obtained in combination grew 38% year-over-year to RMB3 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 RMB2,704 million. Of this, revenues from public cloud services were RMB1,996 million, up 47% from RMB1,353 million in the same quarter last year.

Revenues from enterprise cloud services reached RMB707 million, up 15% from RMB616 million in the same quarter last year. Total cost of revenues was RMB2,358 million, up 43% year-over-year, which was mainly due to our investments into AI computing resources.

IDC costs increased by 26% year-over-year from RMB723 million to RMB911 million this quarter. The increase was mainly due to increased rack services, which serve the expanding AI business.

Depreciation and amortization costs increased from RMB379 million in the same quarter of 2025 to RMB890 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 RMB505 million in the same quarter of 2025 to RMB705 million this quarter. The increase was mainly due to the solution personnel expansion of Camelot.

Fulfillment costs and other costs was RMB2 million and RMB51 million this quarter. Our adjusted gross profit for the quarter was RMB351 million, increased by 7% year-over-year and decreased by 25% quarter-over-quarter.

Adjusted gross margin decreased from 17% last quarter to 13% this quarter. The decrease was mainly due to the higher cost of servers along with the expansion of our AI business, as well as upfront costs incurred for future revenue-generating activities with certain customers.

On the expense side, excluding share-based compensation expenses, our total adjusted operating expenses were RMB455 million, remaining stable compared with the same quarter last year and last quarter, of which our adjusted R&D expenses were RMB184 million, decreased by 8% from the same quarter last year. Adjusted selling and marketing expenses were RMB112 million, increased by 4% year-over-year.

Adjusted general and administrative expenses were RMB159 million, increased by 34% year-over-year. Our adjusted operating loss was RMB16 million, increased by 7% from adjusted operating loss of RMB56 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 RMB748 million, increased by 135% from RMB319 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 adjustments of business structure. This quarter, our capex spending, including those financed by third parties and the right-of-use assets obtained in exchange for finance lease liabilities, were RMB2,985 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 strategy, 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.

哎邹总、李总晚上好，恭喜公司获得非常好的业绩啊。然后我这边有两个问题。第一个问题是关于我们那个星流MaaS平台的。因为刚刚邹总提到说这个星流的收入的话，4月份比1月份同比提升了53倍嘛，这个增长还是非常强的。那想请邹总说一说，就是目前这块业务大概我们的想法是怎么样子的，然后它的收入体量和利润率水平如何？未来怎么看就是整块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这个AI公有云里面AI的这部分收入啊，因为我们也都知道这个上游无论是芯片和存储的价格都是上浮了不少，那同时呢下游的这个需求也是非常的旺盛。那么和去年4Q相比，我们看到今年的一Q和二Q新签的这个订单的情况平均价格是否有了些提升？那么这个提升的幅度如何？我我自己翻译一下。Good evening, Mr. 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. Mr.

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, and 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.

立平你好。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。 好的立平，我来说一下。星流呢实际上我们其实从去年年底开始做这个业务啊，然后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字。对，但是其实我们也是因为其实一直以来是在服务规模以上的客户的，所以呢其实我们从年后来开始呢，我们结合了这个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Live

Coding的场景以及Agent的场景，所以这个量爆起来呢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啊。但是就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，所以呢就是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。另一个呢，从利润率角度来讲呢，这个业务相比我们传统的云计算业务以及我们传统的算力业务来讲呢，它的毛利水平是相对高的，并且呢它是一个随着我们的技术进步毛利水平会有优化的过程啊。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。所以总体来说，我们对于后续的毛利维持在相对高的水平是相对乐观，但是呢因为业务也是有各种各样的变数啊，所以我们还是不做这个完整长期的预测。好吧，谢谢。 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 agents demand, the surge of live coding demand in such use cases. Obviously demand was huge and very strong, but in a way our business was restricted by the underlying resources that is available to us.

