Good morning, ladies and gentlemen, and thank you for standing by for Kingsoft Cloud's second quarter 2026 earnings conference call. All participants are currently in listen-only mode. Following management's prepared remarks, we will open the call for questions. Please note that today's call is being recorded. I will now turn the call over to Mr. Jacky Zhou, 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. Tian Kaiyan, Senior Vice President, Ms. Yu Jun, Vice President, Mr. Zhou Ruilong, Associate Vice President, and Mr. Kwok Chen, 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 the 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 filing 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. [Non-English content] 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 FDE 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 FDE 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 grows 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 five 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. [Non-English content] 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 car home ecosystem. 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 the leading AI for Science customers to support the growth of its new business. [Non-English content] 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 Jianghai 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 government, 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 Yun Shang Gansu to jointly build and operate the Gansu Provincial Public Services Cloud under an integrated investment, construction, and operations model. [Non-English content] 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 lifecycle visual management for multiple mainstream domestic AI chips. [Non-English content] 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 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 financial results for the second quarter, I would like to highlight the following aspects. First, our quarter revenue reached over RMB 3 billion for the first time in our company history, up year-over-year for the last 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 5.4%, up 2.4 percentage points quarter-over-quarter and 0.5 percentage points year-over-year. Our adjusted EBIT margin reached 36%, up from 17% in the same quarter last year and 82% last quarter. Notably, we returned to breakeven at operating income level this quarter and recorded an adjusted operating profit margin of 4%. These outcomes validate 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 in 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 1,624 million in the same quarter last year. Revenues from enterprise cloud services reached RMB 740 million, compared with RMB 724 million in the same quarter last year, down slightly by 1% year-over-year. Total quarter revenues was RMB 3,606 million, representing a 30% year-over-year increase, mainly due to a continued investment in AI cloud infrastructure. IDC costs increased by 23% year-over-year from RMB 803 million to RMB 990 million this quarter. The increase was mainly due to the increase of rack services. Depreciation and amortization costs increased by 75% year-over-year from RMB 752 million in the same quarter of 2025 to RMB 964 million this quarter, largely due to the depreciation of newly acquired and leased 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. The modest increase was 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 14.1% in the same quarter last year and from 13% last quarter. The increase was driven by higher gross margin in public cloud business, thanks to strong AI demand. On the expense side, excluding share-based compensation cost expenses, our total adjusted operating expense were 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. Of which 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 104 million, down 61% year-over-year, largely due to lower credit loss expenses. Our adjusted operating profit was RMB 124 million, turning profit from 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 -7.1% in the same period last year and -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 previous quarters. 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 EBIT margin achieved 36% compared with 70% in the same quarter last year and 82% last quarter. It was mainly due to our improving gross profit as well as higher depreciation costs in our data centers 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 all-in AI strategy and continue to deliver high-quality growth to our shareholders. Thank you all. This concludes our prepared remarks. We will now begin the Q&A session. If possible, please ask your questions in both Mandarin and English. Operator, please proceed. Thank you. We will now begin the question and answer session. If you wish to ask a question, you will need to 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 take our first question. Your first question comes from Liping Zhao from CICC. Please go ahead. Your line is open. [Non-English content] Good evening, MR. Zou and Ms. Li. Thanks for taking my questions. I got 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 is the current usage growth trend and which use cases are driving it most? Second, given the payback period for the MaaS business might be shorter, will the company allocate more resources to it? Thank you. [Non-English content] Okay, just to quickly translate. This answer comes from our SVP, Mr. Liu Tao. In relation to your first question, the development in open source large language models has mainly three impacts. Number one is that we are seeing very big demand coming from web coding and traditionally, foreign models