Good day, and thank you for standing by. Welcome to the Kingsoft Cloud Holdings Limited First Quarter 2025 Earnings Conference Call. At this time, all participants are in a listen-only mode. After the speakers' presentation, there will be a question and answer session. To ask a question during the session, you will need to press star one one on your telephone. You will then hear an automatic message advising your hand is raised. To withdraw your question, please press star one and one again. 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, IR Director of Kingsoft Cloud Holdings Limited. Please go ahead.

Thank you, Operator. Hello, everyone, and thank you for joining us today. Kingsoft Cloud Holdings Limited's first quarter 2025 earnings release was distributed earlier today and is available on our IR website at ir.ksyun.com, as well as on via newswire services. On the call today from Kingsoft Cloud Holdings Limited, we have our Vice Chairman and CEO, Tao Zou, and the CFO, Haijian He. Mr. Zou will review our business strategies, operations, and the company highlights, followed by Mr. He, 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 interpretation. Our interpretations are for your convenience and reference purposes only. In case of any discrepancy, management statements in the 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 US 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 US Securities and Exchange Commission. 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 Vice Chairman and CEO, Tao Zou. Please go ahead.

Thank you. Hello, everyone. Thank you, and welcome all for joining Kingsoft Cloud Holdings Limited's first quarter 2025 earnings call. This quarter, we continued to steadily advance our business to the target of high quality and sustainable development, centering on key areas of AI. First, we recorded year-over-year revenue growth of 11%, reaching RMB 1.97 billion. Both public cloud and enterprise cloud achieved year-over-year growth, among which public cloud increased by 14%, reaching RMB 1.35 billion. Second, we continued to drive progress with AI. This quarter, AI gross billing reached RMB 525 million, representing a year-over-year increase of over 200% and a quarter-over-quarter growth of 11%, further contributing 39% of public cloud revenue. In addition, this quarter, we are accelerating the construction of our computing clusters with more flexible capital deployment, which is expected to launch service officially in the second quarter, further boosting our AI business revenue. Third, as the only strategic cloud platform of the Xiaomi and Kingsoft ecosystem, our business cooperation with the ecosystem progressed smoothly. This quarter, revenue from Xiaomi and Kingsoft ecosystem reached RMB 500 million, up 50% year-over-year, with its contribution to total revenue further increasing to 25%. By fully integrating the strength of both parties and jointly expanding cloud infrastructure for the AI era, our collaboration with Xiaomi and Kingsoft in the AI space continued to progress and deepen. Finally, in terms of profitability, this quarter, our non-GAAP gross profit was RMB 327 million, representing a year-over-year increase of 9.6%. Non-GAAP EBITDA margin reached 16.2%, an increase of 14.3 percentage points year-over-year, mainly attributable to the continued increase in the proportion of AI business revenue. However, we also witnessed that our profits have experienced some fluctuation while non-GAAP gross margin declined by 2.6 percentage points quarter-over-quarter to 16.6%. The decline in gross margin was mainly due to the reduced profit contribution from a lower proportion of enterprise cloud revenue as well as the impact of front-loaded investments of computing resources. The non-GAAP operating profit was impacted by the decline in gross profit, resulting in the loss of RMB 55 million this quarter. Non-GAAP operating margin was negative 2.8%, representing an improvement of 4.4 percentage points compared with a loss of 7.2 percentage points in the same period last year, and turned from a profit to a slight loss quarter-over-quarter. Despite quarter-over-quarter fluctuations in financial performance this quarter and the headwinds of both market pressure and supply chain uncertainties, we remain firmly on track with our long-term strategy and continue to move forward with confidence. We have strengthened our foundation in ecosystem cooperation, computing infrastructure deployment, and AI application, advancing the strategic layout of our company's overall AI cloud services. Now let me walk you through the key business highlights of the first quarter of 2025. In the public cloud space, revenue reached RMB 1.35 billion this quarter, representing a year-over-year increase of 14%. Our AI business, as a key growth driver, reported a significant increase in gross billings to RMB 525 million, up over 200% year-over-year and 11% quarter-over-quarter, accounting for 39% of public cloud revenue, continuing to lead the industry. Based on steady usage growth in ecosystem customers and foundation model customers, computing demands for AI applications in Internet customer business scenarios, such as online education and online travel, also made breakthroughs. In the construction of clusters, we efficiently coordinated and responded quickly to the demand schedule of key customers, creating a benchmark case of delivering full-spectrum cloud services for large-scale clusters within the quarter. In addition, with flexible capital cooperation models, we ensured sufficient underlying computing power supply to support the rapid growth of our AI business. In the enterprise cloud space, revenue reached RMB 616 million this quarter, representing a year-over-year increase of 5%. Affected by seasonal slowdowns in project delivery and acceptance process, enterprise cloud revenue declined quarter-over-quarter. By industry, in the public service sector, we are advancing the application of AI in public service clouds and state-owned asset clouds. Actively embracing the AI-driven trend, Kingsoft Cloud Holdings Limited has built a rich set of model resources through an open-source model marketplace while providing a one-stop model toolchain that covers key processes, including data processing, model fine-tuning, model evaluation, and model quantization. We remain committed to delivering full-process one-stop AI services to help customers deeply optimize model performance in their business scenarios. In the healthcare sector, we initiated the construction of a platform for mutual recognition and sharing of test and examination results in Wuhan. Kingsoft Cloud Holdings Limited's medical imaging cloud capabilities, which have been deployed in regions such as Jiangsu and Chongqing provinces, will once again validate our capabilities. Our capabilities also expanded from imaging scenarios to test and examination scenarios and have been further replicated and extended to the entire Hubei province market. In terms of product and technology, we uphold the principle of building success based on technology and innovation, focusing on delivering best-in-class customer experiences across our core product offerings. This quarter, we continue to enhance the product capabilities of our intelligent cloud computing services. Our Xinyu training and inference platform, as a one-stop AI development and deployment platform, remains committed to providing enterprises with efficient, elastic, and cost-effective model training and inference services. The integration of high-quality models, including the one from Xiaomi, will further expand the platform's ecosystem capabilities and help customers apply AI technologies in scenarios such as natural language processing, multimodal interaction, and intelligent decision-making. Overall, our AI business continued to grow rapidly, and our cloud services have entered a new development cycle. In the public cloud space, we strengthened our capabilities in infrastructure training, inference platforms, and AI tools to help customers reduce training costs and improve stability, convenience, and efficiency throughout model development, fine-tuning, and usage. In the enterprise cloud space, with a focus on AI, data, and office productivity, we provide one-stop model solutions and services under the trend of enterprise AI plus scenario development. Looking ahead, we will maintain deep cooperation with the Xiaomi and Kingsoft ecosystem, fully understand and explore new AI opportunities, and continue to create value for our customers, shareholders, employees, and other stakeholders. I will now pass the call to our CFO, Haijian He, to go over our financials for the first quarter of 2025. Thank you.

