Good day, and thank you for standing by. Welcome to Kingsoft Cloud's third quarter 2025 earnings conference call. At this time, all participants are in a listen-only mode. After the speaker's presentation, there will be a question-and-answer session. To ask a question during the session, you will need to press star one and one on your telephone. You will then hear an automated 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. Please go ahead. Thank you, Operator. Hello everyone, and thank you for joining us today. Kingsoft Cloud's third quarter 2025 earnings release was distributed earlier today and is available on our IR website at ir.ksyun.com, as well as on the TI NewsWire services. On the call today from Kingsoft Cloud, we have our Vice Chairman and the CEO, Mr. Zou, and the CFO, Ms. Li. Mr. Zou will review 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 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 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 are related to events that involve known or unknown risks, uncertainties, and other factors, 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 majorly 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 statement as a result of new information, future events, or otherwise, except as required under applicable law. Finally, please note that unless otherwise stated, all financial figures mentioned during this conference call are denominated in RMB. It's now my pleasure to introduce our Vice Chairman and CEO, Mr. Zou. Please go ahead, Zou. [Foreign language] Hello everyone, thank you and welcome to Kingsoft Cloud's third quarter 2025 earnings call. I am Zou Tao, CEO of Kingsoft Cloud. In the era that artificial intelligence is implemented across various industry verticals and reshaping the technological landscape, Kingsoft Cloud has firmly established its strategic positioning and defined its development orientation. On the premise of steadily meeting the demands of model training, we have made adequate technical and resource reserves for the explosive growth of inference. In the face of the dual trends of rapid model iteration and increasing adoption of artificial intelligence, we have provided our clients with stable and efficient integrated training and inference Intelligent Cloud Computing services and have laid out model API business to turn inference scenarios into new growth engines. The substantial high growth in revenue and the stable profit margin level validates the steady execution of our strategic measures, achieving high quality and sustainable development. First, our revenue in the third quarter reached RMB 2.48 billion, with year-over-year growth rate accelerating from 24% in the previous quarter to 31% this quarter. Both public cloud and enterprise cloud achieved year-over-year and sequential growth, among which public cloud revenue increased significantly by 49% year-over-year, reaching RMB 1.75 billion. Second, Intelligent Computing Cloud business remains on a fast development track. This quarter, gross billings of Intelligent Computing reached RMB 782 million, with a year-over-year growth around 122%. It accounted for 45% of the public cloud revenue, realizing a significant increase from 31% in the same period last year. Generative artificial intelligence and cloud are symbiotically integrated in many aspects, including technology, products, and customer cross-sales. The demand for artificial intelligence not only drives the rapid development of Intelligent Computing Cloud, but also leads to the growth and technological innovation of basic public cloud and accelerates the iterative process of cloud computing technologies. From training clusters to native technologies, our computing power services, model API services, storage services, and data services have all been upgraded. Third, the Xiaomi and Kingsoft ecosystem continued to offer a solid foundation. This quarter, revenue from the Xiaomi and Kingsoft ecosystem reached RMB 691 million, increasing by 84% year-over-year, and its proportion in the total revenue further rose to 28%. From January to September 2025, the total revenue from the Xiaomi and Kingsoft ecosystem reached RMB 1.82 billion. We anticipate adequately fulfilling the business cooperation under the continuing connected transactions annual quota this year and are optimistic in the further increase of the quota next year. Finally, our adjusted gross profit for this quarter reached RMB 393 million, representing a year-over-year increase of 28%. The adjusted operating profit turned from loss to profit, reaching RMB 15.36 million, and the adjusted operating profit margin was 0.6%. The adjusted net profit recorded a historical positive profit of RMB 28.73 million for the first time. The company is aiming at both revenue growth and profitability improvements as the economies of scale are becoming increasingly prominent. While accelerating the construction of intelligent computing infrastructure and technological capabilities, we are also strengthening the control of costs and expenses. [Foreign language] Now I would like to walk you through the key business highlights for the third quarter of 2025. In terms of public cloud services, revenue reached RMB 1.75 billion in this quarter, making a year-over-year increase of 49%. The Intelligent Computing Cloud business has maintained strong growth. We have successfully