Kingsoft Cloud Holdings Limited American Depositary Shares 2026 Q2 Earnings Call

Hello everyone, and thank you for joining us today. Kingsoft Cloud's second quarter 2026 earnings release was issued earlier today, and is available on our IR website and through PR Newswire. Joining us today are Mr. Zou Tao, Chairman and CEO, Ms. Li Yi, CFO, Mr. Liu Tao, Senior Vice President, Mr. Tian Kaiyan, Senior Vice President, Ms. Yu Jun, Vice President, Mr. Zhou Ruilong, Associate Vice President, and Mr. Kwok Chen, Board Secretary and Associate Vice President. Mr. Zou will discuss our business performance and key developments, followed by Ms. Li with a review of our financial results. Management will then take your questions. Consecutive interpretation will be provided for convenience and for reference only. In the event of any discrepancy, management's statements in the original language will prevail.

Before we begin, I would like to remind you that today's call contains forward-looking statements made under the safe harbor provisions of the U.S. Private Securities Litigation Reform Act of 1995. These statements involve risks and uncertainties, and actual results may differ materially from those expressed or implied by the forward-looking statements. Additional information concerning factors that would cause actual results to differ materially is included in the company's filing with the U.S. SEC. The company undertakes no obligation to update any forward-looking statements except as required by applicable law. Unless otherwise stated, all financial figures discussed on today's call are denominated in CNY. With that, it is my pleasure to turn the call over to our Chairman and CEO, Mr. Zou. Mr. Zou, please go ahead.

大家好，欢迎参加金山云2026年第二季度业绩电话会。我是金山云CEO周涛。本季度我们看到了AI云业务形态的进一步演进，开源大模型生态的空前繁荣，给公有云厂商带来巨大的发展空间。而我们几年来一直坚信的AI落地千行百业，正以模型即服务、智能体即服务和FDE相结合的形式向我们走来。面对这一深刻的行业变革，金山云继续坚持技术立业与高质量可持续发展战略，全面推动AI云服务、MaaS业务、FDE业务的发展，取得了可喜的成绩。首先，AI业务继续驱动公司收入高速增长，本季度实现总收入30.7亿元，创单季度历史新高，同比增长31%。其中AI云账单收入达13.3亿元，同比增长82%，占公有云收入比例进一步提升至56%。MaaS业务收入增长强劲，二季度MaaS收入较一季度增长12倍。其次，盈利水平显著提升。本季度经调整毛利率提升至15.4%，环比上升2.4个百分点。经营利润首次转正，经调整经营利润率达4%，创历史新高。这是我们抓住AI浪潮，提升收入质量，落实降本增效等多项举措并行所取得的可喜成果。第三，客户结构持续优化，生态内外商机加速兑现。生态内，本季度来自小米和金山生态的收入达8.1亿元，同比增长28%，占总收入比例为26%。生态外，前五大客户收入同比增长51%。AI云业务已覆盖互联网、前沿AI实验室、汽车智能、自动驾驶、AI for Science、金融科技、游戏、音视频等广泛行业。多元化的客户结构与业务布局，不仅带来收入规模的持续提升，也使我们能够更灵活地调配算力资源，提升议价能力和抗风险能力。 Hello everyone, and welcome to Kingsoft Cloud's second quarter 2026 earnings call.

I am Zou Tao, CEO of Kingsoft Cloud. This quarter, we saw further evolution in the AI cloud market. The rapid growth of the open source model ecosystem is creating significant opportunities for neutral cloud providers. At the same time, our long-held vision of bringing AI to every industry is becoming a reality through a combination of Model-as-a-Service, Agent-as-a-Service, and FDE services. Against this backdrop, Kingsoft Cloud remains committed to technology leadership and high-quality, sustainable growth.

We are accelerating the development of our AI cloud, MaaS and FDE businesses with encouraging progress. First, AI continues to drive strong revenue growth. Total revenue reached a record of CNY 3.07 billion, up 31% year-over-year. AI cloud gross billings increased 82% to CNY 1.33 billion and accounted for 56% of public cloud revenue. MaaS revenue also grows strongly, with Q2 revenue up more than 12 times from the Q1 level. Second, profitability improved significantly. Adjusted gross margin rose to 15.4%, up 2.4 percentage points quarter-over-quarter. Operating profit turned positive for the first time, with adjusted operating margin reaching a record high of 4.0%. This reflects our continued efforts to capture AI opportunities, improve revenue quality and drive greater operating efficiency. Third, our customer mix continued to improve with stronger momentum both within and outside our ecosystem.

Revenue from the Xiaomi and Kingsoft ecosystem reached CNY 810 million, up 28% year-over-year and accounting for 26% of total revenue. Revenue from our top five non-ecosystem customers grew 51%. Our AI cloud business now serves a broad range of sectors, including internet services, Frontier AI Labs, embodied AI, autonomous driving, AI for Science, Fintech, gaming, and online video, to name a few. This diversified customer base supports continued growth while allowing us to allocate computing resources more flexibly and strengthen our pricing power and business resilience.

