Q3 2025 Kingsoft Cloud Holdings Ltd Earnings Call
Reference 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
Operator: I would now like to hand the conference over to your speaker today, Nicole Shan, IR Director of Kingsoft Cloud. Please go ahead.
Yi Li: 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.
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 a draw. Your question. Please press star 1 and 1 again, please be advised. That today's conference is being recorded. I will now like to hand the conference over to your speaker today. Nicole, Champs I are director of King soft Cloud. Please go ahead.
Nicole Shan: Thank you, Operator. Hello everyone, and thank you for joining us today. Kingsoft Cloud Q4, Q2 2025 earnings release was distributed earlier today and is available on our IR website at ir.ksyun.co, as well as on the TI NewsWare services. On the call today from Kingsoft Cloud, we have our Vice Chairman and the CEO, Mr. Zhou Tao, and the CFO, Ms. Li. 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 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.
Nicole Shan: Thank you operator. Hello everyone, thank you for joining us today. Kingsoft Cloud Q3 2025 earnings release was distributed earlier today and is available on our IR website at ksyun.com, as well as on the PR Newswire services. On the call today from Kingsoft Cloud, we have our Vice Chairman and CEO, Mr. Tao Zou, and the CFO, Ms. Yi 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 question during the Q&A session that follows. There will be consecutive interpretation. All interpretations are for your convenience and reference purpose only. In case of any discrepancy, management statement in 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, relate to events that involve known or unknown risks, uncertainties, and other factors, all of which are difficult to predict and many of which are beyond the company's control, which may cause the company's actual results, performance or achievements to differ materially from those in the forward-looking statements. Further information regarding these and other risk, uncertainties, or factors are included in the company's filings with the U.S. SEC. The company does not undertake any obligation to update any forward-looking statements as a result of new information, future events, or otherwise, except as required under applicable law. Finally, please note that, unless otherwise stated, all financial figures mentioned during this conference call are denominated in RMB. It's now my pleasure to introduce our Vice Chairman and CEO, Mr. Zou. Please go ahead, Mr. Zou.
Thank you, operator. Hello everyone. And thank you for joining us today. Kingsoft, Cloud. So quarter 2025 earnings release was distributed earlier today, and is available on our IR website at IR. Doc here, as well as on the pr news World services on the call today from Kings of cloud, we have our white chairman CEO, Mr. Dotel. And therefore need the Mr. Doe will review our business, strategies operations, and other company highlights followed by Miss li, who will discuss the financial performance. There will be available to answer your question. During the Q&A session that follows there will be consecutive integration. Our interpretations are for your convenience and reference purpose only in case of any descriptions management statement in the original language will prevail before we begin, I'd like
Nicole Shan: Before we begin, I'd like to remind you that this conference call contains forward-looking statements within the meaning of Section 21E of the Securities Exchange Act of 1934, as amended, and as defined in the US Private Securities Litigation Reform Act of 1995. These forward-looking statements are based upon management's current expectations and current market and operating conditions, and 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 US SEC.
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 a mandate. And as defend in the US, private security investigation. Reform Act of 1995. This forward-looking statements are based upon Management's, current expectations, and current market, and operating, conditions, and relate to events, that involve knowledge, or unknown risk, 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 different maturity from those. In the forward-looking statements further information regarding this and other risks. And certainties of factors are included in the comments, filings with the US and EC. The company does not undertake any obligation to update any forward-looking statements, as a result of new information, future events or otherwise, if
Nicole Shan: 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 the CEO, Mr. Zhou. Please go ahead, Zhou Tao.
You accept as required under applicable law. Finally, please note that I analyze otherwise stated all Financial fingers mentioned during this conference call are denominated in R&B. It's now my pleasure to introduce our West chairman and CEO Mr. Zou please go ahead.
Tao Zou: 大家好，欢迎参加金山云2025年第三季度业绩电话会。我是金山云CEO周涛。在人工智能进入千行百业、重塑技术格局的时代变革中，金山云坚定战略定位，明确发展方向，在稳健满足计算训练需求的基础上，做好推理需求爆发的技术和资源储备。面对模型快速迭代与计算规模化应用的双重趋势，我们为客户提供了稳定高效的训推一体计算服务，并布局模型API业务，将推理场景打造为新的增长引擎。持续的收入高增长和稳健的利润率水平印证了我们战略举措的稳步落实，实现高质量和持续的良性发展态势。 首先，我们三季度收入达到24.8亿元人民币，同比增长率由上季度的24%再次提速到31%。公有云和行业云均实现了同环比的增长，其中公有云同比大幅增长49%，收入实现17.5亿元人民币。 其次，智算云业务保持快车道发展。本季度智算云上云收入达7.8亿元人民币，同比增长近120%，占公有云收入比例达到了45%，相较去年同期的31%大幅提升。智算和云服务协同共生，从技术、产品到客户销售等方面都深度融合。智算需求不仅仅带动了智算云的快速发展，同时带动了基础公有云的需求增长与技术的创新，驱动了云计算技术的加速迭代。从智算训练集群到智算原生解决方案，我们的算力服务、模型API服务、存储服务、数据服务都进行了升级。 第三，小米金山生态根基牢固。本季度来自小米金山生态的收入达6.7亿元人民币，同比增长84%，占总收入比例进一步提升至28%。2025年1至9月，来自小米金山生态的收入合计达18.2亿元。我们预计今年较为充分地完成关联交易额度下的业务合作，并对明年额度的进一步提升充满信心。 最后，本季度公司经调整毛利润率达到3.9亿元人民币，同比增长28%。经调整经营利润扭亏为盈，达到1,536万元人民币。经调整经营利润率0.6%，经调整净利润历史上首次实现盈利，达2,873万元。公司兼顾收入增长和盈利能力提升，规模效应日渐显著。在加速自算基础设施和技术能力建设的同时，强化成本与费用的管控。
Tao Zou: 大家好，欢迎参加金山云2025年第三季度业绩电话会。我是金山云CEO周涛。在人工智能进入千行百业、重塑技术格局的时代变革中，金山云坚定战略定位，明确发展方向。在稳健满足自算训练需求的基础上，做好推理需求爆发的技术和资源储备。面对模型快速迭代与自算规模化应用的双重趋势，我们为客户提供了稳定高效的迅推一体自算服务，并布局模型API业务，将推理场景打造为新的增长引擎。持续的收入高增长和稳健的利润率水平印证了我们战略举措的稳步落实，实现高质量可持续的良性发展态势。首先，我们三季度收入达到24.8亿元人民币，同比增长率由上季度的24%再次提速到31%。公有云和行业云均实现了同环比的增长，其中公有云同比大幅增长49%，收入实现17.5亿元人民币。其次，自算云业务保持快车道发展。本季度，自算云上单收入达7.8亿元人民币，同比增长近120%，占公有云收入比例达到了45%，相较去年同期的31%，大幅提升。自算和云服务协同共生，从技术、产品到客户销售等方面都深度融合。自算需求不仅仅带动了自算云的快速发展，同时带动了基础公有云的需求增长与技术的创新，驱动了云计算技术的加速迭代。从自算训练集群到自算原生解决方案，我们的算力服务、模型API服务、存储服务、数据服务都进行了升级。第三，小米金山生态根基牢固。本季度，来自小米金山生态的收入达6.7亿元人民币，同比增长84%，占总收入比例进一步提升至28%。2025年1至9月，来自小米金山生态的收入合计达18.2亿元，我们预计今年较为充分地完成关联交易额度下的业务合作，并对明年额度的进一步提升充满信心。最后，本季度公司经调整毛利润率达到3.9亿元人民币，同比增长28%。经调整经营利润率，经营利润扭亏为盈，达到1536万元人民币。经调整经营利润率0.6%。经调整净利润，历史上首次实现盈利达2873万元。公司兼顾收入增长和盈利能力提升，规模效应日渐显著。在加速自算基础设施和技术能力建设的同时，强化成本与费用的管控。
The.