supported the large-scale training and inference demands of various top internet customers, providing high-quality, high-performance, high-stable, and highly efficient cloud computing services. Especially for many artificial intelligence and internet enterprises, facing the simultaneous demands for model training and inference, we have provided customers with stable and integrated intelligent computing services for different scenarios. Meanwhile, we actively expanded customer coverage and the cross-selling of Intelligent Computing Cloud and Basic Cloud. In terms of ecosystem customers, we continued to provide high-quality services to Xiaomi and Kingsoft and continue to prepare underlying resources for ecosystem customers to enhance the rapid expansion capability for intelligent computing demands. In terms of enterprise cloud services, revenue in the quarter was RMB 730 million. We firmly believe that in today's rapidly evolving generative artificial intelligence landscape, intelligence will evolve from model capabilities to industry solutions, empowering and reshaping diverse sectors of the economy. As the indispensable carrier for intelligent computing, cloud services enjoy tremendous potential for such digitalization and intelligentization. In this trillion-dollar sustainably expanding market, we have deeply explored our inherent DNA of ToB enterprise services, targeted advantageous selected verticals and geographical regions, and built core competitiveness for the future. As a result, it has received widespread recognition from our customers and the broader market. For example, in the public services sector, we aim to become the preferred cloud partner for intelligent computing in the public services agencies and enterprises for their inference demands. Taking Qingyang City in Gansu Province as an example, as one of the eight major nodes of the national project East Data Web Computing and a central area for intelligent computing business, we will be responsible for building the public services cloud platform in Qingyang to fully empower the local public services affairs with intelligence and digitalization. In the field of healthcare, we have achieved a milestone breakthrough in a project integrating artificial intelligence with traditional Chinese medicine clinical scenarios, whereby not only have we achieved a deep integration of traditional Chinese medicine theory and artificial intelligence, seizing the commanding position in chronic disease management technology, but we have also verified the practical value of Artificial Intelligence in improving patients' quality of life and disease control rate at the clinical level. In the enterprise services sector, following the successful implementation of a landmark project for intelligent generation of bank credit reports, we continue to advance the intelligentization transformation across the entire credit approval process. This evolution extends from the single function of credit report initiation to a comprehensive intelligence system, including customer onboarding, credit report generation, loan disbursement, monitoring and early warning, and post-loan reporting. We firmly believe that these proven accumulated successful experiences, market reputation, and replicable core solutions will enable us to seize a pioneering position in the emerging industry wave, build a solid core competitiveness, and achieve high-quality and sustainable shareholder returns. [Foreign language]WPS AI [Foreign language]. In terms of product and technology, in public cloud space, we continue to enhance the technology of Intelligent Computing Cloud this quarter, strengthening the capabilities of the Starflow platform and made significant progress in the following three aspects. First, we have launched our model API service, delivering highly available and easily integrable capabilities for model invocation and management, laying a solid foundation for the subsequent provision of diverse model service paradigms. Second, we upgraded our online model services, integrating multiple open-source foundation models and equipped with automatic scaling capabilities, offering a highly available inference level. Third, we launched our data annotation and dataset marketplace, aiming to provide customers with end-to-end support for data flow and help them efficiently advance the model training process. In Enterprise Cloud Space, in order to meet the demands for private deployment scenarios, we have built a computing power scheduling platform, a lightweight mass platform, and a generative artificial intelligence knowledge base. We have closely collaborated with WPS AI to build a trusted intelligent product architecture for public services use cases. Meanwhile, through the organizational development of the dual R&D centers in Beijing and Wuhan, we attract talents from various regions, build a talent pipeline, and maintain sustained investment intensity in the intelligent computing field. As of the end of Q3, the number of employees in Wuhan is 2.8 times the headcount back in 2022 when we first launched our Wuhan strategy. Overall, we will firmly seize the historic opportunities presented by the Xiaomi and Kingsoft ecosystem, continue to invest in infrastructure, focus on refining core products and solutions, and to create long-term value for our customers, shareholders, employees, and other stakeholders. I