I would say that obviously we're optimistic about the growth of this business. However, due to that uncertainty we just mentioned, we would like to let's say see for 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 and inference business is generally higher than traditional cloud computing business, and we do see a lot of improvement in margin from certain perspectives, for example, coming from technology advancement, coming from the optimization of algorithms, coming from the optimizing that algorithms with the relevant models, and also optimization and improvement coming from operating models. I would say we're cautiously optimistic about the margin, but 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，我们请田开颜回答一下。

第二个问题我来回答。那么从我们目前看到的情况来讲呢，从下游的客户的需求来讲，应该是在出现一个激增的一个状态。那么同时的话呢，我们的上游供应商的价格呢其实也在一个激增，不管是从部件还是从整机，还是到原材料，其实都在一个上涨的一个过程里面。所以呢大家其实都共同认为这个增长趋势可能在今年Q2甚至更长的时间呢，还会再延续。所以呢尽管价格出现了上升，但是我们客户依然认为现在尽快地这个买入相应的云服务来满足他们的这个生产和研发的需求，应该还是一个不错的时机。所以在现在这个阶段，这个我们的上游的涨价基本上完全可以被下游的这个客户的这个买单所这个覆盖掉。所以总体来讲的话呢，我们的AI的租赁合同的平均价格是有明显提升了。谢谢。

In relation to the second question about the selling and the purchasing of price in relation to our business, so, yes, as widely recognized, the demand for our cloud computing services have 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 search trend will actually continue, 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 cost pressure coming from our upstream is actually doable and would not negatively affect our margin levels in this current market situation. Thank you.

哎好的，谢谢刘总还有田总的回答。

哎邹总、李总，各位管理层晚上好，感谢给我提问的机会，也祝贺公司取得非常强劲的业绩啊。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，因为我们看到这个同比还是稍微有点踩踏，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了这个产品涨价对我们毛利率的一个正向的一个影响？第二个问题是关于这个行业竞争格局的问题啊，因为我们也关注到近期可能在这个行业高算力是比较紧缺的这个情况之下，大模型公司其实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也在展开合作嘛。那管理层怎么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 the first quarter. We noticed that the gross margin dropped a bit in the first Q, and what are the main reasons?

Have the positive effects of the product price increase have been factored in already? The second question is with ongoing high demand for computing power, large model companies are adapting their resource allocation and forming partnerships beyond public cloud vendors with GPU rental companies and telcos.

How does management view Kingsoft Cloud's competitive position and advantages in this landscape? Thank you.

Thank you for your question. For the first one, our first quarter, the gross profit margin, we can see a 3% percentage decrease.

I think the first factor is the seasonal factor, because there are 30% revenue come from our enterprise cloud. That is the first reason.

The second one is the upfront cost incurred for future revenue-generating activities with certain customers. For the coming quarters, we expect the gross profit margin will recover to nominal level.

Thank you. 第二个问题我先回答一下啊，等等下看看刘涛有没有补充。实际上你这是个非常好的问题啊，我们我们也注意到了。到了智算云，尤其是进入到去年下半年开始吧，你会发现这个，应该说是从去年开始，你会发现这整个的这个市场格局发生了一个很有意思的现象啊。就是有些过去竞争关系的，现在是合作伙伴了，对。我就不不讲具体的这个企业的名字啊，反正有些呢就是就是以前可能是是不是上下游的，现在也变成上下游的；有些是以前是不同地盘上的啊，就是这个这个我们我们是民企啊，那有些是国企央企的，进入到智算时代也也是个紧密合作。其实是这样啊，我觉得这背这个现象的背后呢说明说明几个问题啊。我觉得第一个呢，其实是一种能力的互补。当然也可以说是一种资质的互补啊。其实这个呢我自己在刚接金山云我就谈过，我我说其实这个可能可能很多其实不要以竞争对手去看待。我觉得无论从体制，还是从能力上，它都是个合作伙伴。进入到了智算时代，这个这个已经非常非常明显了啊。第二个呢，其实也说明本身现在整个整个算力市场的需求之旺盛，以及供给的不足的这个矛盾。所以呢这个大家要联合起来，甚至抱团在一起，去把这个客户服务好。对。所以呢就是我知道你刚才谈这个问题啊，这个这个更更像是一个以一种竞争的角度去看这个问题啊。但我们体会下来啊，感受到的其实更多的是一种一种一种面对一个蓬勃发展的时代，我们都有能力的短板，我们也有资质的短板，我们也有这个当然也包括其他资源的短板。我们今天反而是这个这个放弃过去的這個门户之见，啊其实其实是一起在积极拥抱这个时代，并且一起是在这个共赢的这么一个一个一个一个时期。好吧。所以这就是我们的理解。这本质上其实就是能力的互补，然后这个资源的互补。啊我们不是竞争，我们我们反而是更多的合作。过去打得头破血流的这个对手，现在也放在一起前进；过去这个井水不犯河水的这个泾渭分明的这种竞争区域，现在也逐渐在一些融合。好吧。

This is very interesting question, a very good question. In fact, what we observed is 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 is 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 complementary institutions coming from different backgrounds of enterprises, which we have mentioned back in the general computing or CPU computing age, and this is actually manifesting itself again in this new AI or intelligent cloud era.