For.
For.
Hello everyone. Thank you and welcome to King soft clouds. Third, quarter, 2025 earnings call. I am sold house CEO of kingsoft cloud.
Clark: Hello everyone, thank you and welcome to Kingsoft Cloud's Q3 2025 earnings call. I am Zhou 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.
Tao Zou: Hello everyone, thank you and welcome to Kingsoft Cloud Q4, Q2 2025 earnings call. I am Zhou 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, efficient, integrated training and inference intelligent cloud computing services, and have laid out model API business to turn inference scenarios into new growth engines.
In the area that artificial intelligence is implemented across various industry, verticals and reshaping the technological landscape. Kings of cloud, has firmly established in the Strategic positioning.
And Define 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, Cloud Computing Services
And have laid out model, API business to turn inference scenarios into New Growth engines.
Clark: 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 Q3 reached RMB 2.48 billion, with year-over-year growth rate accelerating from 24% in Q2 to 31% in Q3. 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. Q3, gross billings of Intelligent Computing Cloud reached RMB 782 million, with a year-over-year growth around 122%.
Tao Zou: 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 substantial high growth in revenue and the stable profit margin levels, validates, the steady execution of our strategic measures achieving high quality and sustainable development.
first, our Revenue in the third quarter reached R&B 2.48 billion with year-over-year growth rate accelerating from 24% in the previous quarter to 34 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 R&B 1.75 billion.
Second intelligent Computing, Cloud business remains on Fast development track this quarter growth, buildings of intelligent Computing reached R&D 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.
Clark: 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 solid foundation.
Generative artificial. Intelligence and Cloud are seeing the optically integrated in many aspects, including technology products and customer cross sales.
Tao Zou: 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.
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 native Technologies are computing, power Services, model API Services, storage services, and data services have all been upgraded.
Clark: 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%.
Third, the xiaomi and kingsoft ecosystem continues to offer solid foundation. This quarter revenue from the xiaomi and kings of the ecosystem reached. The Army 691 million increase in by 48 by increasing by 84% year-over-year and is proportioned in the total revenue further Rose to 28%.
From January to September 2025, the total revenue from the xiaomi and kings of the ecosystem reached R&D 1.82 billion. We anticipate adequately fulfilling the business cooperation under the continuing connected, transactions, annual report, and this year. And the optimistic, in the further, increase of the quota. And next year,
Profit for this quarter. Reached R&B 393 million representing a year-over-year increase of 28%.
Tao Zou: 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.
The adjusted operating profit turned from loss to profit reaching R&B 15.33 reaching R&B.
15.36 million and the adjusted operating profit. Margin was 0.6%, the adjusted net profit recorded at historical. Positive profit of R&B 28.73 million for the first time.
Clark: 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.
The company is aiming at both Revenue growth and profitability improvements as as the economies of scale is becoming increasingly prominent.
While accelerating the construction of intelligent Computing infrastructure and technological capabilities, we also strengthening the control of costs and expenses.