下面我向大家具体介绍2026年第二季度的业务进展。公有云方面，本季度实现收入23.6亿元，同比大幅增长45%。首先，小米AI全面赋能人车家全生态。金山WPS AI业务推进作为小米金山生态的唯一战略云平台，AI时代所带来的云服务业务增长潜力空前庞大。2026年6月，股东大会正式批准了我们再次提升来自小米关联收入的上限金额。2026年和2027年来自小米关联收入上限合计达100亿元，较上调前提升了39%。今年上半年来，自小米和金山的公有云收入同比增速达54%。其次，星流平台MaaS服务能力进一步强化。星流模型API服务持续完善多模型服务与企业级接入能力。目前星流平台已部署上线120款模型，主流新模型推出后做到同步上线，已接入230多家客户。第三，我们在新兴赛道深化与头部客户合作，面向头部具身智能客户和头部自动驾驶客户，完成大规模算力集群交付，稳定支撑其模型高效迭代。与AI for Science行业头部客户达成深度合作，保障其新业务快速拓展。 Now let me walk you through our business progress in the second quarter of 2026.

In public cloud, revenue reached CNY 2.36 billion, up 45% year-over-year. First, Xiaomi continues to expand AI across its human car home ecosystem. WPS AI continues to advance. As the only strategic cloud platform for the Xiaomi and Kingsoft ecosystem, we see substantial AI driven growth opportunities. In June, our shareholders approved a further increase in the annual caps for connected transactions with Xiaomi. The combined caps for 2026 and 2027 now total CNY 10 billion, 39% higher than before the adjustment. In the first half, public cloud revenue from Xiaomi and Kingsoft grew 54% year-over-year. Second, we further strengthened the MaaS capabilities of our StarFlow platform.

StarFlow now supports 120 models, with major new models launched on the platform in sync with their market release, and serves more than 230 enterprise customers. Third, we deepened cooperation with leading customers in emerging sectors. We delivered large scale computing clusters to leading embodied AI and autonomous driving customers, supporting rapid model iteration and expanded our cooperation with the leading AI for Science customers to support the growth of its new business.

航运云方面，本季度实现收入7.1亿元。公共服务领域，我们与长江南京通信管理局签约打造江海云，共同打造适配长江航运需求的专属数字化底座。我们还与武汉市数据局、武汉云达成战略合作，在算力网、数字政府、智能算力应用、产业生态打造等领域展开合作，夯实武汉数字政府与产业生态底座。数字健康领域，我们牵头国家重点研发计划生物与信息融合专项，打造云端一体化医学虚拟手术平台，成果已在全国30多家医院应用，树立了云厂商牵头医工信交叉国家级科研攻关的行业标杆。企业服务领域，我们与云上甘肃达成深度合作，以投建运一体化模式，共同建设并运营甘肃省级政务平台。 In enterprise cloud, revenue reached RMB 710 million.

In public services, we signed an agreement with the Nanjing Communications Administration of the Yangtze River to build Jianghai Cloud, a dedicated digital infrastructure platform for Yangtze River shipping. We also formed a strategic partnership with the Wuhan Municipal Data Bureau and Wuhan Cloud across computing resource interconnection, digital government, intelligent computing applications, and ecosystem development. In digital health, we are leading a project under the National Key R&D Program on Biology and Information Integration to develop a cloud-based virtual surgery platform, which has been deployed in more than 30 hospitals nationwide. In enterprise services, we deepened our cooperation with Yun Shang Gansu to jointly build and operate the Gansu Provincial Public Services Cloud under an integrated investment, construction, and operations model.

在产品技术方面，我们紧密围绕智算落地与AI应用的需求，升级全栈AI能力。本季度，星流MaaS平台围绕高并发推理需求，持续进行模型部署优化，多个核心模型吞吐能力显著提升，并支持按权限、用量与模型维度进行精细化管理。我们正式发布星元Agent Kit平台，提供涵盖安全沙箱、知识与记忆，及评测治理的全套底座，帮助企业快速搭建生产级AI agents应用。同时，我们将云产品周边AI化，将数据库、存储等组件变成为Agent可便捷调用的平台型产品。我们优化了星流训推平台，提升资源调度灵活性，围绕训练与微调场景，新增了物理队列、资源借用与回收，以及资源算力的灵活配置能力，极大地提升了多任务并发下的资源利用率，降低了研发团队的训练环境门槛与运营成本。面向私有化与国产化智算需求，银河平台完成了多款主流国产算力芯片的深度适配及全生命周期的可视化管理。 In products and technology, we continued to upgrade our full stack AI capabilities for intelligent computing and AI application deployment.

This quarter, we further optimized the model deployment on StarFlow MaaS for high concurrency inference, significantly improving throughput for several core models, and enabling more granular access, usage, and model-level management. We also launched AgentKit, providing secure sandbox, knowledge and memory management, and evaluation and governance tools to help enterprises build production-grade AI agents. At the same time, we are making general purpose cloud products such as database and storage easier for agents to access and use. We enhanced the StarFlow training and inference platform with more flexible resource scheduling, sharing, and allocation for training and fine-tuning workloads, improving utilization and reducing development and operating costs.