Kingsoft Cloud Holdings Limited (KC) Q1 2026 Earnings Report, Transcript and Summary

Good morning, ladies and gentlemen, and thank you for standing by for Kingsoft Cloud's First Quarter 2026 Earnings Conference Call. [Operator Instructions] 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, and thank you for joining us today. Kingsoft Cloud's First Quarter 2026 earnings release was distributed 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 Board Secretary, Mr. Bo 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 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 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 is now my pleasure to introduce our Chairman and CEO, Mr. Zou. Please go ahead.

[Interpreted] 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 setting 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 reported 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 continues 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 revenues for the first time, reaching 50.1%. Notably, our token services delivered exceptionally strong growth with April 2026 revenue skyrocketing to 53x 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 for 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 3-year framework from 2025 to 2027, we reached RMB 14.2 billion. 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 continue to closely align with the large-scale and a 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 5 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 co-development projects, enabling its engineering teams through flexible multi-modal 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 counting platforms to build a supply chain public information platform in Hubei, enabling resources efficiency, data interoperability and business collaboration and have now supported the sales migration of multiple municipal and country-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 health care 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 health care institutions. In the enterprise services sector, we delivered a green energy operation platform for a leading clean energy service provider, enabling effective intensive management of large heavy-duty truck fleet. 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 products and technology, we continue to stay committed to a technology-driven approach closely aligned with AI cloud demand 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. 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 course, 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 a greater long-term value for our customers, shareholders, employees and society. Next, I will hand over to our CFO, Ms. Yi Li, who will walk you through our first quarter financial results. Thank you.

Thank you, Mr. Zou and [indiscernible], 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 the 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 8 quarters, reaching RMB 2,704 million this quarter. For the first time, our AI business became a 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 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 RMB 3 billion this quarter, and 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 RMB 2,704 million. Of this, revenues from public cloud sources were RMB 1,996 million, up 47% from RMB 1,353 million in the same quarter last year. Revenues from enterprise premium services reached RMB 707 million, up 50% from RMB 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. IDC costs 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 819 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 14% 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 personnel expansion of Camelot. Fulfillment costs and other costs were RMB 2 million and RMB 51 million this quarter. Our adjusted gross profit for the quarter was RMB 351 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 server 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 RMB 455 million, remaining stable compared with same quarter last year and last quarter, of which our adjusted R&D expenses were RMB 184 million, decreased by 8% from same quarter last year. Adjusted selling and marketing expenses were RMB 112 million, increased by 4% year-over-year. Adjusted general and administrative expenses were RMB 159 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 expenditure, 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 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.

[Operator Instructions] We will take our first question, and the question comes from Liping Zhao from CICC.

[Interpreted] Congrats on another strong quarter. So I have 2 questions. The first one is relating to your StarFlow MaaS platform. Mr. Zou mentioned that the revenue of the MaaS platform increased 53x from January to April. Could you share the current revenue scale and margin levels? And what's management's outlook on this business? And 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?

[Interpreted] So our token business actually started off at a relatively small base, let's say, end of last year and the beginning of this year. However, traditionally, we have already maintained a very strong customer base of very large-scale leading customers. So at the beginning of this year, we're starting to meet huge demand coming from such customers in light of the surge of agent demand, the surge of AI coding demand in such use cases. So obviously, the demand was huge and very strong, but it's generally -- but in a way, our business was restricted by the underlying resources that is available to us. So I would say that, obviously, we're optimistic about the growth of this business. However, we need to -- 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. And 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. And we do see a lot of improvement in margin from a certain perspective, 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. So 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. So we will not, at this stage, talk more about the specific margin numbers.

