Kingsoft Cloud Hldgs Q2 2026 Earnings Call: Complete Trans...

Kingsoft Cloud Hldgs (NASDAQ:KC) reported second-quarter financial results on Wednesday. The transcript from the company's second-quarter earnings call has been provided below.

This transcript is brought to you by Benzinga APIs. For real-time access to our entire catalog, please visit https://www.benzinga.com/apis/ for a consultation.

View the webcast at https://edge.media-server.com/mmc/p/tdddqknk/

Summary

Kingsoft Cloud Holdings reported a record total revenue of RMB 3.07 billion for Q2 2026, marking a 31% year-over-year increase, driven by strong AI cloud growth.

The company's adjusted gross margin improved to 15.4%, and it achieved a positive operating profit for the first time, with an adjusted operating margin of 4.0%.

Public cloud revenue grew 45% year-over-year, bolstered by increased demand from Xiaomi and Kingsoft ecosystems, while enterprise cloud revenue saw a slight year-on-year decline.

Kingsoft Cloud is focusing on AI cloud market evolution, strengthening its AI cloud, Model as a Service (MAS), and FTE businesses, and expanding its customer base across diverse sectors.

The company plans continued investment in AI infrastructure, with 2026 full-year CAPEX expected to remain in line with previous guidance, amidst ongoing supply challenges in chip procurement.

Management highlighted a strategic focus on maintaining neutrality in the AI cloud market, allowing them to cater to diverse customer preferences for AI models.

Looking ahead, Kingsoft Cloud aims to capitalize on AI demand growth, optimize business structures, improve capital efficiency, and enhance profitability and cash generation capabilities.

Full Transcript

Good morning ladies and gentlemen and thank you for standing by for Kingsoft Cloud's second quarter 2026 earnings conference call. All participants are currently in listen only mode. Following Management's prepared remarks, we will open the call for questions. Please note that today's call is being recorded. I will now turn the call over to Mr. Jackie Zor, senior director of capital markets at Kingsoft. Clyde Jackie, please go ahead.

Thank you. Operator hello everyone and thank you for joining us today. Kingsoft Cloud's second quarter 2026 earnings release was issued earlier today and is available on our IR website and through PR Newswire. Joining us today are Mr. Zhou Tao, Chairman and CEO Ms. Li Yi, CFO Mr. Liu Tao, Senior Vice President, Mr. Tian Kai Yan, Senior Vice President, Ms. Yu Jun, Vice President, Mr. Zhou Railong, Associate Vice President and Mr. Clark Tian, Boss, Secretary and Associate Vice President. Mr. So will discuss our business performance and key developments, followed by Ms. Lee 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 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 U.S. private Securities Litigation Reform act of Magnet 5. These statements involve risks and uncertainties and actual results may differ materially from those expressed or 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 US 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 denominated in renminbi. With that, it is my pleasure to turn the call over to our chairman and CEO Mr. Zhou. Mr. Zhou, please go ahead. Which.

You go the lamp as you fight that journey.

San go. Jinging. Bang.

Hello everyone and welcome to Kingsoft Cloud second quarter 2026 earnings call. I am Zhou Tao, CEO of Kingsoft CL. 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, Kingcoft Cloud remains committed to technology, leadership and high quality sustainable growth. We are accelerating the development of our AI cloud maps and FTE businesses with encouraging progress. First AI continues to drive strong revenue growth.

Total revenue reached a record of RMB 3.07 billion, up 31% year over year. AI cloud gross billings increased 82% to RMB 1.33 billion and accounted for 56% of public cloud revenue. MAS 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 XionGN Kingsoft ecosystem reached R&D 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. kung tianga Now let me walk you through our business progress in the second quarter of 2026 in public cloud revenue reached RMB 2.36 billion, up 45% year over year. First, Xiaomi continues to expand AI across its human car home ecosystem while WPS AI continues to advance as the only strategic cloud platform for the Xiaomi and Kingstop ecosystem. We see substantial AI driven growth opportunities.

