Kingsoft Corp Ltd Adr

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 1 and 1 on your telephone. You will then hear an automated message advising your hand is raised. To withdraw your question, please press star 1 and 1 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. Kingstop 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 News website. On the call today from Kingstop Cloud, we have our Vice Chairman and CEO, Mr. Zhou Tao, and CFO, Ms. Li Yi. Mr. Zhou 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 question during the Q&A session that follows. There will be constructive interpretation. Our interpretations are for your convenience and reference purpose only. In case of any discrepancy, management 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 Security Exchange Act of 1934 as amended and as defined in the U.S. Private Security 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. 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 and certainties or factors are included in the company's filings with the US 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 Zou. Hello, everyone. Welcome to the third round of the Group E-Learning Conference in 2025. I am Zou Tao, CEO of Jinan Yun. In the era of artificial intelligence entering thousands of pages and repeating the technical framework, Jingyan Yun has a firm strategic positioning and a clear direction of development. On the basis of stable satisfaction of the training needs of self-calibration, we are good at reasoning the technology and resource reserves that need to be exploded. Faced with the double trend of fast reception of models and the application of self-calibration, we have provided customers with stable and efficient integrated self-calibration services. and layout model API 5 will create a new growth engine based on the reasoning scene. Continuous income, high growth, and stable profitability level have proven the steady implementation of our strategic goals. Achieve high-quality and sustainable positive development. First of all, our three-week income reached 24.8 billion yuan. The same growth rate was increased from 24% in the previous quarter to 31% again. The public cloud and industry cloud have achieved the same rate of growth. Among them, the public cloud also increased by 49%, with a revenue of 17.5 billion yuan. Secondly, the self-proclaimed cloud business continues to develop rapidly. This quarter, the self-proclaimed cloud has a net income of up to 7.8 billion yuan, with a net growth of nearly 120%. which accounts for 45% of the total revenue of the public cloud. Compared to 31% in the same period last year, there has been a significant improvement. Calculation and cloud services co-exist, and are deeply integrated from technology, products to customer sales. Calculation needs not only drive the rapid development of the cloud, but also drive the growth of basic public cloud needs and the innovation of technology. drive the acceleration of cloud computing technology. From the self-calculation training group to the self-calculation original solution program, our computing service, model API service, storage service, and data service have been upgraded. Third, Xiaomi Jinshan Ecology is based in Laobu. This quarter, the revenue from Xiaomi Jinshan Ecology reaches 6.7 billion yuan, which is 84% of the total growth. The total revenue ratio is further increased to 28% In September 2025, the total revenue from Xiaomi Jinshan Ecology will be 18.2 billion yuan We expect to fully complete the business cooperation under the concept transaction this year and be fully confident in the further improvement of next year's turnover Finally This quarter, the company's net profit has been adjusted to 3.9 billion yuan, which is a 28% increase. The net profit has been adjusted to 1,536,000 yuan. The net profit has been adjusted to 0.6%. The net profit has been adjusted to 2873,000 yuan, which is the first time in history. 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 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. The Xiaomi and Kingsoft ecosystem continued to offer 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 growth 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 is becoming increasingly prominent. While accelerating the construction of intelligent computing infrastructure and technological capabilities,

We are also strengthening the control of costs and expenses. to provide customers with high-quality, high-performance, high-stability, and high-efficiency cloud computing services, especially for large-scale artificial intelligence and Internet-based enterprises. In the case of model training and reasoning business demand, we provide customers with stable training and integrated computing services. At the same time, we actively expand our customers' trust in cloud computing and cloud computing infrastructure. In terms of ecological customers, we continue to provide high-quality services for Xiaomi and Jinshan, and continue to add bottom-level resources to our ecological customers. In terms of industry cloud, this quarter we achieved a revenue of 7.3 billion yuan. We believe that today, when the artificial intelligence industry quickly fell, intelligentization will evolve from model capabilities to industry solutions, and the negative energy will be reintroduced into thousands of industries. and cloud as a smart, unspeakable asset. The vastness and vastness of the digital rich energy of 1,200 pages can be done. In such a market with an extended market of 10 billion units, Jinshan Cloud deeply excavates the genealogy of 2B corporate services, selects the best vertical industries and local areas, and builds the core competitiveness facing the future, winning the wide-ranging praise of the customer market. For example, in the field of public service, We are only one of the top companies in the government's self-calibration industry. With Gansu Qingyang as an example, Gansu Qingyang is one of the eight key points of the country's east and west. We will be responsible for the construction of the Gansu Qingyang government cloud platform, and the digitalization of all local government services. In the field of digital health, we have achieved a milestone in the field of artificial intelligence, China's clinical scene project breakthrough not only achieved the deep integration of Chinese medicine and artificial intelligence, but also at the high point of chronic disease management technology, and at the clinical level, it has verified the actual value of the actual value of the patient's life quality and disease control rate. After the benchmark project of the corporate service industry in the bank's受信报告智能生存的标杆性项目落地后, we will continue to push from the single受信报告发起到受信全流程的智能化转型。 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 2D enterprise services, targeted advantageous selected verticals and geographical regions, and built core competitiveness for the future. 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 West Computing, an essential area of 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 enterprise services sector, following the successful implementation of a landmark project for intelligent generation of bank credit reports, we continued 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 intelligent system, including customer onboarding, credit report generation, loan disbursement, monitoring and earning 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.