Tao Zou: 下面我向大家具体介绍2025年第三季度的业绩情况。公有云方面，本季度实现收入17.5亿元人民币，同比增长49%。智算云业务保持强劲的增长，我们成功地支持了多家互联网行业头部客户的大规模训练和推理需求，为客户提供高质量、高性能、高稳定、高效率的云计算服务。特别是诸多生成式人工智能和互联网企业，在模型训练和推理业务兼具需求的情况下，我们为客户提供了稳定的训推一体智算服务。同时，我们在客户拓新以及智算云基础公有云协同售卖方面积极拓展。生态客户方面，我们持续为小米和金山提供优质服务，并继续为生态客户新增底层资源，夯实智算需求的快速响应能力。行业云方面，本季度实现收入7.3亿元人民币。我们坚信，在人工智能产业快速迭代的今天，智能化必将从模型能力向行业解决方案演化，赋能和重塑千行百业。而云作为智能化不可或缺的载体，数字化赋能千行百业的天地广阔，大有可为。在这样万亿级持续扩张的市场，金山云深度挖掘To B企业服务的基因能力传承，精选优势垂直行业和地域区域，打造面向未来的核心竞争力，赢得了客户与市场的广泛好评。举例来说，公共服务领域，我们旨在成为政府行业智算推力员的首选云伙伴。以甘肃庆阳为例，作为国家东数西算八大节点之一，智算业务的聚集地，我们将负责建设甘肃庆阳政务云平台，全面赋能当地政务的智能化、数字化。数字健康领域，我们实现了里程碑式的人工智能加中医临床场景项目突破，不仅实现了中医理论与人工智能的深度融合，抢占慢病管理技术的制高点，更在临床层面验证了智能化在提升患者生活质量和疾病控制率的实际价值。企业服务领域，在银行授信报告智能生成的标杆性项目落地后，我们继续推行从单一的授信报告发起到授信全流程的智能化转型，打造从客户准入、授信报告生成到贷款发放、监控预警以及贷后报告的智能体系。我们坚信这些已沉淀的成功经验、市场口碑及可复用的核心解决方案，将使我们在这一产业浪潮中占得先机，构筑坚实的核心竞争力，实现高质量可持续的股东回报。
Tao Zou: 下面我向大家具体介绍2025年第三季度的业绩情况。公有云方面，本季度实现收入17.5亿元人民币，同比增长49%。自算云业务保持强劲的增长，我们成功地支持了多家互联网行业头部客户的大规模训练和推理需求，为客户提供高质量、高性能、高稳定、高效率的云计算服务。特别是诸多生成式人工智能和互联网企业，在模型训练和推理业务兼具需求的情况下，我们为客户提供了稳定的迅推一体自算服务。同时，我们在客户拓新以及自算云基础公有云协同售卖方面积极拓展。生态客户方面，我们持续为小米和金山提供优质服务，并继续为生态客户新增底层资源，夯实自算需求的快速响应能力。行业云方面，本季度实现收入7.3亿元人民币。我们坚信，在人工智能产业快速迭代的今天，智能化必将从模型能力向行业解决方案演化，赋能和重塑千行百业。而云作为智能化不可或缺的载体，数字化赋能千行百业的天地广阔，大有可为。在这样万亿级持续扩张的市场，金山云深度挖掘2B企业服务的基因能力传承，精选优势垂直行业和地域区域，打造面向未来的核心竞争力，赢得了客户与市场的广泛好评。举例来说，公共服务领域，我们旨在成为政府行业自算推理云的首选云伙伴。以甘肃沁阳为例，作为国家东数西算八大节点之一，自算业务的聚集地，我们将负责建设甘肃沁阳政务云平台，全面赋能当地政务的智能化、数字化。数字健康领域，我们实现了里程碑式的人工智能+中医临床场景项目突破，不仅实现了中医理论与人工智能的深度融合，抢占慢病管理技术的制高点，更在临床层面验证了智能化在提升患者生活质量和疾病控制率的实际价值。企业服务领域，在银行授信报告智能生成的标杆性项目落地后，我们继续推行从单一的授信报告发起到授信全流程的智能化转型，打造从客户准入、授信报告生成到贷款发放、监控预警与贷后报告的智能体系。我们坚信，这些已沉淀的成功经验、市场口碑及可复用的核心解决方案，将使我们在这一产业浪潮中占得先机，构筑坚实的核心竞争力，实现高质量、可持续的股东回报。
Wait.
Sometimes.
Could be cheerful.
For.
Now, I would like to walk you through the key. This is highlights for the third quarter of 2025
Tao Zou: 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.
Clark: Now I would like to walk you through the key business highlights for Q3 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 public cloud, services Revenue, reached R&B 1.75 billion in the in the in this quarter, making a year-over-year increase of 49%,
The intelligent Computing Cloud business has maintained strong growth. We have success successfully supported, the large scale training and inference demands of various top internet customers, providing high quality and 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 intelligence Computing Services for different scenarios.
Tao Zou: 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 2B 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.
Clark: 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 To B 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.
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 R&B 730 million. We firmly believe that in today's rapidly evolving generative artificial intelligence landscape intelligence, we 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 intelligence.
In this trillion dollars sustainably expanding Market, we have deeply explored our our inherent DNA of 2DS, 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 markets.
Tao Zou: 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 demand. Taking Qingyang City in Gansu Province as an example, as one of the eight major nodes of the national project East Data West 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.
Clark: 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 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.
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 demand.
Taking chinga City in Gansu Province as an example, as 1 of the 8, major nodes of the national project East data, West Computing and a central area of intelligent Computing businesses. We will be responsible for building the Public Services Cloud platform in China to fully empower, the local public services affairs with the intelligence and digitalization.
Tao Zou: 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 rates 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 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 intelligence system, including customer onboarding, credit report generation, loan disbursement, monitoring and early warning, and post-loan reporting.
Clark: 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 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.
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 in 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 continue to advance the intelligent transformation across the entire credit approval process,
Tao Zou: 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.
Clark: 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.
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 early warning and post loan reporting. We firmly believe that these proven accumulated successful experiences Market reputation and replicable. Work 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.
Tao Zou: 产品技术方面，工业云领域，本季度智算云持续强化星流平台能力，在以下三个方面取得了重要进展。首先，我们发布了模型API服务，提供高可用、集成的模型调用与管理能力，为后续提供多样化的模型服务模式打下了扎实的基础。其次，模型在线服务升级，整合多款开源模型，具备自动扩缩容能力，为推理服务提供高可用平台底座。第三，我们上线的数据标注及数据集广场，旨在为客户提供数据流转全流程的支撑，助力客户高效推进模型训练进程。行业与领域，我们基于私有化部署场景，建设了算力调度平台、轻量化MaaS平台和生成式人工智能知识库等，并紧密与WPS AI政务办公应用相结合，打造行业云客户可信赖的智能产品架构。同时，我们将通过北京、武汉双研发中心的组织建设，吸引各地优秀人才，进行人才梯队建设，持续保持在智算领域的投入强度。截至三季度末，武汉员工数量已达2022年武汉战略发布之初的2.8倍。总体而言，我们将坚定以小米金山生态带来的历史性机遇为抓手，继续投资基础设施，专注于打磨核心产品及解决方案能力，为我们的客户、股东、员工和其他利益相关方持续创造价值。接下来有请我们的CFO李毅女士为大家介绍三季度财务运营，谢谢。
Tao Zou: 产品技术方面，公有云领域本季度自算云持续强化新流平台能力，在以下三个方面取得了重要进展。首先，我们发布了模型API服务，提供高可用一级层的模型调用与管理能力，为后续提供多样化的模型服务模式打下了扎实的基础。其次，模型在线服务升级，整合多款开源模型，具备自动扩缩容能力，为推理服务提供高可用平台底座。第三，我们上线的数据标注及数据集广场，旨在为客户提供数据流转全流程的支撑，助力客户高效推进模型训练进程。行业云领域，我们基于私有化部署场景，建设了算力调度平台、轻量化MaaS平台和生成式人工智能知识库等，并紧密与WPS AI政务办公应用相结合，打造行业云客户可信赖的智能产品架构。同时，我们将通过北京、武汉双研发中心的组织建设，吸引各地优秀人才，进行人才梯队建设，持续保持在自算领域的投入强度。截至三季度末，武汉员工数量已达22年武汉战略发布之初的2.8倍。总体而言，我们将坚定以小米金山生态带来的历史性机遇为抓手，继续投资基础设施，专注于打磨核心产品及解决方案能力，为我们的客户、股东、员工和其他利益相关方持续创造价值。接下来有请我们的CFO李毅女士为大家介绍三季度财务业绩，谢谢。
Nissan.