will now pass the call over to Ms. Li Yi, our CFO, to go over our financials for the third quarter of 2025. Thank you. Thank you, Zou, and Shan. Good evening and good morning, everyone. Thank you all for joining the call today. Before we walk through the details of financial results for the third quarter, I would like to highlight the following aspects. First, revenue has consecutively achieved year-over-year growth for six quarters, reaching RMB 2,478 million this quarter. This represents an accelerated year-over-year growth rate of 31%, up from 24% in the previous quarter. Revenue from public cloud service sold at RMB 1,752.3 million, a significant increase of 49% from RMB 1,165.5 million in the same quarter last year. Meanwhile, robust demand for our intelligent cloud, which also called as AI Cloud Business, drove around 120% year-over-year billing growth, which totaled RMB 782.4 million. Second, profitability has seen substantial improvement. Our adjusted gross margin rose to 16%, up from 50% in the previous quarter, and adjusted EBITDA margin improved to 33%, compared with 17% last quarter. Notably, we turned quarterly adjusted operating loss and adjusted net loss into profit simultaneously for the first time. This gain validates our strong execution in pursuing high-quality, sustainable development, as well as our ability to monetize opportunities in the Intelligent Cloud Space. Third, we would like to express our gratitude to shareholders for their support during our risk equity financing in September. We successfully raised HKD 2.8 billion, and 8% of the fund will be allocated to further investment in AI infrastructure and 20% to general operational needs. This funding will fully underpin the growth of our Intelligent Cloud business and enable us to create long-term value for all stakeholders. Now, I will walk you through our financial results for the third quarter of 2025 and use the RMB as currency. Total revenues were RMB 2,478 million. Of these, revenues from public cloud services were RMB 1,752.3 million, up 49% from RMB 1,175.5 million in the same quarter last year. Revenues from enterprise cloud services reached RMB 725.7 million, compared with RMB 710 million in the same quarter last year. Total cost of revenues were RMB 2,097.1 million, up 33% year-over-year, which was mainly due to our investment into infrastructure to support Intelligent Cloud business growth. IBC cost increased by 15% year-over-year, from RMB 673.8 million- RMB 775.7 million this quarter. The increase was mainly due to the purchase of racks, which serve the expanding Intelligent Cloud business, as well as the basic computing and storage cloud demand brought by AI development. Depreciation and amortization costs increased from RMB 297.5 million in the same quarter of 2024 to RMB 649.7 million this quarter. The increase was mainly due to the depreciation of newly acquired and leased servers and late work equipment, which were mainly allocated to Intelligent Cloud business. Solution development and services cost increased by 90% year-over-year, from RMB 499 million in the same quarter of 2024 to RMB 595.9 million this quarter. The increase was mainly due to the solution personnel expansion. Fulfillment costs and other costs were RMB 5.2 million and RMB 70.6 million this quarter. Our adjusted gross margin for the quarter was RMB 392.6 million, increased by 28% year-over-year and 12% quarter-over-quarter. It was mainly due to the expansion of our revenue scale, the inadequate distribution for intelligent cloud, and the cost control of IBC racks and servers. Adjusted gross margin increased from 50% last quarter to 16% in this quarter. On the expense side, excluding share price compensation costs, our total adjusted operating expenses were RMB 420.9 million, decreased by 70% overall year and 25% quarter-over-quarter, of which our adjusted R&D expenses were RMB 188.4 million, decreased by 90% from same quarter last year. The decrease was mainly due to the decrease of personnel costs resulting by our strategic adjustment for research team, as well as the expense serving to from Beijing Wuhan dual research same strategy. Adjusted selling and marketing expenses were RMB 127.6 million, increased by 50% year-over-year. Adjusted general and administrative expenses were RMB 104.9 million, decreased by 29% year-over-year due to the reverse of credit loss. The impairment of long-range assets was near this quarter, compared with RMB 190.7 million in the same quarter last year. Our adjusted operating profit was RMB 15.4 million, totaling profit from adjusted operating loss of RMB 140.2 million in the same period last year. The improvement was mainly due to the expansion of revenue scale and gross profit, the expense control, as well as the reverse of credit loss. Adjusted operating profit margin increased from minus 7% in the same period last year to 0.6% this quarter, representing an increase of eight percentage points. Our long gap EBITDA profit was RMB 826.6 million, increased by 3.5 times of RMB 185.4 million in the same quarter last year. Our long gap EBITDA margin achieved 33%, compared with 10% in the same quarter last year. It was mainly due to our strong commitment to intelligent cloud development, strategic adjustment of business structure, strict control of costs and expenses, as well as the long recovery impact of subsidy in other income. As