Kingsoft Cloud Holdings Limited (KC) Earnings Call Transcript & Summary

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

Thank you, operator. Hello, everyone, and thank you for joining us today. Kingsoft Cloud'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 the PRNewswire services. On the call today from Kingsoft Cloud, we have our Vice Chairman and CEO, Mr. Zou Tao; and the CFO, Mr. 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 purpose only. In case of any discrepancy, management's statement 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 U.S. Private Securities Litigation Reform Act of 1995. These forward-looking statements are based upon management's current expectations and current market and operating conditions and relate to events that involve known or unknown risks, uncertainties and other factors, all of which are difficult to predict and many of which are beyond the company's control, which may cause the company's actual results, performance or achievements to differ materially from those in the forward-looking statements. Further information regarding these and other risks, uncertainties or factors are included in the company's filings with the U.S. SEC. The company does not undertake any obligation to update any forward-looking statements as a result of new information, future events or otherwise, except as required under applicable law. Finally, please note that, unless otherwise stated, all financial figures mentioned during this conference call are denominated in RMB. It's now my pleasure to introduce our Vice Chairman and CEO, Mr. Zou. Please go ahead. Thank you.

[Interpreted] Hello, everyone. Thank you, and welcome all for joining Kingsoft Cloud's First Quarter 2025 Earnings Call. I am Zou Tao, CEO of Kingsoft Cloud. This quarter, we continued to steadily advance our business with a target on 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 quarter-over-quarter, 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 declined 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 55.8 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 tracking with our long-term strategy and continued 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 for the first quarter of 2025. In public cloud space, revenue reached RMB 1.35 billion this quarter, representing a year-over-year increase of 14%. AI business as a key growth driver recorded 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, consumer demand 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, created benchmark case of delivering full spectrum cloud services for large-scale clusters within the quarter. In addition, through flexible capital cooperation models, we ensured sufficient underlying computing power supply to support the rapid growth of our AI business. In enterprise cloud space, revenue reached RMB 616 million this quarter, representing a year-over-year increase of 5%. Affected by seasonal slowdown 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 cloud and state-owned asset cloud, actively embracing the AI-driven trend. Kingsoft Cloud has built a rich set of model resources through 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 health care sector, we initiated the construction of a platform for mutual recognition and sharing of test and examination results in Wuhan. Kingsoft Cloud's medical imaging cloud capabilities, which have been deployed in regions such as Jiangsu and Chongqing provinces were, once again, validated. 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 continued to enhance the product capabilities of our intelligent cloud computing services. Our Xingliu 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 extend 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 and 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, Henry, to go over our financials for the first quarter of 2025. Thank you.

[Foreign Language] 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 continues to drive our growth and lay 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 of 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 a better rack 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 Camelot 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 for enterprise cloud services and the higher upfront investments into servers and racks for AI business. On expenses side, excluding share-based compensation, our total adjusted operating expenses were RMB 427.3 million, a decrease of 9% year-over-year and 4.3% quarter-over-quarter, of which our adjusted R&D expenses was RMB 200.8 million, increased by 4% from 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 increase of gross profit and a decrease of credit loss expenses. However, the adjusted operating profit turned loss from last quarter, which was mainly due to the decrease of gross profit in this quarter. Our non-GAAP EBITDA profit was RMB 318.5 million, increased by -- 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. It was 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 a strong liquidity position to support operations and in 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 fueled our business growth, but also reinforced our confidence in this trajectory. With demand for AI cloud service continuing to grow, we are well positioned to capture and capitalize on AI capital opportunities. Thank you.

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

[Operator Instructions] We will now take the first question from the line of Brian Gong from Citi.

[Foreign Language] I'll translate myself. [Technical Difficultly] For both public cloud and 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. Can management elaborate what's the latest demand from Xiaomi are?

[Interpreted] So, thank you very much for your question. So, in relation to the first question about the declined 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 impacts for both the -- our own enterprise cloud services as well as the business from Camelot, because obviously, Q1 there is the factor of the Chinese New Year and 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 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 to generate revenue. So, in fact, in the first quarter, we have delivered a 512-node cluster to our key customers, Xiaomi. However, that delivery time point was only at the end of March, and therefore, the revenue and profit reflection as 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 is actually trained from our cluster. And the -- in fact, the tremendous growth of the KC'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're serving Xiaomi, the pace of Xiaomi's demand has a lot to do with when and the amount of the revenue and profit will show on our financial statements on a quarterly basis.

We will now take the next question from the line of Xiaodan Zhang from CICC.

[Foreign Language] First of all, I noticed that the Kingsoft Cloud and Kingsoft Office has recently jointly launched an AI all-in-one model machine for government affairs sector. So, 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? And secondly, could you please update on the non-GAAP OP margin outlook for the subsequent quarters?

[Interpreted] So, let me quickly translate. So as you 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 and come together with Kingsoft Office to jointly develop and offer a plan or a solution to such 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 to become more efficient in office scenarios. And this is targeted for Chinese government agencies in various layers -- 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 customers. So the pricing can actually vary by quite a lot.

