Prepared remarks
Good morning, ladies and gentlemen, and thank you for standing by for Kingsoft Cloud's Second Quarter 2026 Earnings Conference Call. Please note that today's call is being recorded. I will now turn the call over to Mr. Jacky Zuo, Senior Director of Capital Markets at Kingsoft Cloud. Jacky, please go ahead.
Thank you, operator. Hello, everyone, and thank you for joining us today. Kingsoft Cloud's Second Quarter 2026 earnings release was issued earlier today and is available on our IR website and through PR Newswire. Joining us today are Mr. Zou Tao, Chairman and CEO; Ms. Li Yi, CFO; Mr. Liu Tao, Senior Vice President; Mr. Kaiyan Tian, Senior Vice President; Ms. Yu Jun, Vice President; Mr. Zhu Rilong, Associate Vice President; and Mr. Kuang Jian, Board Secretary and Associate Vice President. Mr. Zou will discuss our business performance and key developments, followed by Ms. Li with a review of our financial results. Management will then take your questions. Consecutive interpretation will be provided for convenience and for reference only. In the event of any discrepancy, management's statements in the original language will prevail. Before we begin, I would like to remind you that today's call contains forward-looking statements made under the safe harbor provisions of U.S. Private Securities Litigation Reform Act of 1995.
These statements involve risks and uncertainties, and actual results may differ materially from those expressed or implied by the forward-looking statements. Additional information concerning factors that would cause actual results to differ materially is included in the company's filings with the U.S. SEC. The company undertakes no obligation to update any forward-looking statements, except as required by applicable law. Unless otherwise stated, all financial figures discussed on today's call are denominated in renminbi. With that, it is my pleasure to turn the call over to our Chairman and CEO, Mr. Zou. Mr. Zou, please go ahead.
Hello, everyone, and welcome to Kingsoft Cloud's Second Quarter 2026 Earnings Call. I am Zou Tao, CEO of Kingsoft Cloud. This quarter, we saw further evolution in the AI cloud market. The rapid growth of the open source model ecosystem is creating significant opportunities for neutral cloud providers. At the same time, our long-held vision of bringing AI to every industry is becoming a reality through a combination of Model as a Service, Agent as a Service and FTE services. Against this backdrop, Kingsoft Cloud remains committed to technology leadership and high-quality sustainable growth. We are accelerating the development of our AI cloud, MaaS and FTE businesses with encouraging progress. First, AI continues to drive strong revenue growth. Total revenue reached a record of RMB 3.07 billion, up 31% year-over-year. AI cloud gross billings increased 82% to RMB 1.33 billion and accounted for 56% of public cloud revenue.
MaaS revenue also grew strongly with Q2 revenue up more than 12x from the Q1 level. Second, profitability improved significantly. Adjusted gross margin rose to 15.4%, up 2.4 percentage points quarter-over-quarter. Operating profit turned positive for the first time with adjusted operating margin reaching a record high of 4.0%. This reflects our continued efforts to capture AI opportunities, improve revenue quality and drive greater operating efficiency. Third, our customer mix continued to improve with stronger momentum both within and outside our ecosystem. Revenue from the Xiaomi and Kingsoft ecosystem reached RMB 810 million, up 28% year-over-year and accounting for 26% of total revenue. Revenue from our top 5 non-ecosystem customers grew 51%. Our AI cloud business now serves a broad range of sectors, including Internet services, frontier AI labs, embodied AI, autonomous driving, AI for science, fintech, gaming and online video, to name a few.
This diversified customer base supports continued growth while allowing us to allocate computing resources more flexibly and strengthen our pricing power and business resilience. Now let me walk you through our business progress in the second quarter of 2026. In Public Cloud, revenue reached RMB 2.36 billion, up 45% year-over-year. First, Xiaomi continues to expand AI across its Human x Car x Home ecosystem, while WPS AI continues to advance. As the only strategic cloud platform for the Xiaomi and Kingsoft ecosystem, we see substantial AI-driven growth opportunities. In June, our shareholders approved a further increase in the annual caps for connected transactions with Xiaomi. The combined caps for 2026 and 2027 now total RMB 10 billion, 39% higher than before the adjustment. In the first half, public cloud revenue from Xiaomi and Kingsoft grew 54% year-over-year. Second, we further strengthened the MaaS capabilities of our StarFlow platform.