of September 30, 2025, our cash and cash equivalent totaled RMB 3,954.5 million, decreased from RMB 5,464.1 million as of June 30, 2025. The decrease was mainly due to our infrastructure investment for intelligent cloud. This quarter, our capital expenditures, including those financed by third parties and the right-of-use assets obtained in 2024 finance lease liabilities, were RMB 2,787.8 million. Looking forward, AI technology drives the revolution of Cloud computing. We do more than just fulfill the computing demands of model training, inference. We also empower enterprises to invoke an API and apply AI capabilities to their business. Stepping into the phase of rapid development in AI applications and explosive growth in demand, we will further invest into infrastructure, strengthen technology, enhance service stability, and provide customers with high-value-added Cloud services. That's all for the introduction of our operational and financial results. Thank you all. Thank you, Operator Wu. I now want you to start a Q&A session. Please ask your question in both Mandarin, Chinese, and English if possible. Operator, please go ahead. Thank you. Thank you. As a reminder, to ask a question, you will need to press star one and one on your telephone and wait for your name to be announced. To withdraw your question, please press star one and one again. Please stand by while we compile the Q&A queue. Our first question comes from the line of Xiaodan Zhang from CICC. Please go ahead. Your line is open. Hey, Zou Tao, Li Yi, Nicole, and Clarke, [Foreign language]. Thank you, management, for taking my questions. First of all, what are the key drivers of AI revenue growth in Q3? Has there been any structural change in the demand of your ecosystem and external clients for the past quarter? Secondly, how does management see the margin trend in the coming quarters? What is the expected mix of different computing resources acquisition models? Thank you. Please stand by while the speakers reconnect. Please stand by while the speakers reconnect. Please stand by. Once again, please stand by while the speakers reconnect. Thank you. Speakers, you are now reconnected. Please go ahead. Yes. Sorry, Xiaodan, we didn't get your question. Could you repeat that again? Thank you. Yes, no problem. My first question is regarding the AI revenue. Could management break down the key drivers for AI revenue in Q3? Has there been any structural change in the demand of your ecosystem and external clients for the past quarter? Secondly, how does management see the margin trend in the coming quarters? What's the expected mix of different computing resources acquisition models going onwards? Thank you. [Foreign language] Basically, the core of the reason behind the AI revenue growth in Q3 is that we had some clusters that, you know, partially delivered in the previous quarters, for example, like the second quarter of 2025. These clusters and these services have only been partially accounted for revenues from a full quarter basis. Now in Q3, they are starting to be recognized as full quarter revenues. Also, there is the factor of partially delayed revenue as well. Some of the revenue which we had in Q2 but was not accounted for, and then this revenue got delayed into the third quarter. Yeah. [Foreign language] [Foreign lanaguage] [Foreign language] So in regarding the second part of your first question, which is about the structure of internal and external customers, I think I used to say that from a large trend, general trend perspective, we're currently in the phase of transitioning from large and top customers' training demand to general and wider spread customers' inference demand. Most at the current stage, we still see, you know, the majority of our demand coming from the larger customers in their training demand. However, especially in the latest quarter, we're increasingly seeing the trend of customers adopting artificial intelligence models into their diverse industries. In face of this general trend, we have also, as we mentioned in the prepared remarks, launched our Starflow platform to meet the demands of such general trend. This also goes back to the margin question that you also asked about. We generally think that in the future, the inference demand will tend to exhibit higher margin profile than the current stage of training. Therefore, we think that when that wave of demand comes, we expect to have higher margins. Thank you, Xiaodan. At the EBITDA level, as the proportion of the AI business continues to rise and its cost structure is mainly dominated by depreciation, we expect this year's EBITDA margin will still remain above 20%. I have to mention that the significant quote unquote improvement this quarter was mainly driven by a one-time other income, which will return to the normal level next quarter. Thank you, Xiaodan. Operator, next question, please. Thank you. Now, next question comes from the line of Wenting Yu from CLSA. Please go ahead. Your line is open. Hey, Zou Tao, Li Yi, Clarke, and Nico, [Foreign language]. The first question is, could management share the outlook and guidance on the revenue outlook for next year and beyond the internet complex post-model training and embodied intelligence scenarios that are already underway this year? Which other industry and application scenarios are expected to have strong computing power