[Interpreted] So in relation to your second question about the selling and purchasing price in relation to our business. So yes, as far as we recognize, the demand for our cloud computing services have been surging tremendously. So is the pricing from our upstream, which includes from components to holistic servers to other raw materials. So the current consensus of the market, including our customers, is that the price hiking, the price surge trend will actually continue, not only already happened in Q1, but also will continue in Q2 and maybe some quarters to follow. So they would believe that the current time point to secure more computing power is actually the right moment to do so. And because of that, the pass-through of the price -- of the cost pressure coming from our upstream is actually doable and would not affect our -- it would not negatively affect our margin levels in this current market situation.

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

[Interpreted] The first question is regarding the gross margin in the first quarter. We noticed that the gross margin dropped a bit in first Q, and what are the main reasons? Has the positive effect of the product price increase has been factored in already? And 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 to GPU rental companies and telcos. How does management think of cloud competitive position and advantages in this landscape?

Great question. For the first -- the first quarter margin, we can see a 3% percentage decrease. This is mainly -- I think the first factor is the seasonal factor because there is the 30% revenue come from the public -- enterprises cloud. So that is the first reason. And the second one is the upfront cost incurred for future revenue generating activities with certain customers. For the coming quarters, we expect the gross margin will recover to normal level.

[Interpreted] So this is a very interesting question. It's a very good question. So in fact, we observed a relatively interesting change in market landscape starting in 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. And what you mentioned in your question is also -- it also exemplifies the close cooperation between private enterprises and state-owned enterprises. And 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, GPU computing age, and this is actually manifesting itself again in this new AI for intelligent cloud era. And secondly, we think that this fundamentally reflects the strong discrepancy between -- or the strong gap, the big gap between supply and demand in today's market. So 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. So 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 the shortcomings and we work together to serve the needs of the end customers.

Your next question comes from the line of Daley Li from Bank of America Securities.

[Interpreted] I have 2 questions here. First question about the demand outlook for the public cloud. The 1Q result is pretty strong. And how do we see the demand trend in Q2 and the second half this year? Regarding the demand mix, how is the trend for inferencing and model training? And the second question is about the contract term with our clients. As the upstream costs are in a rising trend, are we taking like a shorter-term contract -- any change in terms of the contract terms?

[Interpreted] So in terms of AI demand, as we mentioned, it's seasonally strong. And looking at the second quarter, we currently actually have a very long list of our 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. And I would say that out of which the autonomous driving and robotics generally tend to have very strong model training requirements and demand. And particularly for robotics, they have also -- also for autonomous driving, actually, they have also a lot of data processing or data treatment requirements demand for the training of their models. And for the inference side of the story, we have the Internet companies and large language model companies coming from their demand for AI coding and agents such use cases. So this is a general 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 this new -- the supply chain, the price surge, we currently have more flexible kind of contract period arrangements, which maximizes our profit and benefits.

Your final question comes from the line of Timothy Zhao from Goldman Sachs.

[Interpreted] Congrats on the very strong results. My first question is regarding your revenue from Xiaomi and Kingsoft Cloud -- and Kingsoft Ecosystem. I noticed that the revenue growth accelerated compared to the fourth quarter of last year. Just wondering especially related to Xiaomi 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? And after you announced the [indiscernible] transaction -- revenue cap with Xiaomi for this year and next, just wondering how do you think about the utilization rate versus last year? And my second question is regarding your CapEx and also lease assets. I noticed that the total amount spent was around RMB 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?

[Interpreted] So on the training, the vast majority of those resource demands come from Kingsoft Cloud. We continue to see growth -- growing demand in that respect. In inference demand, especially since the launch of V2. MiMo V2, a lot of underlying resource has been reallocated to do the training for that -- to do the inference for that model. Now 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. So probably we don't have to personally comment on that, but we generally remain optimistic about that.

For CapEx in the 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. But we have to admit the supply chain capacity is the primary limiting factor for the capital spending for the 2026. And we estimate that our base estimate to say for the 2026 is around RMB 15 billion to RMB 20 billion at this moment.

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

Thank you, operator. Thank you once again 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.

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 interpreters present on the live call.]