StarFlow now supports 120 models with major new models launched on the platform in sync with their market release and serves more than 230 enterprise customers. Third, we deepened cooperation with leading customers in emerging sectors. We delivered large-scale computing clusters to leading embodied AI and autonomous driving customers, supporting rapid model iteration and expanded our cooperation with a leading AI for science customer to support the growth of this new business. In Enterprise Cloud, revenue reached RMB 710 million. In public services, we signed an agreement with the Nanjing Communications Administration of the Yangtze River to build Yanghai Cloud, a dedicated digital infrastructure platform for Yangtze River Shipping. We also formed a strategic partnership with the Wuhan Municipal Data Bureau and Wuhan Cloud across computing resource interconnection, digital governance, intelligent computing applications and ecosystem development.
In digital health, we are leading a project under the National Key R&D program on biology and information integration to develop a cloud-based virtual surgery platform, which has been deployed in more than 30 hospitals nationwide. In enterprise services, we deepened our cooperation with Yunshang Gansu to jointly build and operate the Gansu Provincial Public Services Cloud under an integrated investment construction and operations model. In products and technology, we continued to upgrade our full stack AI capabilities for intelligent computing and AI application deployment. This quarter, we further optimized the model deployment on StarFlow MaaS for high concurrency inference, significantly improving throughput for several core models and enabling more granular access usage and model-level management. We also launched AgentKit, providing secure sandbox, knowledge and memory management, and evaluation and governance tools to help enterprises build production-grade AI agents.
At the same time, we are making general purpose cloud products such as database and storage easier for agents to access and use. We enhanced the StarFlow training and inference platform with more flexible resource scheduling, sharing and allocation for training and fine-tuning workloads, improving utilization and reducing development and operating costs. For private deployment of domestic AI infrastructure, our Galaxy Stack platform completed deep integration and full life cycle visual management for multiple mainstream domestic AI chips. Looking ahead, we will continue to capture opportunities both within and outside our ecosystem, improve the operating efficiency of our computing assets and strengthen our profitability and cash generation capability amid AI industry tailwinds. We remain committed to creating long-term sustainable value for our customers, shareholders and society. With that, I will hand the call over to our CFO, Li Yi, who will review our second quarter financial results. Thank you.
Thank you, Mr. Zou and Mr. Tian, and thank you all for joining the call today. I will now discuss the second quarter financial results using RMB as currency. Before we walk through the details of the financial results for the second quarter, I would like to highlight the following aspects. First, our quarterly revenue reached over RMB 3 billion for the first time in our company's history, up year-over-year for the ninth consecutive quarter. In particular, our AI cloud gross billing increased 82% year-over-year to RMB 1.33 billion, accounting for over 43% of our total revenue versus 31% a year ago. This reflects a continued structural shift in our business mix towards AI. Second, our profitability has improved. Our adjusted gross margin was 15.4%, up 2.4 percentage points quarter-over-quarter and 0.5 percentage points year-over-year. Our adjusted EBITDA margin reached 36%, up from 17% in the same quarter last year and 28% last quarter.
Notably, we returned to breakeven at the operating income level this quarter and recorded an adjusted operating profit margin of 4%. This outcome validates our ability to turn strong AI business demand into healthy profit growth. Third, we continue to invest to accelerate the build-out of our AI compute capacity. Capital expenditures together with right-of-use assets obtained through third-party financing and finance leases reached RMB 3.3 billion this quarter versus RMB 2.9 billion last quarter and RMB 2.8 billion in the same quarter last year. Now let me walk you through our financial results for the second quarter of 2026. This quarter, total revenue was RMB 3,072 million, up 31% year-over-year or 40% quarter-over-quarter. Of these, revenues from public cloud services were RMB 2,358 million, up 45% from RMB 1,625 million in the same quarter last year. Revenues from enterprise cloud services reached RMB 714 million compared with RMB 724 million in the same quarter last year, down slightly by 1% year-over-year.
Total cost of revenues was RMB 2,606 million, representing a 30% year-over-year increase, mainly due to continued investment in AI cloud infrastructure. IDC costs increased by 23% year-over-year from RMB 803 million to RMB 990 million this quarter, mainly due to increased rack services. Depreciation and amortization costs increased by 75% year-over-year from RMB 552 million in the same quarter of 2025 to RMB 964 million this quarter, largely due to the depreciation of newly acquired AI infrastructure, including servers and network equipment. Solution development and services costs increased by 4% year-over-year from RMB 564 million in the same quarter of 2025 to RMB 586 million this quarter, with the modest increase mainly due to higher costs incurred in AI transformation in solution development and delivery. Fulfillment costs and other costs were approximately RMB 66 million in total this quarter versus RMB 92 million in the same quarter last year.