demand that could drive the revenue growth next year? The second question is, with multiple cloud providers in both China and U.S. increasing the proportion of server leasing in their computing resource mix, how does management view the current market dynamics for procurement versus leasing? From a cost effectiveness and profit margin perspective, how will the company allocate the resources between these two approaches? Thank you. Wenting, thank you for your question. The company's budget process is currently underway and expected to be completed around the beginning of the next year. We will share specific details with you once it is finalized. However, regarding the demand for our AI business, we are fully confident in the subsequent demand growth. For your second question regarding the procurement method, we primarily align our capital channels with actual customer needs, including cluster scale, delivery time, and the supply inventory levels. There is no rigid top-down allocation target. From the cost effectiveness perspective, both approaches have their own pros and cons. The leasing model is fine to our supply chain channels and provides a certain degree of flexibility in resource allocation, with the flexibility also offered through short-term and long-term contracts. Self-procurement, on the other hand, gives us great autonomy in controlling delivery timelines and managing clusters. It also reduces the profit sharing with suppliers, thereby elevating our appreciation on profit margin. Thank you, Wenting. [Foreign language] Yeah, you know, you know, as you mentioned that, you know, the robotic companies in China is a growth in very fast pace. You know, as you this year, we have covered most of the robot companies in China, and we can see the revenue is increasing very rapidly. In the next year, we believe the increase of the robotic companies will also be fast. Meanwhile, you know, as more and more internet companies in China are using token token services, which is the API services, we are seeing the increase in the business is very quickly. We believe in the next year, this will be a very important factor to driving the revenue to increase. Thank you. [Foreign language] This is the CEO, CEO Zou Tao, and he added that you understand that your question, your second question is really about the choice between the leasing model and the CapEx model. We've talked about that before. Generally, there's a general rule of thumb. When we're looking at the larger customers, especially the customers that have solid profile, have solid fundamentals, and are trustworthy, premium customers, for example, like Xiaomi, we would tend to choose the CapEx model. While in other growth stage companies, medium and small size, the small and medium size of the companies, we generally tend to adopt the leasing model, which is also a meaningful way to reduce our own risk. As Li Yi rightly mentioned, there's no this kind of like top-down target for the split between these two different methods. We also talked about in the last quarter as well that the impact of these two different methods have different impacts to gross margins. However, as we have seen the financial results for the past three quarters, which we have adopted various combinations of these two different models, and you know especially when you compare the growth margin for the third quarter versus the second quarter, it actually also improved sequentially. I would say that at the current stage we do not expect material changes to the current status, but generally speaking, in the future we do expect the margin to improve. Thank you. Thanks, Wenting. Next question, please, Operator. Thank you. Our next question comes from the line of Timothy Zhao from Goldman Sachs. Please go ahead. Your line is open. [Foreign language]. Thank you Madam for taking my question. My question is regarding the differences between AI training versus inferences. Could Madren share what is the pricing methodology between these two kinds of demand and what has been the pricing trend over the past few months or year to date? In terms of the overall utilization rate of the chips of GPUs, pricing and profitability, can you share more color on the gap between training and inferences? Thank you. Okay, let me answer this question. You know, when we're talking about the price strategy for inference and the training, you know there's not too much difference between the two things. The price is based on the qualities, how many sources use, which is the most important factors. Also, comparing the margin rate, you know there are two kinds of inference services. One is, you know, customers buy resource and use our platform to inference. That margin ratio is very similar to the training margin ratios. Another one is, you know, customers do directly buy our API token services. We think that will have a better margin ratio. You know, this business just in the beginning. We need time to see what is the big difference between the two things. Thank you. Thanks, Timothy. Operator, please. Thank you. Due to time constraints, this concludes our question and answer session. I'll hand the call back to Nicole for closing remarks. Thank you. Thank you all once again for joining us today. If you have any questions, feel free to contact us. Look forward to speaking with you again next quarter. Have a nice day. Bye-bye. Bye-bye.