Thank you, Mr. Zou, and thank you all for joining the call today. I will now walk you through the financial results for the first quarter of 2025. This quarter, our AI strategy continued to drive our growth and laid a foundation for future development. Total revenues for this quarter were RMB 1,970.0 million, reflecting an 11% year-over-year increase. Out of this, revenues from public cloud services were RMB 1,353.5 million, up 14% from RMB 1,187.4 million in the same quarter last year. This growth was mainly fueled by a surge in AI-related business, with the billing reaching RMB 525 million. This quarter, our capital expenditure reached RMB 605 million. Revenues from enterprise cloud services reached RMB 616.5 million, up 5% from RMB 588.2 million in the same quarter last year, primarily driven by increased demand in industry solutions. However, we have witnessed a 25% sequential decrease in enterprise cloud revenues, which was mainly due to the seasonality impact. Total cost of revenue was RMB 1,651.7 million, up 11% year-over-year, which was in line with our revenue expansion. IDC costs dropped by 6% year-over-year from RMB 768.5 million to RMB 722.8 million this quarter, reflecting our execution on cost control and better resource utilization. Depreciation and amortization costs increased from RMB 183.5 million in the same period of last year to RMB 378.5 million this quarter, mainly due to the depreciation of newly acquired high-performance servers to expand our AI business. Solution development and service costs rose by 13.3% year-over-year from RMB 446.0 million to RMB 505.2 million, driven by expansion in personnel to support revenue growth. Fulfillment costs and other costs were RMB 3.1 million and RMB 42.1 million this quarter, respectively. Our adjusted gross profit for the quarter was RMB 327.7 million, a 9.6% increase year-over-year, while a decrease of 23.4% quarter-over-quarter. Adjusted gross margin was 16.6% in this quarter, compared with 16.8% in the first quarter of 2024 and 19.2% in the fourth quarter last year. Our adjusted gross margin has been negatively impacted by the seasonality of enterprise cloud services and higher upfront investments into servers and racks for AI business. On the expenses side, excluding share-based compensation, our total adjusted operating expenses were RMB 427.3 million, a decrease of 9% year-over-year and a 4.3% quarter-over-quarter. Of which, our adjusted R&D expenses were RMB 200.8 million, increased by 4% from the same quarter last year. Adjusted selling and marketing expenses were RMB 107.8 million, increased by 10.1% year-over-year. Adjusted G&A expenses were RMB 118.7 million, decreased significantly by 13.6% year-over-year due to the decline of credit loss. Our adjusted operating loss was RMB 55.8 million, narrowed by 56% from RMB 127.0 million in the same period of last year. The improvement was mainly due to the increase of gross profit and a decrease of credit loss expenses. However, the adjusted operating profit turned to a loss from last quarter, which is primarily due to the decrease of gross profit in this quarter. Our non-GAAP EBITDA profit was RMB 318.5 million, increased by RMB 8.3 million from RMB 33.2 million in the same quarter of last year. Our non-GAAP EBITDA margin achieved 16.2%, compared with 1.9% in the same quarter last year, mainly due to our strong commitment to AI cloud computing development, strategic adjustments, business structure, and our strict control over costs and expenses. As of March 31, 2025, our cash and cash equivalents totaled RMB 2,322.7 million, providing us a strong liquidity position to support operations and AI investments. Looking ahead, our cloud infrastructure is ready to serve in a short time. The demand from ecosystems and other AI application scenarios not only fuels our business growth but also reinforces our confidence in this trajectory. With demand for AI cloud service continuing to grow, we are well-positioned to capture and capitalize on AI opportunities. Thank you. We are now happy to take your questions.