In June, our shareholders approved a further increase in the annual caps to connected transactions with Xiaomi. The combined caps for 2026 and 2027 now total RMB10 billion, 39% higher than before the adjustments in the first half. Public cloud revenue from Xiaomi and Kingsoft grew 54% year over year. Second, we further strengthened the MAP 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 customer to support the growth of this new business.

Nanjing tung jin hai. Bingwa su.

In Enterprise cloud revenue reached RMB710 million in public services, we signed an agreement with the Nanjing Communications Administration of the Yangtze river to build Yanghai 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 and 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 Yunshang Gansu to jointly build and operate the Gansu Provincial Public Services Cloud under an integrated investment, construction and operations model. Shungji chanda.

Where are.

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 stopload maps for high concurrency inference, significantly improving throughput for several core models and enabling more granular access, usage and model level management. We also launched Agent Kit providing secure sandbox knowledge and memory management and evaluation and governance tools to help enterprises build production grade AI agents. At the same time, we are making general purpose cloud products such as database and storage easier for agents to access and use.

We enhanced the starflow training and inference platform with more flexible resource scheduling, sharing and allocation for training and fine tuning workloads, improving utilization and reducing development and operating costs for private deployment of the MASTIC AI infrastructure. Our Galaxy Stack platform completed deep integration and full lifecycle visual management for multiple mainstream domestic AI chips. Looking ahead, we will continue to capture opportunities both within and outside our ecosystem, improve the operating efficiency of our computing assets and strengthen our profitability and cash generation capability. Amid AI industry tailwinds. We remain committed to creating long term sustainable value for customers, shareholders and society. With that, I will hand the call over to our CFO Li Yi who will review our second quarter financial results.

Thank you, thank you Mr. Zhou and Mr. Tian and thank you all for joining the call today. I will now discuss the second quarter financial results used as fee as currency before we walk through details the financial results for the second quarter, I would like to highlight the following items. First, our quarter revenue reached over 3 billion for the first time in our company history up year over year. For the last consecutive quarter. In particular, our AI Cloud growth billing increased 82% year over year to 1.33 billion, accounting for over 43% of our total revenue Earth 31% a year ago. This reflects a continued structural shift in our business needs towards AI Second, our profitability has improved.

Our adjusted Gross margin was 15.4%, up 2.4 percentage points quarter of quarter at 0.5 percentage points year over year, our adjusted EBITDA margin reached 36%, up from 70% in the same quarter last year and 82% last quarter. Notably, we returned to break even at operating income level this quarter and recorded an adjusted operating profit margin of 4%. These outcomes validate our ability to turn strong AI business demand into healthy profit growth.

Third, we continue to invest to accelerate the build out of our AI compute capacity. Capital expenditures together with right of use assets obtained through third party financing and finance leases reached $3.3 billion this quarter versus $2.9 billion in last quarter and $2.8 billion in the same quarter last year. Now let us walk you through our financial results for the second quarter of 2026 this quarter. Total revenue were $3,072 million, up 31% year over year or 40% quarter over quarter of these revenues from public cloud services were 2,358 billion, up 45% from 1,625 million in the same quarter last year. Revenues from Enterprise cloud services reached 740 million compared with 724 million in the same quarter last year, down slightly by 1% year on year.

Total cost revenues was 3,606 million, representing a 30% year over year increase mainly due to a continued investment in AI cloud infrastructure. IDC costs increased by 23% year over year from 803 million to 1,190 million this quarter. The increase was mainly due to the increase of RAC services. Depreciation and amortization costs increased by 75% year over year from 552 million in the same quarter of 2025 to 964 million this quarter, largely due to the depreciation of newly acquired and raised air infrastructure including servers and network equipment. Solution development and service costs increased by 4% year over year from 564 million in the same quarter of 2025 to 586 within this quarter.

The modest increase was mainly due to higher costs incurred in AI transformation in solution development and delivery. Formulated cost and other costs were approximately 66 minutes in total this quarter versus 92 million in the same quarter last year. Our adjusted gross profit for the quarter was 472 million, increased by 35% year over year and 34% quarter over quarter. Adjusted gross margin was 15.4%, up from 14.9% in the same quarter last year and from 13% last quarter. The increase was driven by higher gross margin in public cloud business thanks to strong AI demand tailwind on the expense side.