Our adjusted gross profit for the quarter was RMB 472 million, increased by 35% year-over-year and 34% quarter-over-quarter. Adjusted gross margin was 15.4%, up from 14.9% in the same quarter last year and from 13% last quarter. The increase was driven by higher gross margin in the public cloud business, thanks to strong AI demand tailwinds. On the expense side, excluding share-based compensation expenses, our total adjusted operating expense was RMB 391 million, a decrease from RMB 561 million in the same quarter last year and from RMB 455 million last quarter, mainly reflecting our disciplined cost and expense control. Our adjusted research and development expenses were RMB 184 million, up 1% year-over-year. Adjusted selling and marketing expenses were RMB 102 million, down 7% year-over-year. Adjusted general and administrative expenses were RMB 105 million, down 51% year-over-year, largely due to lower credit loss expenses.
Our adjusted operating profit was RMB 124 million, an improvement from an adjusted operating loss of RMB 166 million in the same period last year. This improvement was primarily driven by the expansion of our revenue scale, higher gross margin and enhanced operating efficiency. Adjusted operating profit margin was 4% this quarter compared with minus 7.1% in the same period last year and minus 2.2% last quarter. Our adjusted net loss was RMB 6 million, down from RMB 300 million in the same quarter last year and RMB 237 million in the previous quarter. Our non-GAAP EBITDA profit was RMB 1,100 million, increased by 171% from RMB 406 million in the same quarter last year. Our non-GAAP EBITDA margin achieved 36% compared with 70% in the same quarter last year and 82% last quarter. This was mainly due to our improving gross profit as well as higher operating costs in our cost of debt as we accelerate our AI computing capacity build-out.
As of June 30, 2026, our cash and cash equivalents totaled RMB 4,674 million compared with RMB 4,904 million as of March 31, 2026. The modest decrease was mainly due to our continued investment in AI infrastructure to support business growth. Looking ahead, we aim to capitalize on the explosive growth in AI demand by further investing in infrastructure, expanding our product and service offerings, managing credit and liquidity risk and improving operating efficiency. We remain committed to our AI strategy and continue to deliver high-quality growth to our shareholders. Thank you all.
So this concludes our prepared remarks. We will now begin the Q&A session. If possible, please ask your questions in both Mandarin and English. So operator, please proceed.
Questions and answers
We will take our first question. Your first question comes from Liping Zhao from CICC. We will drive demand by further investing in infrastructure, expanding our product and service offerings, managing credit and liquidity risk, and improving operating efficiency. We remain committed to our AI strategy and continue to deliver high-quality growth to our shareholders. Thank you all. Jacky Zuo, Senior Director of Capital Markets. So this concludes our prepared remarks. We will now begin the Q&A session. If possible, please ask your questions in both Mandarin and English. So operator, please proceed.
I have two questions on your MaaS business. First, how will improvements in open source model capabilities affect the company's MaaS business? Based on your observations, what's the current usage growth trend and which use cases are driving it most? And second, given the payback period for the MaaS business might be shorter, will the company allocate more resources to it?
To answer your questions: The development in open source large language models has mainly three impacts. Number one, we're seeing very big demand coming from startups and enterprises. Traditionally, foreign models have been taking the lead in this area. However, since the launch of GLM and K3, these high-performance models have driven increasing adoption among users in Mainland China opting for domestically developed large language models. Second, the increasing use of agentic scenarios has also changed our business. In response, we have launched the agentic product to satisfy such needs. Third, for day-to-day routine tasks and workloads, customers often choose price-for-performance models, which are essentially the Chinese models. That is why the development of open source large language models is beneficial for our business. Regarding the balance between MaaS and computing power businesses: we have different business models for these two lines.
For computing power services, once we sell the computing power, utilization tends to be much higher and we usually secure long-term contracts to maintain utilization over prolonged periods, making it relatively stable. MaaS, however, is subject to factors such as token price fluctuations, the launch of new models that customers prefer, and the operating efficiency we can achieve in delivering MaaS. Therefore, we generally balance the two business models so that they complement each other, and we dynamically evaluate resource allocation between them.
We will take our next question. Next question comes from Wenting Yu from CLSA.
Since June, how has the chip procurement progressed in recent months? And what's your latest full-year CapEx guidance? And the second question is about the enterprise cloud. This segment of revenue has decelerated in the past two quarters. How should we think about the full-year enterprise cloud growth? And what's the AI transformation and medium-term positioning for this segment?
Three points on procurement and CapEx. Number one: since 2023 there have been ongoing discussions about limited supply, and I would say constrained supply has become a new norm. Second, despite supply constraints, Chinese cloud computing and AI industry development has not been largely restricted. We address supply limitations by increasing the number of business partners and suppliers we work with and by improving the compatibility with Made-in-China chips. Many domestic chips are becoming mature and are particularly good for inference use cases. Number three: CapEx timing is lumpy by nature because purchases are large and occur in relatively few transactions, so monthly figures are not linear. For the full-year CapEx estimate, we expect it to remain in line with our prior expectations. I will hand over to our CFO, Li Yi, for details.