In terms of product technology, in the field of public cloud, Zhishan Cloud continues to strengthen its network platform capabilities. In the following three aspects, we have achieved significant progress. First, we have released a model API service to provide high-capacity, multi-level model call and management capabilities. In the follow-up, we have established a solid foundation for the diversified model service model. Secondly, the model online service upgrade integrate multiple open source models, have automatic expansion and expansion capability, provide high-capacity platform base for push-and-pull services. Third, our online data center and data center square are only supporting customers to provide data flow and full flow support, and assist customers to effectively advance the model training process. In the industry and field, based on private deployment scenarios, We have built a well-designed translation platform, a lightweight mass platform, and a production-based artificial intelligence knowledge warehouse, and are closely combined with the WS-AI real-time office applications to achieve the smart product architecture that customers can trust. At the same time, we will attract excellent talents from all over the country through the organization of the Beijing-Wuhan Double Research and Development Center to carry out talent team building, and continue to maintain the investment and strength in the business field. As of the end of the third quarter, the number of Wuhan employees has reached 2.8 times that of the launch of the Wuhan strategy in 2022. Overall, we will firmly rely on the historic opportunity brought by Xiaomi Jinshan Ecotourism to continue to invest in basic facilities, focus on the project capability of polishing core products, and continue to create value for our customers, shareholders, employees, and other stakeholders. Next, let's welcome our CFO, Ms. Li Yi.

In terms of product and technology, in public cloud space, we continued 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 data set 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 demand for private deployment scenarios, we have built a computing power scheduling platform, a lightweight mass platform, and a generative artificial intelligence knowledge base. And 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. Good evening and good morning everyone, and thank you all for joining the call today. Before we walk through the details of the financial results for the third quarter, I would like to highlight the following aspects. First, our revenue has consistently achieved year-over-year growth for six quarters, reaching 2,478 million this quarter. This represents an accelerated year-over-year growth rate of 31%, up from 24% in the previous quarter. Renew from public cloud service stood at 1,752.3 million, a significant increase of 49% from 1,165.5 million in the same quarter last year. Meanwhile, robust demand from our intelligent cloud, which also called as AI cloud business, drove around 120% year-over-year billing growth. which totaled $782.4 million. Second, profitability has been substantial improvement. Our adjusted growth 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 operational and adjusted net loss into profit simultaneously for the first time. These gains validate 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 the support during our recent equity financing in September. We successfully raised HK$2.8 billion and 80% 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 R&D as currency. Total revenues were $2,478 million. Of these, revenues from public cloud services were $1,752.3 million, up 49% from $1,175.5 million in the same quarter last year. Real News from enterprise cloud services reached $725.7 million, compared with $710 million in the same quarter last year. Total cost of Real News was $2,097.1 million, up 33% year-over-year, which was mainly due to our investment into infrastructure to support intelligent cloud business growth. IDC costs increased by 50% year-over-year, from $673.8 million to $775.7 million this quarter. The increase was mainly due to the purchase of RACs, which serve their expanding intelligent cloud business, as well as the basic computing and storage cloud demands brought by AI development. Depreciation and amortization costs increased from 297.5 million in the same quarter of 2024 to 649.7 million this quarter. The increase was mainly due to the depression of newly acquired and leased servers and later work equipment which were mainly allocated to intelligent cloud business. Solution development and services cost increased by 90% year over year from 499 million in the same quarter of 2024 to 595.9 million this quarter. The increase was mainly due to the solution's low expansion. Fulfillment costs and other costs were 5.2 million and 17.6 million this quarter. Our adjusted gross margin for the quarter was 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 enlarged contribution from Intelligent Cloud, and the cost control of IPC racks and servers. Adjusted growth margin increased from 50% last quarter to 16% in this quarter. On the expense side, excluding sharpest compensation costs, our total adjusted operating expenses were $420.9 million. decreased by 70% over a year and 25% quarter-over-quarter, of which our adjusted R&D expenses were $188.4 million, decreased by 90% from the same quarter last year. The decrease was mainly due to the decrease of personal costs resulting from our strategic adjustment for research teams, as well as the expense serving to from Beijing-Wuhan dual research center strategy. Adjusted selling and marketing expenses were $127.6 million, increased by 50% year-over-year. Adjusted general and administrative expenses were $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 $197 million in the same quarter last year. Our adjusted operating profit was $15.4 million, turning profit from adjusted operating loss of $140.2 million in the same period last year. The improvement was mainly due to the expansion of revenue scale and 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 8 percentage points. Our non-GAAP EBITDA profit was $826.6 million, increased by 3.5 times of $185.4 million in the same quarter last year. Our long gap EBITDA margin achieved 33%, compared with the 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 retirement impact of subsidy in other income. As of September 30, 2025, our cash and cash equivalents totaled $3,954.5 million, decreased from $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 access of 10x24 finance list allowabilities was 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, strengthening technology, enhanced 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 Wei, and now I'll give you start a Q&A session, please ask your question in both Mandarin, Chinese, and English, if possible. Peter, please go ahead. Thank you.