Woman.
Clark: In terms of product and technology in public cloud space, we continue to enhance the technology of intelligent computing cloud this quarter, strengthening the capability 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.
Tao Zou: 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 TaoFlow 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 platform. 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 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 3 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 paradigm,
second, we upgraded our online model Services integrating multiple open-source Foundation models and equipped with automatic scaling capabilities, offering a highly available inference platform,
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 to a lot of training process.
Enterprise Cloud space.
Clark: In enterprise cloud space, in order to meet the demands for private deployment scenarios, we have built a computing power scheduling platform, a lightweight MaaS 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.
Tao Zou: 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 2.8x the headcount back in 2022 when we first launched our Wuhan strategy.
In order to meet the demand for private deployment scenarios, we have built a computing power scheduling platform, a lightweight, math 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 built 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 have come back in 2022. When we first launched our Wuhan strategy,
Tao Zou: Overall, we will firmly seize the historical 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.
Clark: 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. Yi Li, our CFO, to go over our financials for Q3 2025. Thank you.
Overall we will firmly see 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 miss Li e our CFO to go over our financials for the third quarter of 2025. Thank you.
Yi Li: Thank you, Zhou-dong. 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 Q3, I would like to highlight the following aspects. First, our revenue has consistently achieved year-over-year growth for 6 quarters, reaching CNY 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 stood at CNY 1,752.3 million, a significant increase of 49% from CNY 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 CNY 782.4 million.
Yi Li: Thank you, Douglas, and Kingsoft Cloud. 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, our revenue has consistently 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 services stood 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 from our intelligent cloud, which also codes as AI Cloud Business, drove around 120% year-over-year billing growth, which totaled RMB 782.4 million. Second, profitability has seen substantial improvement.
Good evening, and good morning, everyone. And 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 boring aspects,
First I will you have a dream year-over-year growth for 6 quarters, reaching 2478 million, this quarter, this represents an accelerated year-over-year growth rate of 31% up from 24% in the previous quarter.
Grow from 5 cloud service. Sold at 1,700 and 52.3 million, a significant increase of 49% from 1,155.5 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 700 and 82.4 million
Second profitability has been substantial Improvement.
Yi Li: 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 operational and adjusted net loss into a profit simultaneously for the first time. This gain 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.
Yi Li: 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.
Our adjusted growth margin Roi 16% up from 50% in the previous quarter and adjusted. The epitome of margin improved to 33% compared with 17% last quarter.
Note boys, we turned quarterly adjusted operational and adjusted later life into profit simultaneously for the first time.
This game, validate our strong execution, interesting 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 to equity financing in September.
Yi Li: 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 on our financial results for Q3 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.
We successfully 2.8 billion. And 8% of the fund will be allocated to further investment in are infrastructure and transport them to General operational. Needs this funding will finally undertake the growth of our intelligent Cloud business, and enable us to create long-term value for all stakeholders.
Haven't seen.
Yi Li: Now, I will walk you through our financial results for the third quarter of 2025 and use the RMB as a 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 to RMB 775.7 million this quarter. The increase was mainly due to the purchase of racks, which serve their expanded intelligent cloud business, as well as the basic computing and storage cloud demands brought by AI development.
Total revenue. What 20148 million of these revenues from public cloud. Services were when found 70052.3 million of 49% from 1,175.7 million in the same quarter last year.
Real news from Enterprise cloud services rated 725.7 million compared with 710 million in the same quarter last year.
Yi Li: Total cost of revenues were CNY 2,097.1 million, up 33% year-over-year, which was mainly due to our investment into infrastructure to support the intelligent cloud business growth. IDC costs increased by 50% year-over-year from CNY 673.8 million to CNY 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 CNY 297.5 million in the same quarter of 2024 to CNY 649.7 million this quarter. The increase was mainly due to the depreciation of newly acquired and leased servers and network equipment, which were mainly allocated to intelligent cloud business.
Total cost of real news were 297.1 million up to 33% year-over-year which was mainly due to our investment into infrastructure to support the intelligent Cloud business growth.
IBC cost increased by 50% year-over-year from 600733.8 million to 7775.7 million recorded.
The increase was mainly due to the purchase of racks, which serve their expanded intelligent Cloud business, as well as the best Computing and storage Cloud demands, followed by AI development.
Differentiation and amortization costs.
Yi Li: 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 later 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 inordinate contribution from intelligent cloud, and the cost control of IBC racks and servers. Adjusted gross margin increased from 50% last quarter to 16% in this quarter.
Increased from 2 hands 97 minute in the same quarter or 2024 to 649.7 million with quarter. The increase was mainly due to the depression of newly Acquired and listed servers. And later work equipment, which were mainly allocated to intelligent Cloud business.
Yi Li: Solution development and services costs increased by 90% year-over-year from CNY 499 million in the same quarter of 2024 to CNY 595.9 million this quarter. The increase was mainly due to the solution personal expansion. Fulfillment costs and other costs were CNY 5.2 million and CNY 17.6 million this quarter. Our adjusted gross margin for the quarter was CNY 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 united contribution from Intelligent Cloud and the cost control of IDC racks and servers. Adjusted gross margin increased from 50% last quarter to 60% in this quarter.