Excluding share based compensation cost expenses, our total adjusted operating expense were 391 million, a decrease from 561 million in the same quarter last year and from $455 million last quarter, many reflecting our disciplined cost and expense control of which our adjusted research and development expenses were 184 million, up 1% year over year. Adjusted selling and market expenses were 102 million, down 7% year over. Adjusted general and administrative expenses were 105 million, down 61% year over year, largely due to lower credit loss expenses. Our adjusted operating profit was 124 million, totally profit from adjusted operating loss of 166 million in the same period last year. This improvement was primarily driven by the expansion of our revenue sales, higher gross margin and enhanced operating efficiency.

Adjusted operating profit margin was 4% this quarter compared with minus 7.1% in the same period last year and minus 2.2% last quarter. Our adjusted net loss was 6, down from 300 million in the same quarter last year and 237 million in previous quarters. Our non GAAP EBITDA profit was 1,100 million increased by 171% from 406 million in the same quarter last year. Our non GAAP EBITDA margin achieved 36% compared with 70% in the same quarter last year and 82% last quarter. It was mainly due to our improving gross profit as well as higher duration costs in our core debt as we accelerate our AI computing capacity build out. As of June 30, 2026, our cash and cash equivalent countered 4,674 million compared with 4,904 million as of March 31, 2026.

The modest decrease was mainly due to our continued investment in AI infrastructure to support business growth. Looking ahead, we aim to capitalize on the exclusive growth in air demand by further investing in infrastructure, expanding our product and service offerings, managing credit and liquidity risk and improving operating efficiency. We remain commitment to our core in AI strategy and continue to deliver high quality growth to our shareholders.

Thank you all.

So this concludes our prepared remarks. We will now begin the Q and A session. If possible, please ask your questions in both Mandarin and English. So operator, please proceed.

Thank you. We will now begin the question and answer session. If you wish to ask a question, you will need to press Star 11 on your telephone and wait for your name to be announced to withdraw your Question, please press Star one one. Again, we will take our first question. Your first question comes from Lipping Zhao from cicc. Please go ahead. Your line is open.

Let me translate by myself. So, good evening Ms. Zhou and Ms. Lee. Thanks for taking my questions. I got two questions on your MAS business. First, how will improvements in open source model capabilities affect the company's MAS business? Based on your observations, what's the current usage growth trend and which use cases are driving it most? And second, given the payback period for the MAS business might be shorter. Will the company allocate more resources to it? Thank you.

Hanoki samba. Okay, so just to quickly translate. So this answer comes from our SVP, Mr. Lyota. So in relation to your first question, the development in open source large language models has mainly three impacts. Number one is that we're seeing very big demand coming from bytecode and traditionally foreign models have been taking the lead in this area. However, once we have seen the launch of GLM and K3, these kind of high performance models, we're seeing increasingly users from mainland China adopting and using this made in China large language model. And secondly, the increasing use of Agentix scenarios also brought change to our business and with that we have launched, as mentioned in the prepared remarks, the Agent Kit product to satisfy such needs.

And thirdly, it is worth mentioning that in terms of day to day routine tasks and workloads, the choice usually is the price for value kind of models which are essentially the Chinese models. So that is why this development open source large language model is actually beneficial for our business. And your second question regarding the balance between math business and the computing power. So we basically have different business models for this two business for computing power business, essentially once we sell the computing power, the utilization is by nature 100% compared to and we usually come with long term contracts to secure the utilization throughout a prolonged period of time and therefore it's relatively safe, so to speak.

But for the mass business it is subject to quite a few factors including the fluctuation of the token price, the launching of new models which the customers might prefer to use, and also the operating efficiency that we're able to achieve in doing a mass business. So therefore we generally balance these two business models and hope to have each one of them complement the other one. So we generally dynamically evaluate these two businesses and try to decide how much resources to allocate. Thank you.