have been taking the lead in this area. However, once we have seen the launch of GLM and K3, these kind of high-performance models, we are seeing increasingly users from mainland China adopting and using this made-in-China large language model. Secondly, the increasing use of agentic scenarios also brought change to our business. With that, we have launched, as mentioned in the prepared remarks, the AgentKit product to satisfy such needs. Thirdly, it is worth mentioning that in terms of day-to-day routine tasks and workloads, the choice usually is the price for value kind of models, which are essentially the Chinese models. That is why this development open source large language model is actually beneficial for our business. Your second question regarding the balance between MaaS business and the computing power. We basically have different business models for the two business. For computing power business, essentially, once we sell the computing power, the utilization is by nature 100%, and we usually come with long-term contracts to secure the utilization throughout a prolonged period of time, and therefore it is relatively safe, so to speak. But for the MaaS business, it is subject to quantity factors, including the fluctuation of the token price, the launching of new models, which the customers might prefer to use, and also the operating efficiency that we are able to achieve in doing a MaaS business. Therefore, we generally balance these two business models and hope to have each one of them complement the other one. So we generally dynamically evaluate these two business and try to decide how much resources to allocate. Thank you. Thank you, Tao. That is very helpful. Thank you. We will take our next question. Next question comes from Wenting Yu from CLSA. Please go ahead. Your line is open. [Non-English content] The first question is that since June, how has the chip procurement progressed in recent months, and what is your latest full year CapEx guidance? The second question is about the enterprise cloud. This second line of revenue has decelerated in the past two quarters. How should we think about the full- year enterprise cloud growth and what is the AI transformation and medium-term positioning for this segment? Thank you. [Non-English content] Allow me to quickly translate. The answer comes from our SVP team, Mr. Kaiyan Tian. Three points. Number one, actually, since 2023, it has been three years and the market has always been hearing voices about the limited supply. I would say this is actually a new norm. The supply difficulty is actually a long-term kind of situation. Secondly, we should also be aware of the fact that despite of those constraints, financial constraints, the Chinese cloud computing or AI industry development has not been restricted or largely restricted by that. The way that we actually tackle with such situations is that we try to increase the number of business partners that we work with. We try to increase the number of suppliers we work with, and we also work with increasing the compatibility of made in China chips. You are all very much aware of the. Recently, many of the made in China chips are becoming public, and they are particularly good in use cases such as model inference. Number three, I would like to say that when you look at the CapEx number from a month-to-month basis, it is usually quite volatile. I have to say that the purchasing number, because of it is usually a large chunk of money in a relatively small number of purchases. So the purchasing number, if you look at it by monthly basis, is actually not a linear number. I would say that for our whole year CapEx estimate, it should still be in line with what we have been expecting and our CFO, Li Yi, should be able to give you more details in that regard. Hi, Tingting. Our CapEx venture includes capitalized assets through lease arrangement, reaching RMB 6.2 billion in the first half of 2026, accounting for over 75% of our full-year CapEx master year. July's data cannot fully represent the third quarter of all trends, it clearly shows tangible growth acceleration. Accordingly, we maintain our full-year CapEx base case unchanged at RMB 15 billion. Thank you, Tingting. [Non-English content] Thank you. We will take our next question. Oh, sorry. We need to continue for another question. Apologies. Okay. [Non-English content] Okay. This answer comes from our VP, Ms. Li Yi. Generally, although we are seeing relatively slow growth in the enterprise cloud segment, I would say it is not the right way to look at it from the linear extrapolation perspective. I will give you three reasons. I think number one, just to explain why we are thinking of looking at relative weakness in this regard, is that the upstream supply pricing hike, which changed quite significantly in recent quarters, has affected our prospective customers, essentially the SOE companies and also the government agencies. They have to frequently adjust their budgeting quota, which delays their decision-making process. That is number one. Number two, you are all quite aware that the seasonality in enterprise cloud business is quite strong. Usually, the delivery and the revenue recognition are concentrated in the second half of every year. We have actually quite a strong pipeline to deliver in second half of the year. Thirdly, this is actually a result of a proactive adjustment of our business structure, namely proactively from the project-based business model to operating based business model, where operating business model from a financial reporting perspective is automatically classified into public cloud. This is not simply as it would seem, as a weakening of the enterprise