Solutions development and services cost increased by 90% year-over-year from 499 million in the same quarter of 2024 to 595.99 this quarter. The increase was mainly due to the solutions has no expansion
for your me cost. And other costs were 5.2 million and 71.6 million with quarter.
Our adjusted growth margin for the quarter was 392.6 Million increased by 28% year-over-year and 12% quarter of quarter. It was mainly due to the expansion of our Revenue skills, the United contribution from intelligent cloud and the cost control of IBC, rocks and servers.
Adjusted gross margin increased from 50% last quarter to 16% in this quarter.
Yi Li: 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.
Yi Li: On the expense side, excluding traffic concession costs, our total adjusted operating expenses were CNY 420.9 million, decreased by 70% year-over-year and 25% quarter-over-quarter. Of which, our adjusted R&D expenses were CNY 188.4 million, decreased by 90% from same quarter last year. The decrease was mainly due to the decrease of personal costs resulting from our strategic adjustment for research team, as well as the expense owing to from Beijing Wuhan dual research team strategy. Adjusted selling and marketing expenses were CNY 127.6 million, increased by 15% year-over-year. Adjusted general and administrative expenses were CNY 104.9 million, decreased by 29% year-over-year due to the reverse of credit loss.
On the expense side, exclusive best conversion cost on how to adjust the operating expenses for 420.9 million decreased by 70% over a year and 25% report of quarter of which are adjusted and expenses for 108 88.4 million decreased by 90% from same quarter last year. The decrease was mainly due to the decrease of personal cost resulting out, strategic adjustment, for research team, as well as the expense serving to, from Beijing Wuhan deal research. Same strategy.
Adjusting selling and marketing expenses for 127.66% year-over-year, adjusted General and administrative expenses for 104.9 million decreased by 29% year-over-year due to the reverse of credit loss, the impairment of longing at that was near this quarter compared with that 100 and 190.7 million in the same quarter last year.
Yi Li: The impairment of long-lived assets was nil this quarter, compared with CNY 190.7 million in the same quarter last year. Our adjusted operating profit was CNY 15.4 million, turning profit from adjusted operating loss of CNY 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 -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 CNY 826.6 million, increased by 3.5x of CNY 185.4 million in the same quarter last year.
Our adjusted operating profit was 15.4 Million.
Turning profit for adjusted operating loss of 140.2 million in the same period last year.
The Improvement was mainly due to the expansion of Revenue skill and Profit. The expense can show, as well as the reverse of credit loss.
Yi Li: 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 8 percentage points. Our long gap EBITDA profit was RMB 826.6 million, increased by 3.5x 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 our income. As of 30 September 2025, our cash and cash equivalent totaled RMB 3,954.5 million, decreased from RMB 5,464.1 million as of 30 June 2025.
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 long Gap in beta profit was
Yi Li: Our non-GAAP EBITDA margin achieved 33% compared with 10% in the same quarter last year. It was mainly due to our strong commitment to intelligent computing cloud development, strategic adjustment of business structure, strict control over costs and expenses, as well as the non-recurring impact of subsidy in our income. As of 30 September 2025, our cash and cash equivalents totaled CNY 3,954.5 million, decreased from CNY 5,464.1 million as of 30 June 2025. The decrease was mainly due to our infrastructure investment for intelligent computing cloud. This quarter, our CapEx, including those financed by third parties and right of use assets obtained in 2024, financed lease liabilities were CNY 2,787.8 million. Looking forward, AI technology drives the revolution of cloud computing.
826.6 million increased, by 3.5 times of 10085.4 million in the same code last year. Our long Gap in beta 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 adjustments of business structure, structure of our costs and expenses as well as the long retirement impact of subsidy in other income.
As of September 30 2025 our cash and cash equivalent totaled. 3, 3,954.5 million decreased from 5,464.1 million. As of June, 3020 2025, the decrease was mainly due to our infrastructure investment for intelligent cloud.
Yi Li: 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 financed 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. We are now due to start a Q&A session. Please ask your question in both Mandarin, Chinese, and English if possible.
This quarter, our Capital stages, including those financed, by Third parties, and the right of use as a 10 inch 24,787.8.
Yi Li: We do more than just fulfill the computing demands of model training inference.
Looking forward AI technology drops. The revolution of cloud computing. We do more than just 4 field, the Computing demands of model training inference. We also Empower Enterprises to invoke an API and ai ai capabilities to their business.
Yi Li: We also empower enterprises to invoke an AI 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.
Step into the face 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
Nicole Shan: Thank you, Operator. We are now going 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 to start like session. Uh, please answer your question, both manager and Chinese and English if possible operator. Please go ahead. Thank you.
Yi Li: Operator, 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.
Tao Zou: 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 Beline Oshiyadan Zhang from CICC. Please go ahead. Your line is open.
Operator: 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.
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 cic. Please go ahead. Your line is open.
Xiaodan Zhang: Hey, Zhou-总, Li-总, Nicole, Clark, thanks 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's the expected mix of different computing resources acquisition models? Thank you.
Xiaodan Zhang: going forward? I will quickly translate my questions. 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, and what is the expected mix of different computing resources acquisition models? Thank you.
Hey.
Actually get something on the table to beat now.
Um, so things management for taking my questions. And first of all, what are the key drivers of a AI Revenue growth in Q3? And has there been any uh, structural change in the demand of uh your ecosystem and external clients for the past quarter?
And secondly um 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
Operator: 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.
Tao Zou: 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.
please stand by while the speakers reconnect, please stand by
Once again, please stand by while the speakers reconnect. Thank you.
Because you are now reconnected, please go ahead.
Yes uh sorry so now we we didn't get to our question. Could you repeat that again? Thank you.
Nicole Shan: Yes, sorry, Xiaodan, we didn't catch your question. Could you repeat that again? Thank you.
Yi Li: Yes, sorry, we didn't get your question. Could you repeat that again? Thank you.
Xiaodan Zhang: 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.
Xiaodan Zhang: 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.
Um, and secondly, um, how does management see the Modern Trend in the coming quarters? And uh what's the expected mix of uh different Computing, resources acquisition models uh going on with thank you.