Thank you. As a reminder, to ask a question, you will need to press star 1 and 1 on your telephone and wait for your name to be announced. To withdraw your question, please press star 1 and 1 again. Please stand by while we compile the Q&A queue. Our first question comes from the line of Xieodan Zhang from CICC. Please go ahead. Your line is open.

Hi, Mr. Zhou, Ms. Li, Mr. Nicole Clark. Good evening. Thank you for answering my question. I have two questions. The first one is that we see that the income of AI in three dimensions has achieved a very bright growth. I would like to ask you to disassemble the management layer, which is the main driving factor behind it. Are there any structural changes in the needs of our internal and external customers? So thanks management for taking my questions. And first of all, What are the key drivers of AI revenue growth in Q3? And has there been any structural change in the demand of your ecosystem and external clients for the past quarter? And secondly, how does management see the margin trend in the coming quarters? And what's the expected mix of different computing resources acquisition models? Thank you.

Please stand by while the speakers reconnect. Please stand by. 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.

Sorry, Sheldon. We didn't get your question. Could you repeat that again? Thank you.

Yes, no problem. So my first question is regarding the AI revenue. So could management break down the key drivers for AI revenue in Q3? And has there been any structural change in the demand of your ecosystem and external clients for the past quarter? And secondly, how does management see the margin trend in the coming quarters? And what's expected mix of different computing resources acquisition models going onwards? Thank you.

I'll answer first, and then you can add to it. I'll answer first, and then you can add to it. I think the main reason for the increase is that we have gradually completed the order delivery in the first two or three seasons, or the complete delivery, and then entered a stage of full delivery. This is the core. Of course, there is also a part that is from So basically, the core reason behind the AI revenue growth in Q3

is that we have some clusters that partially delivered in the previous quarters, for example, like the second quarter of 2025. And these clusters and these services have only been partially accounted for revenues from a full quarter basis. But now in Q3, they are starting to be recognized as full quarter revenues. And also, there's 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 are delayed into the third quarter.

Xiao Liang, just now, because we cut the line, I didn't hear your other question.

Yes, my first question is about AI. And I also want to ask about Is there any structural change in the demand of our internal and external customers in the third quarter? And then my second question is, we have seen that since this year, because of the change in the calculation resource acquisition model, although the profit-saving rate has dropped a bit, but our EBITDA profit-saving rate has improved significantly. I would also like to ask Mr. Zhou to share his expectations for the profitability trend in the future, and what will be the structure and proportion of our different algorithmic opportunities in the future? Thank you.

I will answer Liu Tao and Li Yizuo first. The changes in the customer demand in the internal and external sectors are like this. I also talked about it in the last episode. Uh, uh, uh, uh, uh, uh, uh, uh. We also, through this queue, we also clearly feel that this kind of model is really applied, whether it is public or public. This kind of trend of entering thousands of industries is becoming more and more obvious. In fact, we also released a new platform in September. In fact, it is also to welcome the arrival of the next stage of AI applications. At the same time, this question can also echo the change in the maoli level that you just mentioned. In fact, in the last question, we also talked about it. As our scale becomes larger, anyway, we are concentrated in a few big companies. So, compared to the maoli level of our earliest business, it has dropped again. So, we are also actively deploying higher maoli. To put it bluntly, from the current development trend, we think So 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, a 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. At the current stage, we still see 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. So in face of this general trend, we have also, as we mentioned in the prepared remarks, we have launched our Starflow platform to meet the demands of such general trend. And 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. And therefore, we think that when that wave of demand comes, we expect to have higher margins.