Thank you Thaozon, that's very helpful.

We will take our next question. Next question comes from Wencheng Vu from CISA Please go ahead. Your line is open.

The first question is that since June, how has the chip procurement progressed in recent months and what's your latest full year capex guidance? And the second question is about the enterprise cloud. This segment of revenue has decelerated in

the past two quarters.

How should we think about the full year enterprise cloud growth? And what's the AI transformation and medium term positioning for this segment? Thank you.

So you know,

take. So allow me to quickly translate. So the answer comes from our SAP, Mr. Tian Taiyan. So three points. Number one, actually since 2023 it's been three years and the market has always been hearing voices about the, you know, the limited supply. So I would say this is actually a new norm. The supply difficulty is actually a long term kind of situation. But secondly, we should also be aware of the that despite of those constraints, financial constraints, the Chinese cloud computing or AI industry development has not been restricted or largely restricted by that.

And the way that we actually tackle with such situation is that we try to increase the number of business partners that we work with, we try to increase the number of suppliers we work with and we also work with the increasing the compatibility of made in China chips. You are all very well, very much aware of the, you know, recently many of the made in China chips are becoming public and they are particularly good in use cases such as model inference.

Now number three, I would like to say that when you look at the CAPEX number from a month to month basis it is usually quite volatile and I have to say that the purchasing number because of it's usually a large chunk of money in relatively small number of purchases. So the purchasing number, if you look at it by monthly basis, it's actually not a linear number. So I would say that for our whole year capex estimate it should still be in line with what we have been expecting and our CFO should be able to give you more details in that regard.

Hi Qingqing. Our CapEx venture include capitalized assets through lease arrangement reaching 6.2 billion in the first half of 2026 accounting for over 75% of our full year CAPEX last year where July's data cannot fully represent third quarters of all trade in it clearly shows tangible growth acceleration. Accordingly we maintain our 4 year CapEx base case unchanged at 15 billion. Thank you Ting Ting. Thanks Tington.

Thank you. We will take our next question.

Oh, sorry, we have. We need to continue for another question.

Apologies.

Okay. Nature. Yeah. Woman through dong qi jian shao bao.

Okay, so this answer comes from Our Lady, Ms. Yujun. So generally I don't think, although we are seeing relatively slow growth in the enterprise cloud segment, I would say it is not the right way to look at it from a linear extrapolation perspective. I would give you three reasons. I think number one, just to explain why we're looking at relative weakness in this regard is that the upstream supply pricing hiking hike which changed quite significantly in recent quarters has affected our prospective customers. Essentially the SOE companies and also the government agencies, they have to frequently adjust their budgeting quota which delays their decision making process. So that's number one.

And number two, you're all quite aware that the seasonality in enterprise cloud business is quite strong. Usually the delivery and the revenue recognition are concentrated in the second half of every year. So we have actually quite a strong pipeline to deliver in the second half of the year. And thirdly, this is actually a result of a proactive adjustment of our business structure, namely proactively from the project based business model to operating based business model where operating business model from a financial reporting perspective is automatically classified into public cloud. So this is not simply as it was as a weakening of the enterprise cloud business. So that's the three points I would like to offer. Thank you.

That's helpful. Thank you.

Thank you. We will take our next question. Your question comes from Timothy Zhao from Goldman Sachs.

Please go ahead.

Your line is open.

Now. Thank you madam for taking my question. My first question is regarding the mass banish. Just wondering compared to the peers in the market, how do you think about the Kingston Cloud competitive advantage in a MAS services in terms of the application scenarios et cetera. And could you share more about the revenue recognition and the profitability profile of the MAAS service business? Second question is regarding the overall pricing trend in the AI cloud business. Just wondering if you can share what is the latest trend over the past couple months and what have you heard from from the customers after you announced certain price hikes or discount reduction over the past few months and whether you are able to quantify the impact from the price hike to your overall AI cloud revenue growth. Thank you.

And. Talking.