Tao Zou: 我先回答你再补充一下。我先来回答一下，然后到时候就请刘涛补充一下。我觉得主要的增长这个因素，就是因为我们在二三季度逐步完成了之前的订单的交付或者集群的交付，然后进入到全量计费的这么一个阶段。这是一个最核心的。当然还有一部分就是从递延过来的部分递延的收入，在三季度你可以理解成一步变成全量的。可能在二季度是部分交付，部分计费，到三季度你已经全部交付，全部计费了。这是最核心的增长趋势。
Clark: 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 Q2 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's the factor of partially de-delayed revenue as well. Some of the revenue, which we had in Q2 but was not accounted for, this revenue are delayed into Q3.
Yi Li: Basically, the core reason behind the AI revenue growth in Q3 is that we had some clusters that partially delivered in 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'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 got delayed into the third quarter. Yeah.
Um, so, uh, basically, the core of the reason behind the AI Revenue growth in Q3 uh, is that we had some, uh, clusters that, you know, partially delivered in the previous quarters. Uh, for example, like the second quarter of 2025 and, uh, these clusters and these Services have only been partially accounted for, uh, rep.
News, uh, in, uh, from a from a full quarter basis. Uh, but now, in the 3 in the, in, in Q3, they are starting to be recognized as full quarter revenues. And also, there's the, um, the factor of partiality is delayed Revenue as well. Uh, some of the revenue, uh, which we had in Q2 but was not accounted for, uh, and then, uh, this Revenue are delayed into the, uh, the third quarter. Yeah.
uh, so I'm going to give you
Tao Zou: 肖丹刚才因为我们断线了，我没有听到你另外一个问题。
Xiaodan Zhang: 对，我第一个关于AI的问题，还有一个是想请教一下，就是我们看到三季度我们内外部的客户是否有，就是客户的需求是否有出现一些结构性的变化。然后我第二个问题是我们看到今年以来，因为这个算力资源获取模式的变化，虽然毛利率是有些下降的，但是我们的EBITDA利润率改善的幅度是非常超预期的。也想请周总分享一下，就是对于后续季度这个利润率趋势的一个展望，然后以及后续就是我们不同的算力资源获取的模式大概会是一个怎么样的结构和比例。谢谢。
Xiaodan Zhang: 对，那个我第一个关于AI的问题，还有一个是想请教一下，就是我们看到，三季度我们内外部的客户需求是否有出现一些结构性的变化？然后我第二个问题是我们看到，今年以来，因为这个算力资源获取模式的变化，虽然毛利率是有一些下降的，但是我们的EBITDA利润率改善的幅度是非常超预期的。这也想请周总分享一下，就是对于后续季度这个利润率趋势的一个展望，然后以及后续就是我们不同的这个算力资源获取的模式大概会是一个怎么样的结构和比例，谢谢。
1.
Tao Zou: 我先回答，等下刘涛和李怡做些补充。内外部客户需求的变化是这样啊，就是我上个季度也谈了一下，就是从这个大趋势上看，确实就是从我之前用的话术，叫做那个大客训练逐步向这个普客推理这个转变。实际上就是现在我们主要还是在训练这个建设方面，现在逐渐转是围绕几个大客去展开资源的部署吧。同时呢，我们也通过这一个Q吧，我们也明显确实是感受到了这种，这个应该说是模型真正运用到无论是工业呢，还是航运啊，这种进入到千行百业的这种趋势是越来越明显了。实际上我们在九月份也发布了新的平台，其实也是为了去迎接下一阶段的这个AI应用的到来吧。这个问题同时呢，也能够去呼应一下你刚才讲的这个毛利水平的变化。实际上在上个季度我们也谈过，随着我们的规模变大吧，可能集中在几家大客，所以呢，相较我们最早做这桩业务的这个毛利水平略有下降，所以我们也在积极地部署更高毛利的。说得更直白点，我们从目前的这个发展趋势来看，我们认为未来整个推理应用，这个毛利水平会显著高于目前的这个训练阶段。对，好不好？这是一个大的趋势，好吧。然后具体的看看刘涛、李怡有什么补充吧。
Tao Zou: 我先回答刘涛和李毅做一下补充。内外部客户需求的变化是这样，就是我上个季度也谈了一下，就是从大趋势上看，确实就是从我之前用的话术叫做大客训练逐步向普客推理转变。实际上就是现在我们主要还是在训练建设方面，现在逐渐主要是围绕几个大客去展开资源的部署。同时我们也通过这一个Q，我们也明显确实是感受到了这种应该说是模型真正应用到无论是公允还是含允，这种进入到千行百业的这种趋势是越来越明显的。实际上我们在9月份也发布了新的平台，其实也是为了去迎接下一阶段的AI应用的到来。这个问题同时也能够去呼应一下你刚才讲的毛利水平的变化。实际上在上个Q我们也谈过，随着我们的规模变大，反正集中在几家大客，所以相较我们最早做资产业务的毛利水平略有下降。所以我们也在积极的部署更高毛利的。说得更直白点，我们从目前的发展趋势来看，我们认为未来整个推理应用，这个毛利水平会显著高于目前的训练阶段。对，好吧。这是一个大的趋势，好吧。然后具体的看看刘涛、李毅有什么补充吗？
um,
you know, the the
Clark: Regarding the second part of your first question, which is about the structure of our 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 a large and top customers training demand to a general and wider spread customers inference demand. Most of 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, we have launched our StarFlow platform to meet the demands of such general trend.
Yi Li: 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. 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. In face of this general trend, we have also, as we mentioned in the prepared remarks, launched our TaoFlow Platform to meet the demands of such general trend. This also goes back to the margin question that you also asked about.
And the general Transit perspective, we're currently in the face of transitioning from a large and top customers training demand to, uh, General and writers uh, spread customers inference demand.
Clark: 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.
Yi Li: 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.
Uh, most at the current stage, we still see, uh, you know, majority of our demand coming from the larger customers in their training demand, however, especially in the uh, latest quarter. We're increasingly seeing the trend of um uh, customers adopting uh, artificial intelligence models into their diverse Industries. So, in face of this General Trend, we have also, as we mentioned, in the prepared remarks, uh, we have launched our staff flow platform, uh, to uh, meet the demands of such of such General Trends. Uh, and this also goes back to the margin question that you also uh, asked about. Uh, we generally think that the um, in the future the uh, inference demand will tend to exhibit higher margin profile than the current stage uh, of training. And therefore we we think that when that wave of demand comes, we expect to have higher margins.