Please ask your question in both Mandarin Chinese and English because of consecutive interpretation. Operator, please go ahead. Thank you. As a reminder, to ask a question, please press star one one on your telephone and wait for your name to be announced. To withdraw your question, please press star one one again. We will now take the first question from the line of Brian Gong from Citi. Please go ahead.

I will translate myself. Thanks to management. So one is, you know, for both public cloud and the enterprise cloud, the growth seems a little bit weaker than our previous expectation. What are the reasons behind this? And how should we see the full-year growth right now? And secondly, recently, Xiaomi released its own large language model. How does management leverage this, and what's the latest demand from Xiaomi?

Thank you very much for your question. So in relation to the first question about the growth speed, in terms of both public cloud and enterprise cloud, as we noted in the prepared remarks, especially for the enterprise cloud, the seasonality is quite evident. That includes impact for both our own enterprise cloud services as well as the business from Camelot. Because, obviously, Q1 houses the factor of the Chinese New Year. A lot of customers for enterprise cloud business are still doing their budgeting. Now in terms of the public cloud, as we mentioned before, the public cloud business of Kingsoft Cloud Holdings Limited focuses mainly on key customers, which typically are large customers. And they have their own cycle of the construction of the clusters before they can actually get online and generate revenue. So in fact, in the first quarter, we have delivered a 512-node cluster to our key customers. However, that delivery time point was only at the end of March, and therefore, the revenue and profit reflection in the financial numbers will only be shown in the next quarter, which is the second quarter, Q2. Now in relation to your question about the model from Xiaomi, in fact, the Xiaomi's 7 billion parameter model was actually trained from our cluster. And in fact, the tremendous growth of Kingsoft Cloud Holdings Limited's AI business has much to do with the demand coming from Xiaomi. In the long-term perspective, the tremendous demand for model inference coming from Xiaomi still has significant potential. However, since we are serving Xiaomi, the pace of Xiaomi's demand has a lot to do with when and the amount the revenue and profit will show on our financial statements on a quarterly basis.

Thank you. We will now take the next question from the line of Sheridan Suncroft from CICC. Please go ahead.

Thanks, management, for taking my questions. First of all, I noticed that Kingsoft Cloud Holdings Limited and Kingsoft Office have recently jointly launched an AI all-in-one model machine for the government affairs sector. How do you view the business opportunities in the government affairs AI field? And also, could you introduce the pricing models of this all-in-one machine? Secondly, could you please update on the non-GAAP OP margin outlook for the subsequent quarters? Thank you.