So in relation to your question about the positioning we have, we do have a unique positioning in the MAS business. Namely we're different from some of the full stack cloud providers which they have their in house or proprietary models. We do not have such models and therefore correspondingly we do not have to sell those large language models that our affiliated companies have to offer and as a result we're able to actually sell and we actually Encourage our sales team to sell the models that our customers like the most, for example the glm, et cetera. So that's number one.

And secondly, it's quite important in today's market to have your proprietor or your own computing power, which is the only way that you can actually secure significant profitability in this business. 20. Four man doing. So in relation to your question about the price hack. So there are basically two products or solutions that we have employed increasing price, number one, that is storage and number two, that is computing power. So I'll talk about them separately respectively in terms of storage. Storage is usually the incremental amount of storage. It actually comes with the intelligent computing demand that is relatively small portion of the intelligent computing overall ticket size. And therefore in the vast majority of the customers that we negotiated with, they relatively easily accepted such a price hike.

In which case as a result we're actually able to not only in some cases, not only pass through the increase in our cost, but also increasing our

profitability

in that scenario. Number two, in terms of computing power, because of our specific capabilities, including pack capabilities as well as the operating, maintenance and network capabilities, again we are able to pass through that cost hike into our customers. In some of the cases we also increased our profitability and in this quarter we have also some projects which we are doing managed services, which is an Atlante business model. We look forward to seeing more of that coming to reflect in the financial statement.

Thank you.

Thank you. We will take the next question. Your next question comes from Wei Xiong from ubs. Please go ahead, your line is open.

Good evening management. Congrats on a solid quarter and thank you for taking my question. Considering the proprietary models and user ecosystem of other cloud providers, how should we think about our long term positioning in the cloud market and the sustainable margin level down the road? Thank you.

Number two in the Zomi Chan channel. So we believe that MAS or AI cloud service provider is important to be able to offer the top models which the customers like and also stable services to our customers. So as mentioned, as a neutral cloud layer, we are able to be in good relations with all of the top model providers or large language model labs and be able to provide the best model according to our customers demands. And also we're able to, based on our technology capabilities, we're able to provide highly available and highly reliable services to them based off out of the SLA that we signed with them. I think thirdly in relation to the profitability question you asked, it is important to work closely with the LLM firms labs to for example to optimize to optimize the inference of those models.

And that would include the for example working with them based on the undisclosed weighting of the of the models to increase our inference model inference efficiency. In some of the cases we're able to get to very close level or even reach the same level of the inference efficiency coming out from the LLM companies themselves. Thank you.

Thank you. We will take our final question. Your final question comes from Ying Liu from Morgan Stanley. Please go ahead. Your line is open.

Let me translate my question. I would like to ask under the two business model Computing Power Leasing and model as a service, what is ROIC for these two business models and what is the marginal change for the roic? Thank you.

Thank you. Lu Yang at this stage we don't disclose Separate OSC on MaaS and AI computing power services because LISD varies across projects driven by feedback cycles, gross margin, fixed assets and depreciation policies overall must be with much better probability than AI Computing Power Services. At this stage, we have seen continued improvement in operating leverage as our AI business scales up, fixed costs are steadily diluted and our trailing trail, Martha's adjusted operating profit, has turned positive, driving a gradual recovery in our overall roic. We adhere to a demand driven and disciplined air investment strategy with a strong focus on capital efficiency.

With the continuous business structure optimization and maturing AI commercialization, I think our overall LSE will keep improving steadily.

Okay, thank you.

Thank you. There are no further questions. Apologies. The question and answer session I will hand back for closing remarks.

Okay, thank you all for joining us today. If you have any further questions, please contact our IR team. So have a good evening. You may now disconnect. Thank you.

This concludes today's conference call. Thank you for participating. You may now disconnect.

Disclaimer: This transcript is provided for informational purposes only. While we strive for accuracy, there may be errors or omissions in this automated transcription. For official company statements and financial information, please refer to the company's SEC filings and official press releases. Corporate participants' and analysts' statements reflect their views as of the date of this call and are subject to change without notice.

Kingsoft Cloud Hldgs Q2 2026 Earnings Call: Complete Transcript

Summary

Full Transcript