cloud business. That is the three points I would like to offer. Thank you. Thank you. We will take our next question. Your question comes from Timothy Zhao from Goldman Sachs. Please go ahead. Your line is open. [Non-English content] Thank you very much for taking my question. My first question is regarding the MaaS business. Just wondering, compared to the peers in the market, how do you think about the Kingsoft Cloud competitive advantage in the MaaS services in terms of the application scenarios, etc.? Could you share more about the revenue recognition and the profitability profile of the MaaS service business? My second question is regarding the overall pricing trend in the AI cloud business. Just wondering if you can share what is the latest trend over the past couple months, and what have you heard from the customers after you announced a certain price hikes or discount reduction over the past few months, and whether you are able to quantify the impact from the price hike to your overall AI cloud revenue growth? Thank you. [Non-English content] In relation to your question about the positioning, we do have a unique positioning in the MaaS business. Namely, we are different from some of the full stack cloud providers, which they have their in-house or proprietary models. We do not have such models, and therefore, correspondingly, we do not have to sell those large language models that our affiliated companies have to offer. As a result, we are able to actually sell and we actually encourage our sales team to sell the models that our customers like the most. For example, the GLM, etc. That is number one. Secondly, it is quite important in today's market to have your proprietary or your own computing power, which is the only way that you can actually secure significant profitability in this business. [Non-English content] In relation to your question about the price hike, there are basically two products or solutions that we have employed increasing price. Number one, that is storage, and number two, that is computing power. I will talk about them respectively. In terms of storage, the incremental amount of storage actually comes with the intelligent computing demand. That is a relatively small portion of the intelligent computing overall ticket size. Therefore, in the vast majority of the customers that we negotiated with, they relatively easily accepted such a price hike. In which case, as a result, we are actually able to, in some cases, not only pass through the increase in our cost, but also increasing our profitability in that scenario. Number two, in terms of computing power, because of our specific capabilities, including pack capabilities, as well as the operating maintenance and network capabilities, again, we are able to pass through that cost hike into our customers. In some of the cases, we also increased our profitability. In this quarter, we have also some projects which we are doing managed services, which is an asset-light business model. We look forward to seeing more of that coming to and reflecting the financial statements. Thank you. We will take the next question. Your next question comes from Wei Zhang from UBS. Please go ahead, your line is open. [Non-English content] Good evening management, congrats on a solid quarter and thank you for taking my question. Considering the proprietary models and user ecosystem of other cloud providers, how should we think about our long-term positioning in the cloud market and the sustainable margin level down the road? Thank you. [Non-English content] We believe that for MaaS or cloud AI cloud service provider, it is important to be able to offer the top models which the customers like and also stable services to our customers. As mentioned, as a neutral cloud player, we are able to be in good relations with all of the top model providers, large language model labs, and be able to provide the best model according to our customers' demands. Also, based on our technology capabilities, we are able to provide highly available and highly reliable services to them out of the SLAs that we signed with them. I think thirdly, in relation to the profitability question you asked, it is important to work closely with the LLM labs, for example, to optimize the inference of those models. That would include, for example, working with them based on the undisclosed weighting of the models to increase our model inference efficiency. In some of the cases, we are able to get to a very close level or even reach the same level of the inference efficiency coming out from the LLM companies themselves. Thank you. Thank you. We will take our final question. Your final question comes from Yang Liu from Morgan Stanley. Please go ahead, your line is open. [Non-English content] Let me translate my question. I would like to ask under two business models, computing power leasing and MaaS, what is the ROIC for these two business models, and what is the marginal change for the ROIC? Thank you. Thank you, Liu Yang. At this stage, we do not disclose separate ROIC of MaaS and AI computing power services. ROIC varies across projects driven by payback cycles, gross margin, fixed assets and depreciation policies. Overall, MaaS bears much better probability than AI computing power services at this stage. We have seen continued improvement in operating leverage. As our AI business scales up, fixed cost 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 the continuous business structure optimization and maturing AI commercialization, I think our overall ROIC will keep improving steadily. Okay, thank you. Thank you. There are no further questions. Apologies. 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.