Yi Li: Thank you, Shaodan. As the EBITDA level as a 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 about 20%. I have to mention that the significant quarter-on-quarter improvement this quarter was mainly driven by a 1 time other income, which will return to the normal level next quarter. Thank you, Shaodan.
Yi Li: Thank you, Chao Zhang. 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 one-time other income, which will return to the normal level next quarter. Thank you, Chao Zhang.
Can you show that I believe we have level as a proportion of the AI business continues to rise. And it cost structure is mainly dominated by depreciation. Uh, we expect these esap beta margins will be about 20%.
Uh, I have to, I have to mention that the significant quote unquote Improvement in this quarter was many driven by a 1-time other income, which will return to the normal level next quarter. Thank you, shun
Operator next question, please.
Thank you.
Nicole Shan: Operator, next question please.
Yi Li: Operator, next question, please.
Tao Zou: Thank you. Our next question comes from the line of Wenting You from CLSA. Please go ahead. Your line is open.
Operator: Thank you. Our next question comes from the line of Wenting Yu from CLSA. Please go ahead. Your line is open.
Our next question comes from the line of renting you from clsa. Please go ahead. Your line is open.
Wenting Yu: 周总、李总、Nicole Shan，晚上好，感谢给我提问的机会。我这边有两个问题想请教。那第一个是，能否请管理层分享一下明年的这个收入的指引和增速的一个预期。那在今年已经铺开的这个互联网厂商模型的后训练以及机身智能这些应用场景的基础上，那我们还预期未来在哪一些行业跟场景会出现强劲的这个算力的需求，从而去推动我们收入的进一步增长。那第二个问题是，当前我们看到国内外多家云厂商在算力资源配置里面都提高了服务器租赁的这个比例，那结合市场上采购跟租赁这两块的市场情况，那我们在性价比跟利润率的角度会怎么去考虑优化这两种方式的这个分配。那我很快分一下我的问题。The first question is, could management share the outlook and guidance on the revenue outlook for next year and beyond the Internet companies 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? The second question is: with multiple cloud providers in both China and the 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?
Xiaodan Zhang: would like to ask. The first is, could management share the outlook and guidance on the revenue outlook for the next year? Beyond the internet companies' 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? The second question is, with multiple cloud providers in both China and the US 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.
um, the first question is,
Um, good management share the Outlook and guidance on the revenue outlook for the next year and Beyond the internet conference post model training and embodied intelligence. Scenarios that 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. Um, and the second question is with multiple Club providers in both China and Us increasing the proportion of server, leasing in their Computing resource, mix and how does um management view the current market dynamics for procurement versus pleasing and from a cost Effectiveness and profit margin perspective, how would the company allocate the resources between these 2 approaches? Thank you.
Wenting Yu: From a cost effectiveness and profit margin perspective, how will the company allocate the resources between these two approaches? Thank you.
Clark: Wenty, 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 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. Regarding your second question about the procurement method, we primarily align our capital channels with actual customer needs, including cluster scale, delivery time, and 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 expands 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.
Yi Li: Wenting, thank you for your question. The company's budget process is currently underway and expected to be completed around the beginning of 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 supply inventory levels. There's 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.
Thank you for your question. The cam, the company's budget process is currently underway and expected to be completed around the beginning of the next year. Uh, we will short the specific details with you with finalized. However, regarding the demand for our AI business. We are fully confident in the subsequent demand growth.
and uh, uh, for your second question about the
Regarding the procurement method.
We primarily allow our Capital Channels with actual customer name including
Uh, cluster scale deliver time and the supply inventory levels. There's no rigid top down allocation targets from the cost. Effectiveness perspective, both approaches have their own pros and cons
Uh, the listing model is fine, our supply chain channels and provide a certain degree of flexibility in resource allocation.
Self procurement. For the other hand. Give us great autonomy in control deliver timelines and managing clusters.
Clark: Self-procurement, on the other hand, give us great autonomy in control delivery timelines and managing clusters. It also reduces the profit sharing with the suppliers, thereby elevating our pressure on profit margin. Thank you, Wenty.
The also reduce the profit sharing with suppliers there. Thereby activating, our appreciation of profit margin.
Thank you. My
Yi Li: It also reduces the profit sharing with suppliers, thereby elevating our prediction on profit margin. Thank you, Wenting.
Tao Zou: 你要不你先回答一下他们未来哪些行业。
Tao Liu: You know, as you mentioned that, you know, the robotic companies in China is growing very fast. 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 services, which is API services, we are seeing the increase of the businesses very quickly. We believe in the next year, this will be a very important factors to driving the revenue to increase. Thank you.
Tao Zou: Yeah. As you mentioned, the robotic companies in China are growing very fast. This year, we have covered most of the robotic 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, as more and more internet companies in China are using token services, which is API services, we are seeing the increase of the business very quickly. We believe in the next year, this will be a very important factor to drive the revenue to increase. Thank you.
Yeah, you know you know as you mentioned that you know the robotic companies in China is a growing very fastly. So 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. So in the next year, we believe the, uh, increase of the robot robotic companies will also be found. I mean, well, you know, as more and more internet companies in China are using talking talking talking Services, which is the API Services. Uh, we are seeing in the increasement of the business is very quickly, so we believe in the next few years. This will be a very important factors to uh driving the revenue to increase. Thank you.
What happens?
Tao Zou: 我再补充一下关于你谈到的后面那个问题。我的理解就是我们未来怎么选择是自采的服务模式还是通过服务器租赁的模式。我在上个Q基本上讲过一个总原则。我们针对我们的一些大客，包括像小米之类的，相对来讲公司现今的充裕，整个公司的发展态势非常良好的。或者简单讲就是可靠的客户，我们会采取一些自己支付开派的这种方式。但对于其他的一些可能有一定风险，或者说在整个发展的还是在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租赁的方式来提供服务。这样也是进一步降低我们自身的风险，好吧。所以当然没有一个具体的怎么样的配比，我觉得只能是更多的是从客户角度，对像小米这类客户我们觉得优质可靠的，我们就会通过自己投开派的这种方式来服务。例如一些中小的企业，我们还是会采取资源租赁的这种方式。所以这两个确实就是从我们上个Q我也谈过，对于我们总体的毛利水平会有一定的影响。但是经过今年应该说三个季度跑下来看，我觉得基本上尤其包括我们Q3的总体的毛利水平比Q2还是有一定的提升。所以我上次也谈到过，我基本上可能会保持在这么一个水平。未来主要是看我们的推理业务的进展情况。总体来讲，毛利水平有望进一步改善，好吧。
Talk.