Secondly, we would think that this is fundamentally reflects 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 has 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.

各位管理层大家晚上好，感谢接受我的提问。我这边也是想请教两个问题，这可能也是相关的。就是第一个就是关于这个客户的需求这方面，就是我们一季度这个增长还是非常快的，然后想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较强？其中这个推理跟训练的这个占比的趋势大概是怎么样子的？第二个问题是关于可能这是一个小细节问题，就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这个变化，这个期限可能变缩短或者做一些调整？谢谢这两个问题。那我这边简单翻译一下。Assessment management taking my question.

I have a two questions here. First question about the demand outlook for the public cloud.

The 1Q 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.

OK，这个，我是刘涛，这个问题我来回答一下啊。第一呢是说关于二季度的展望，首先呢就是其实刚才我们在前面的内容里也提到过，就是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，但是受限于这个供应链的这个变化，所以可能还是就是需求是极端旺盛的。另外呢就是说从行业上来看，哪些客户行业？其实还是非常丰富的，就是既有互联网的客户，也有这种比如具体的大模型公司，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。对，所以说整体来看就是多个行业现在的需求都在爆发式的增长。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、机器人是明显是以训练的需求为主，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呢，我们还是看到了一些新进市场的训练的玩家在正在进入市场。同时呢这个来自大模型公司和互联网公司的推理，以及比如像Live Coding带来的推理需求也是在增长的。所以这块都在增长。另外呢就是从合约角度来看，因为现在的供给还比较紧张的，所以在我们作为供给侧来说是有比较大的选择权的。我们会和客户签定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。好，就这些。

In terms of the AI demand, as we mentioned, it's extremely strong, and looking at the second quarter, we currently actually have a very long list of a backlog, which is mainly subject to the supply chain restrictions. Now, 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 demands, and particularly for robotics, and also for autonomous driving, actually, they have also a lot of data processing or data treatment demands for the training of their models. For the inference side of the story, we have internet companies and large language model companies coming from their demand for live coding and agents, such use cases.

This is the general recap of the overview of the demand side of things. Now, since you also mentioned about the contract period, we had relatively standard contract periods in the past, but then now in light of the price surge, we currently have more flexible kind of contract period arrangements, which maximizes our profit and benefits.

Thank you.

哎感谢刘总还有田总的回答，谢谢，Thank you.

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，那第一条问题是关于我们小米和金山的這個生态的收入。那我看到在这个季度的同比的增速确实相比于去年四季度，来自于小米和金山的收入的增速有一些加速的趋势。想请问一下我们在小米今年以来的MiLM大模型特别是MiLM 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26至27年和小米的这个关联交易的额度，那想请教一下我们对整个额度的使用率相对于25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30亿人民币左右，那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这个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 Kingsoft ecosystem. I noticed that the revenue growth accelerated compared to the fourth quarter of last year.

Just wondering, is that related to Xiaomi after the MiLM large language model launch, and especially MiLM 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 connected 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 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宜啊，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，包括你们也从这个业界上也看到了这个训练带来的这个资源的需求还是在增长的。另一方面呢就是推理的业务，尤其是在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，对吧，然后再通过更新换代去换新一代的资源去做训练。所以推理的需求也增长很快。当然这里面其实就是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。如果业务回报是正向的很好的话，它其实会放开了去推，那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这个趋势是比较乐观的，第二呢就是我们会这个线性的根据这个业务的发展来去做这个额度的这个预测。好。

On the training segment, the vast majority of that resource demand has come from Kingsoft Cloud, we continue to see growth growing demand in that respect. In inference demand, especially since the launch of V2, MiLM 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 MiLM, we are relatively optimistic. However, it's ultimately subject to the return on Xiaomi's side, we wouldn't personally comment on that, but we generally remain optimistic about that.

For capex spendings, actually the AI era presented huge opportunities for us. Fortunately, we launched our internet compute business back in 2023.

We have well established our supply chain capabilities, and our supply network is in place now. As Mr.

Liu Tao has mentioned, we have seen a surging 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.

Our best estimate is to say for the 2026 is around 15 billion to 20 billion at this moment. Thank you.

Thank you.

Thank you, operator. Thank you, everyone, for joining us today.

If you have any further questions, please feel free to contact us. Looking forward to speaking with you again next quarter.

Have a nice day.