So let me quickly translate. As rightly pointed out, the market for AI in the office automation targeting the government space has been developing very fast, and therefore, that's the reason why Kingsoft Cloud Holdings Limited and Kingsoft Office have come together to jointly develop and offer a plan or a solution to such a market, which has been actually validated by the market. So that integrated solution is actually an integration of both software and hardware, and notably, in the software portion, there's the AI component that helps them become more efficient in office scenarios. And this is targeted for Chinese government agencies in various layers of various tiers. Now in terms of the pricing question you asked, it actually varies based on the different configuration of hardware that we are providing to the customer. So the pricing can actually vary by quite a lot.

Thank you for the question on the margin side. I think probably a few things I want to point out. Given the seasonality in Q1, as probably many of you understand, our primary OPEX is the human capital expenses, so the salaries, compensation, bonuses, and so on. So in Q1, basically, not only do we need to incur the normal salary payment, but also there's a bonus and also certain kinds of employee benefits also incurred in Q1 during the holiday seasons, as you understand. Given the revenue side was affected by the delay of certain projects, and also the top-line growth has been affected by seasonality, the variation of the top-line growth largely affected the bottom line. So the cost structure, especially on salary and compensation, is relatively fixed. That's why it's kind of affecting the OP margin in Q1. It's kind of very straight line given the better margin profile, for example, the AI projects and our relationship with our ecosystem partners, especially for Xiaomi, as our CEO, Mr. Zou, just mentioned, the big project we're likely to deploy on the way, it will be largely booked starting from Q2 going forward. So, hopefully, our top-line growth will drive a better margin expansion in the following quarters. So we are in the view that our OP margin will be better in the following quarters. It depends on the top-line growth, the pacing of that, and the scale of the revenue quality in the following quarters. But on the other hand, we also want to point out that the EBITDA margin will likely be better compared with the OP margin given the nature of the AI business. So as the AI business penetration becomes higher in the public cloud services, hopefully, the EBITDA margin can recover a little bit faster than the OP margin side. So I think I will encourage the audience to probably closely track our gross margin profile and EBITDA margin profile as well as the R&D cost, which are primarily linked to the expenses and the compensation and salaries of employees. I think these are factors that are going to be the leading indicator for the OP margin going forward for the following quarters. So while we don't give formal guidance, I understand Brian also mentioned this, for the full-year top-line revenue in the call today, by the way, in the view that the margin profile in the following quarters likely, especially in the second half of this year, will be better than the first half of this year. And at this moment, we don't give a kind of formal management guidance for the top line, but the margin profile will continue to be better, especially in the second half of this year. Thank you.

Thank you. We will now take the next question from the line of Thomas Chong from Jefferies. Please go ahead.

Thanks, management, for taking my question. My first question is about the AI CapEx and the OpEx breakdown. Can we have an update, like, last quarter? And my second question is about our quarterly CapEx, like Q2. Is the chip ban issue affecting the sequential momentum in CapEx? And my first question is more about the industry landscape. Given that customers are now using more, like, distilled models, smaller models, rather than large models, would that affect the cloud revenue? Thank you.

Thank you, Thomas. I will take the first two questions, and I defer to CEO, Mr. Zou, for the second and third questions. The first question regarding the capital expenditures. So I have mentioned, in this quarter, our total CapEx was RMB 605 million for the first quarter of this year. So if the audience remembers, since last year, we actually diversified the way we're financing the investment into AI, especially infrastructure construction. So our own cash to be used for the CapEx is one part, but also we are going to, for example, do financial leasing, operation leasing with our partners, for example, Xiaomi as well. But also, we are going to get financing, for example, bank loans and certain leasing agreements with state-owned banks in China locally, as well as some leasing companies in China as well to arrange certain off-the-balance-sheet financing arrangements. So I think these are the three ways that we're financing the total AI infrastructure demand. So out of that, I think the reason you probably point out that total CapEx for this quarter is kind of RMB 600 million for this quarter. But I think our total investment into AI also starts to lease certain servers from third parties to reduce our burden to pay out of pocket from our cash. So there's a certain leasing and rental agreement we actually start to negotiate and set up with third parties starting from Q1. So, hopefully, for next quarter, we're going to give some updates regarding our total spending, including both our own cash out of pocket, but also the leasing agreement that we'll start to arrange with third parties. So this is going to be the total investment of the AI infrastructure from our definition. So I'm likely to have some updates for next quarter because we just start to arrange those agreements with third parties to ensure to reduce and save, and to be more efficient in terms of our own cash management. So I think right now, we give the number on total CapEx, but the leasing plus the CapEx and plus our own cash will be another update for next quarter. And also given the OpEx, as I’m mentioning, our R&D expenses for this quarter are around RMB 200 million. And the sales expenses are around RMB 108 million, and the management SG&A is around RMB 119 million. So if you’re putting the three numbers together, it’s roughly about RMB 400 million on the OPEX side, including R&D, sales marketing, and SG&A. This probably can give you a kind of color regarding the total OpEx plus CapEx on a quarterly basis. Thank you.