Thank you, Xiaozhan. 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 remain about 20%. I have to mention that the significant quote-on-quote improvement this quarter was mainly driven by one-time other income, which will return to the normal level next quarter. Thank you, Xiaobai.

Operator, next question, please.

Thank you. Our next question comes from the line of Wenting Yu from CLSA. Please go ahead. Your line is open.

Hey, President Zhou, President Li, President Clark, good evening. Thank you for the opportunity to ask me a question. I have two questions to ask. The first one is, can you please share with the management level the forecast for next year's income guidance and increase? In the future, what industries and scenarios do we expect to have strong profit demand in the future to promote our income growth? The second question is that we see that domestic and overseas cloud companies have increased the ratio of server rents in the software resource configuration. Combined with the market situation of purchasing and rents in the market, how do we consider the distribution of these two methods in terms of cost-effectiveness and profitability? I will quickly summarize my question. 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 industries and application scenarios are expected to have strong computing power demand that could drive the revenue growth next year. And the second question is, with multiple club providers in both China and U.S. increasing the proportion of server leasing in their computing resource mix, and how does management view the current market dynamics for procurement versus leasing? And from a cost effectiveness and profit margin perspective, how would the company allocate the resources between these two approaches? Thank you.

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 show the specific details with you once it was finalized. However, regarding the demand for our AI business, we are fully confident in the subsequent demand growth. And for your second question about the Regarding the procurement method, we primarily align our capital channels with actual customer needs, including collector skills, delivery time, and the supply inventory levels. There's no rigid total allocation target. From the cost effectiveness perspective, both approaches have their own pros and cons. The leasing model defines 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. Sales 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 pressure on profit margins.

Thank you.

Yeah, you know, you know, as you mentioned that, you know, the robotic companies in China is a closing very fastly. So, uh, you know, as you, uh, this year we have covered most of the robot companies in China and, uh, we can see the revenue is increasing very rapidly. So in the next year we believe that, uh, uh, increase of the robotic companies will also be fast. Meanwhile, you know as more and more Internet companies in China using talking token services, which is the API services we are seeing the Increasement of the business is very quickly. So we believe in the next year. This will be a very important factors to Drive in the revenue to increase.

Thank you What that was for you uh uh uh You see,可能有一定风险或者说在在这个整个发展的这个还是在这个发展过程当中的这一些我们基本上逐渐逐渐会倾向于这种逐渐的方式来提供服务这样也是进一步降低我们自身的这个风险好吧所以那个当然没有一个具体的 I don't know. I don't know. I don't know. . . .

Hello. So this is the CEO. He added that you understand that your second question is really about the choice between the leasing model and the CapEx model. So we've talked about that before. So generally, there's a general rule of thumb. So when we're looking at the larger customers, especially the customers that have solid profiles, 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, small and medium size companies, we generally tend to adopt the leasing model, which is also a meaningful way to reduce our own risk. So as Lee rightly mentioned, there's no top-down target for the split between these two different methods. And we also talked about in the last quarter as well that the impact of these two different methods have different impacts to growth margins. However, we have seen the financial results for the past three quarters, which we have adopted various combinations of these two different models. And 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.

Thank you, Timothy. Next question, please.

Thank you. Our next question comes from the line of Timothy Zhao from Goldman Sachs. Please go ahead. Your line is open.

Okay, thank you for accepting my question. My question is still about training and reasoning. I would like to ask what is the difference between the pricing of our entire AI training and reasoning? In the past few months or this year, what are the special changes in the pricing of the entire AI service? In terms of the usage rate of our reasoning and training cards, Thank you, Benjamin, for taking my question. My question is regarding the differences between AI training versus inferences. Could Benjamin 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? And in terms of the overall utilization rate of the chips of GPUs, pricing and probability, can you share more color on the gap between training and inferences? Thank you.

OK. Let me answer these questions. When I'm talking about the price strategy for inference and the training, there's not too much difference between two things. So the price is based on the price qualities how many how many sources use which is Most important factors and also comparing you know the margin rate You know there was two there are two kind of influence Services with one is you know customer by resource and use our platform to influence so that margin ratio is very similar to the training margin ratios and But another one is customers directly buy our API token services. We think that will have a better margin ratio. But this business is just in the beginning, so we need time to see what is the big difference between the two things.

Thank you.

Thank you. Due to time constraints, this concludes our question and answer session. So 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.