Thank you, Zou. Thank you for the question on the margin side. I think probably a few things I want to point out. So, given the seasonality in Q1, as probably many of you understand that our primarily OpEx is human capital expenses. So, the salaries, compensation, bonuses, so on and so forth. So in Q1, basically, we not only need to incur the normal salary payment, but also there's a bonus and also certain kind of employee benefits also incurred in Q1 during the holiday season, 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. So, the variation of the top line growth largely affected the bottom line. So, the cost structure, especially on the salary and the compensation are relatively fixed. That's why it's kind of affecting on the OP margin in Q1. It's kind of very straight-line reason. So, going forward, I think given the better margin profile, for example, the AI projects and our relationship with our ecosystem partners, especially for Xiaomi, our CEO, Mr. Zou just mentioned, the big projects were likely to deploy on the way and 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 end, we also want to point out, given that EBITDA margin will be likely better compared with the OP margin given the nature of the AI business, so as the AI business penetration become higher in the public cloud services, so hopefully, the EBITDA margin can be recovered 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 costs, 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 a formal guidance, I understand Brian also mentioned this, for the full year top line revenue in the call today, but we are 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 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.

We will now take the next question from the line of Thomas Chong from Jefferies.

[Foreign Language] 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. Does the chip ban issue affect the sequential momentum in CapEx? And my third question is about -- more about the industry landscape. Given that customers are now using more like a distilled model, smaller models rather than large models, would that affect the cloud revenue?

Thank you, Thomas. I will take the first 2 -- first question and defer to CEO, Mr. Zou for the second and third question. [Foreign Language] 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 investments into AI, especially the infrastructure construction. So, our own cash to be used for the CapEx is one part, but also, we are going to, for example, doing the financial leasing and operation leasing with our partners, for example, Xiaomi as well. But also, we are going to get the financing, for example, the bank loans and certain leasing agreement with the 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 3 ways that we're financing the total AI infrastructure demand. So, out of that, I think the reason you probably point out the total CapEx for this quarter is kind of RMB 600 million for this quarter. But I think our total investment into AI because we also start to leasing certain servers from third parties to reduce our burden to pay out of pocket from own cash. So there are certain leasing and rental agreement we actually start to negotiate and set up with third party start 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 we're starting to arrange with third parties. So it is going to be the total investment of the AI infrastructure from our definition. So I'm going to likely have an update for next quarter because we just start to arrange those agreements with third parties, ensure to reduce and saving and to be more efficient in terms of our own cash management. So I think right now, we give the number on the 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 mentioned in earnings calls, our R&D expenses for this quarter is around kind of RMB 200 million and the sales expenses is around RMB 108 million. And the management SG&A is around RMB 119 million. So if you're putting the 3 numbers together, it's roughly about RMB 400 million on the OpEx side, including R&D, sales, marketing and SG&A. I think this probably can give you kind of a color regarding the total OpEx plus CapEx on a quarterly basis. Thank you. [Foreign Language]

[Interpreted] Okay. So very quickly to translate Mr. Zou's response to the chip band question. So, honestly, and very frankly, there surely will be an impact, right? However, this is actually not the same time for similar kind of restrictions to be imposed on chips. So -- and we have experienced a similar things before. And so before this round of restriction actually hit us, we have had some inventory and storage. So therefore, the short -term impact is not that material. However, from a long term -- from mid-to-long-term perspective, there will be meaningful impact for both the Kingsoft Cloud 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 computing resources. And that kind of cooperation -- we have managed to continue that cooperation 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 for revenue and profitability for Kingsoft Cloud. And the reason has been follows. The first one is for the traditional large language model customers, their models have been 100 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. And 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 incremental amount for our revenue development. And thirdly, in terms of the -- in the future for the Xiaomi and Kingsoft Ecosystem, we also expect to have actually a positive impact coming from the more prevailing usage of relatively small models because more of the model inference would -- originally, they're coming from outside of the Kingsoft Cloud -- our computing power infrastructure from other companies. Actually, when the Xiaomi and Kingsoft Ecosystem started to adopt more medium-sized or smaller sized models, they were actually starting to use more of Kingsoft Cloud computing resources. So that's actually another part of potential incremental revenue and profit for us.

We will now take the next question from the line of Wenting Yu from CLSA.

[Foreign Language] So, the first question is, can management share the recent gross margin rends for AI cloud leasing services? Previously, we observed the aggressive price competition in the industry, mainly focused on model API pricing. Are we seeing the pricing pressure extend to the AI server listing business as well? And the second question is, following the open sourcing of R1 by DeepSeek, how do we see the latest dynamics of model training demand? While there is incremental demand for post-training models, the opensource release of R1 may also lead to some model vendors abandoned for the iteration. So how should we evaluate these 2 factors and their overall impact in the industry?

[Interpreted] So, in relation to the AI cloud service margin or pricing pressure question, let me respond to you from 2 dimensions, like which is internal and external. So, externally, as you rightly pointed out, we're actually seeing sort of market concentration for AI players as our customers. And therefore, they do have some impacts to 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 and for those projects that we entered into in the past, there's no meaningful or 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 and to provide cloud services to them. However, for non -top customers, we're increasingly using -- leveraging the partners who will supply us the servers and computing resources, and we jointly together to provide cloud service to these customers. And because these are partners that provide resources, we actually also have to share some of the profits with them. So this is like a partnership in 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. So, in response to your question regarding the impact of open-source of DeepSeek R1 to the demand of model training, so my answer to you is this and this is coming from our SVP, Mr. Liu Tao. So, the old batch of large language model companies, so-called in [ 10 large language ] model companies, we do have seen their demand shrinking to some extent due to the success of DeepSeek. However, most of the contracts that we entered with them are long-term contracts and 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 other than those large language model companies, some of them coming from the Internet space, some from other emerging industries, they are inspired by the success of DeepSeek and also think that by using relatively manageable resources, they will also potentially be able to train and [ owe us ] state-of-the-art model. So therefore, we are 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 DeepSeek model.

There are no further questions at this time. 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.]