Our CapEx in H1 includes capitalized assets for lease arrangements, reaching RMB 6.2 billion in the first half of 2026, accounting for over 75% of our full-year CapEx last year. While July data cannot fully represent third-quarter trends, it clearly shows tangible growth acceleration. Accordingly, we maintain our full-year CapEx base case unchanged at RMB 15 billion. Thank you, Tian.
We will take our next question.
Sorry, we need to continue for another question.
Apologies.
Regarding enterprise cloud: Although we are seeing relatively slower growth in the enterprise cloud segment, it's not appropriate to view this as a linear decline. Three reasons: First, upstream supply pricing increases in recent quarters have affected prospective customers — especially state-owned enterprises and government agencies — causing them to frequently adjust budgets and delay decision-making. Second, enterprise cloud has strong seasonality, with delivery and revenue recognition concentrated in the second half of the year, and we have a strong pipeline for H2. Third, this apparent slowdown is partly due to a proactive adjustment in our business structure, shifting from a project-based model to an operating-based model; operating-based revenue is automatically classified as public cloud from a reporting perspective. Therefore, this is not simply a weakening of the enterprise cloud business.
We will take our next question. Your question comes from Timothy Zhao from Goldman Sachs.
My first question is regarding the MaaS business. Compared to peers in the market, how do you think about Kingsoft Cloud's competitive advantage in MaaS services in terms of application scenarios, etc.? Could you share more about the revenue recognition and the profitability profile of the MaaS service business? Second, regarding the overall pricing trend in the AI cloud business: what is the latest trend over the past couple of months? What have you heard from customers after you announced certain price hikes or discount reductions over the past few months and can you quantify the impact from the price changes on your overall AI cloud revenue growth?
On our positioning in MaaS: We have a unique stance. Unlike some full-stack cloud providers that push in-house proprietary models, we do not limit customers to models affiliated with our company. Instead, we support and encourage customers to use the models they prefer, such as GLM and others. Second, owning proprietary computing capacity is important to secure profitability in this business; it enables us to achieve higher margins. Regarding pricing: we have adjusted prices in two main areas — storage and computing. Storage increases are generally easier to pass through because incremental storage associated with intelligent computing is a relatively small portion of the overall ticket size, and most customers have accepted such changes. For computing, because of our PaaS capabilities and operating and network services, we are able to pass through cost increases to customers in many cases and in some cases improve profitability. This quarter we also had projects using managed services, which are more asset-light, and we expect to see more of these reflected in our financials.
We will take the next question. Your next question comes from Wei Xiong from UBS.
Congrats on a solid quarter. Considering the proprietary models and user ecosystem of other cloud providers, how should we think about your long-term positioning in the cloud market and the sustainable margin level down the road?
We believe a MaaS or AI cloud service provider must offer the top models customers want and provide stable services. As a neutral cloud player, we maintain good relations with leading model providers and LLM labs and can provide the best model for each customer's needs. Technically, our platform provides high availability and reliability aligned with SLAs. On profitability, it's important to work closely with LLM firms to optimize model inference. That includes working with them on optimization techniques and model weightings to increase inference efficiency. In some cases, we have achieved inference efficiency levels close to, or on par with, the efficiency achieved by the LLM providers themselves.
We will take our final question. Your final question comes from Yang Liu from Morgan Stanley.
I would like to ask on the two business models, computing power leasing and model as a service: what is the ROIC for these two business models? And what is the marginal change for the ROIC?
At this stage, we don't disclose separate ROIC for MaaS and AI computing power services because ROIC varies across projects driven by CapEx cycles, gross margin, fixed assets and depreciation policies. Overall, MaaS delivers much better profitability than AI computing power services at this stage. We have seen continued improvement in operating leverage as our AI business scales up, fixed costs are steadily diluted and our trailing 12 months adjusted operating profit has turned positive, driving a gradual recovery in our overall ROIC. We adhere to a demand-driven and disciplined AI investment strategy with a strong focus on capital efficiency. With continuous business structure optimization and maturing AI commercialization, we expect our overall ROIC to keep improving steadily.
There are no further questions. This concludes the question-and-answer session. I will hand back for closing remarks.
Okay. Thank you all for joining us today. If you have any further questions, please contact our IR team. So have a good evening. You may now disconnect. Thank you.
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.