So, basically, to translate from Mr. Zou's response to the chip ban question. So honestly and very frankly, there surely will be an impact. Right? However, this is actually not the first time for similar kinds of restrictions being imposed on chips. So we have experienced similar things before. And so before this round of restrictions actually hit us, we have had some inventory and storage, so therefore, the short-term impact is not that material. However, from a mid to long-term perspective, there will be a meaningful impact for both Kingsoft Cloud Holdings Limited as a company and for the industry as a whole as well. We mentioned before since 2023, we have already strengthened our cooperation with Made in China computer resources. And that kind of cooperation we have managed to continue since then. And in light of similar restrictions, we have made and we have been well prepared for the gradual substitution of made in China computing resources should restrictions continue to be more restrictive. So the conclusion, the basic conclusion is that there’s no negative impact on revenue and profitability for Kingsoft Cloud Holdings Limited. And the reason has been as follows. The first one is for the traditional HashiCorp model customers, their models have been a hundred billion parameter large language models. And it has historically been using our computing power for training and inferences, and this part is actually not impacted. Secondly, for the more traditional Internet space customers, they have actually always been using relatively smaller models, including the 30B and 10B kind of parameter amounts for our business. So this for us is actually an incremental amount for our revenue development. And thirdly, in the future, for the Xiaomi and Kingsoft ecosystem, we also expect to have extra positive impact coming from the more prevalent usage of relatively small models because more of the model inference would originally come from outside of the Kingsoft Cloud Holdings Limited computing power infrastructure from other companies. Actually, when Xiaomi and Kingsoft started to adopt more medium-sized or smaller-sized models, they're actually starting to use more of Kingsoft Cloud Holdings Limited computing resources. So that's actually another part of potential incremental revenue and profit for us.

Thank you. We will now take the next question from the line of Wenting Yu from CLSA. Please go ahead.

So the first question is, can management share the recent gross margin trends for AI cloud leasing services? Previously, we observed aggressive price competition in the industry mainly focused on model API pricing. Are we seeing the pricing pressure extend to the AI server leasing business as well? And the second question is, following the open sourcing of R1 by Deepstick, how do we see the latest dynamics of model training demand? While there is incremental demand for post-training models, the open-source release of R1 may also lead to some model vendors abandoning further iteration. So how should we evaluate these two factors and their overall impact on the industry?

In relation to the AI cloud service margin or pricing pressure question, let me respond to you from two dimensions, which are internal and external. So externally, as you rightly pointed out, we're experiencing a sort of market concentration for AI players as our customers and therefore, they do have some impact on our new projects which we entered into more recently. And the impact would largely depend on the project size. However, for the old long-term contracts that we have signed in the past, those projects that we entered into in the past, there's no meaningful, no material impact. Another point I want to point out is that starting from the second half of 2024, we're increasingly leveraging the so-called resource pool supply chain to expand our infrastructure. So the strategy basically is for top key customers, we use our own cash and dry powder and CapEx to build the infrastructure to provide cloud service to them. However, for non-top customers, we're increasingly using leveraging the partners who will supply us with the servers and computing resources. And we jointly together provide cloud service to these customers. And because these are partners that provide resources, we actually have to share some of the profit with them. So this is like a partnership in a profit-sharing model. And for that reason, that new or emerging supply chain model has also, to some extent, negatively impacted the gross margin level of the company. In response to your question regarding the impact of open source of Deepstick R1 on the demand for model training, my answer to you is that this is coming from our SVP, Ms. Linlin Yang. So the old batch of large language model companies, it's open in ten and large language model companies, we do have seen their demand shrinking to some extent due to the success of Deepstick. However, the contracts that we entered with them are long-term contracts, which we have entered in the past. So, as we responded in the first question, the impact is very limited. However, there's also a group of other companies than those large language model companies. Some of them are coming from the Internet space, some from other emerging industries. They are inspired by the success of Deepstick. And also think that by using relatively manageable resources, they will also potentially be able to train and own a state-of-the-art model. So therefore, we're seeing increasing demand coming from these customers as well. So all in all, we don't see a negative impact from the success of the Deepstick model.

Thank you. There are no further questions at this time. This concludes today's conference call. Thank you for participating.