To you woman.
Clark: This is CEO Tao Zou. He added that, he understand is 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, small and medium-sized companies, we generally tend to adopt the leasing model, which is also a way, a meaningful way to reduce our own risk.
Yi Li: This is the CEO, Zhou Tao. He added that he understands that 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 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 kind of a top-down target for the split between these two different methods.
Um, so, um, uh, this is the CEO CEO. He added that. Um, you understand that the question your second question is really about the choice between the leasing model and the capex model. Uh, so we're talking 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 profile have solid fundamentals. Um, and the trustworthy, uh, premium customers, for example, like xiaomi, we would tend to choose the capex model while in other, uh, growth stage, uh, companies, uh, medium and small size, the small and medium sized the companies. Uh, we generally tend to adopt the leasing model, uh, which is also a way, uh, meaningful.
Clark: As Li rightly mentioned, there's kind of a 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. You know, especially when you compare the gross margin for Q3 versus Q2, it actually also improves sequentially. I would say that at the current stage, we do not expect material changes to the current status.
Yi Li: We also talked about in the last quarter as well that the impact of these two different methods has 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 especially when you compare the gross 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. Generally speaking, in the future, we do expect the margin to improve. Thank you.
To reduce our own risk. Uh, so as we write write rightly mentioned, there's no. It's kind of like, top down, uh, targets. So, the split between these 2, uh, different, uh, methods. Um, and we also talked about, uh, in the last quarter as well that the impact of these 2 different methods, uh, have different impacts to, um, gross margins. However, we have seen the financial results for the past 3 quarters, uh, which we have adopted various, uh, the combinations of these 2 different models. Uh, uh, and, you know, especially when you compare the, uh, the the growth, the growth margin for the third quarter versus the second quarter. Uh it actually also uh improved, the sequentially. So um I I would say that at the current stage, we do not expect material changes, uh, to the current status. Uh, but generally speaking, uh, in the future, we do expect a margin to uh to improve.
Clark: Generally speaking, in the future, we do expect the margin to improve.
Thank you.
Nicole Shan: Thanks. The next question please, operator.
Yi Li: Thanks, Wenting. Next question, please, Operator.
Operator: Thank you. Our next question comes from the line of Timothy Zhao from Goldman Sachs. Please go ahead. Your line is open.
Tao Zou: Thank you. Our next question comes from the line of Timothy Zhao from Goldman Sachs. Please go ahead, your line is open.
Xiao from Goldman Sachs, please go ahead. Your line is open.
Timothy Zhao: Thank you, Madrone, for taking my question. My question is regarding the differences between AI training versus inferences. Could Madrone 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 these questions. 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 servers used, which is the most important factors.
Timothy Zhao: 好的，感谢关宇成接受我的提问。我的问题还是关于训练和推理的。想请教一下，我们对于整个AI训练和推理的定价方式有什么不同？过去的几个月或者是今年以来，整个的AI的服务相关的定价的价格有哪些特别的变化？我们在推理和训练的卡的利用率、价格，包括利润率上面的差别，大概是有多少？这个是我的问题。我很快翻译一下。 Thank you, Madam, for taking my question. My question is regarding the differences between AI training versus inferences. Could Madam share what is the pricing methodology between these two kinds of demand, 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.
Thank you for taking my question. My question is regarding the differences between uh, AI training versus inferences uh could imagine share. What is the pricing, uh, methodology between these 2 kinds of demand and what has been the type pricing Trend, uh, all the past few months, or year to date. And, uh, in terms of the overall utilization rate of the chips of gpus, uh, pricing and profitability, can you share more color on the Gap uh, between training and inferences? Thank you.
Tao Zou: Okay, let me answer this question. When we are talking about the price strategy for inference and training, there is not too much difference between the two things. The price is based on the qualities, how many sources you use, which is the most important factor. Also, comparing the margin rate, there are two kinds of inference services. One is customer-buy resource and use our platform to inference. That margin ratio is very similar to the training margin ratios. 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.
Tao Liu: Also, comparing, you know, the margin rate, you know, there were two kind of inference services. One is, you know, customer 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. That, we think that will have a better margin ratio. You know, this business just in the beginning, so we need time to see what is the big difference between the two things. Thank you.
Okay, let me answer this questions, you know, uh, when I talking about the price strategy uh, for influence and uh, uh, and the training, you know, there's not too much difference between 2 things. So so the the price is based on the, uh, qualities, how many, how many sources use, which is the, uh, most important factors. And also, uh, comparing uh, you know, the margin rate, uh, you know that was too. There are 2 kind of inference uh, Services which 1 is, you know, customer buy resource and use our platform to influence. So that margin ratio is very similar to the training margin ratios uh but compared but another 1 is, you know, customers still uh directly by our API token services that are we think that will have a better uh, margin ratio but you know, this business is just uh in the beginning. So we have we need time to see what what is the big difference between the 2 things? Thank you.
Yes, I think I'll catch up with you.
Thank you.
Nicole Shan: Thanks. Anything? Operator.
Yi Li: Thanks, Timothy. Operator, please.
Due to time constraints, this concludes our question and answer session so I'll hand the call back to Nicole for closing remarks.
Tao Zou: Thank you. Due to time constraints, this concludes our question and answer session. I'll hand the call back to Nicole for closing remarks.
Operator: 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 and you
Today, if you have any questions, feel free to contact us look forward to speaking with you again, next quarter. Next
Nicole Shan: Thank you. Thank you all once again for joining us today. If you have any questions, feel free to come have at it. Look forward to speaking with you again next quarter. Have a nice day. Bye-bye.
Yi Li: 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.
Say bye. Bye.