キングソフト・クラウド（KC）2026年第2四半期決算説明会：AI売上高の増加が初の調整後営業利益を牽引

キングソフト・クラウド（NASDAQ: KC）は、AIクラウド需要の加速に伴い四半期売上高が過去最高を記録し、調整後営業利益が初めて黒字化に転じたと発表した。経営陣はまた、AI計算能力の拡張を継続する一方で、通期の設備投資（CapEx）のベースシナリオを維持した。

主要なポイント

• 2026年第2四半期の売上高は、AIクラウド需要に牽引され、前年同期比31%増の30億7000万人民元と過去最高を記録した。
• AIクラウドの総請求額（グロスビリング）は前年同期比82%増の13億3000万人民元に達した。これはパブリッククラウド売上高の56%、総売上高の43%以上を占めた。
• 調整後粗利益率は15.4%となり、前四半期比で2.4ポイント、前年同期比で0.5ポイント上昇した。
• 調整後営業利益は1億2400万人民元に達し、利益率は過去最高の4.0%を記録した。同社が調整後営業黒字を達成したのはこれが初となる。
• パブリッククラウド売上高は前年同期比45%増の23億6000万人民元となった。MaaS売上高は2026年第1四半期から12倍以上に増加した。
• 設備投資、使用権資産、ファイナンス・リースを含むAIインフラ投資額は、当四半期中に33億人民元に達した。

主要財務データ

事業および営業業績

AIクラウドは引き続きキングソフト・クラウドの最大の成長エンジンとなった。同社によると、AIクラウドの顧客基盤は現在、インターネットサービス、AI研究所、エンボディードAI（身体性AI）、自動運転、AI for Science、フィンテック、ゲーム、オンライン動画など多岐にわたる。経営陣は、この多様化により計算リソースのより柔軟な配分と価格支配力の強化が支えられていると述べた。

シャオミ（Xiaomi）およびキングソフト（金山）のエコシステムからの売上高は前年同期比28%増の8億1000万人民元に達し、総売上高の26%を占めた。上半期における同エコシステムからのパブリッククラウド売上高は54%増加した。株主はまた、シャオミとの継続的関連当事者取引の上限額引き上げを承認し、2026年と2027年の合計上限額は100億人民元となった。

キングソフト・クラウドのMaaSプラットフォームは120のモデルに対応し、230社以上の企業顧客にサービスを提供した。経営陣は、このビジネスの急成長の背景として、高性能な中国産オープンソースモデルの普及拡大とエージェント型ユースケースの拡大を挙げている。

同社はまた、安全なサンドボックス環境、ナレッジ・メモリ管理、評価およびガバナンスをカバーするAgentキットを立ち上げた。さらに学習・推論プラットフォームをアップグレードし、リソースのスケジューリング、利用率、モデルデプロイメントの効率を向上させた。

エンタープライズクラウドの売上高は7億1000万人民元に達した。経営陣は、納品および収益認識が通常下半期に集中するため、直近の成長を直線的に引き延ばして見るべきではないと述べた。また同社は、プロジェクト型の案件の一部を運用型モデルへと移行しており、これらはパブリッククラウド売上高に分類される可能性がある。

経営陣の見通し

経営陣は通期の設備投資（CapEx）のベースシナリオを維持した。使用権資産およびファイナンス・リースを含む2026年上半期の投資額は62億人民元に達し、これは比較対象となる2025年通期の同投資指標の75%以上に相当する。

同社は、計算資産の利用率、収益性、キャッシュ創出能力を向上させながら、AIインフラへの投資を継続する計画である。経営陣は、投資判断は引き続き需要主導であり、資本効率に重点を置くことを強調した。

リスクおよび注視すべき点

• 経営陣は、AIチップ供給の制約を業界の長期的な条件と位置付けた。キングソフト・クラウドは、サプライヤーの多様化と国産チップとの互換性向上によってこれに対応している。
• MaaSの採算性（経済性）は、トークン価格、新しいモデルの投入、顧客のモデル選好、運用効率によって変動する可能性がある。
• エンタープライズクラウドのプロジェクトのタイミングは、特に国有企業や政府機関などの顧客による予算編成の変更の影響を受けやすい。
• AIインフラの調達は比較的少数の大規模プロジェクトに集中しているため、月次および四半期の設備投資額（CapEx）は変動しやすくなる可能性がある。
• 継続的なAIキャパシティの拡張は減価償却費の増加を招くため、投下資本利益率（ROIC）を維持するには持続的な稼働率が必要となる。

アナリストQ&Aの要点

経営陣は、計算力サービスとMaaSではリスク・リターン特性が異なると述べた。計算力契約は一般に長期契約を通じて高い稼働率の予見可能性を提供する一方、MaaSはより高い収益性を提供し得るものの、トークン価格、モデルの変更、運用効率の影響を受けやすい。そのため、リソース配分は両モデル間で動的に調整される。

競合上の優位性について、経営陣は、自社で優先すべき独自モデルを持たない中立的なクラウドプロバイダーとしてのキングソフト・クラウドの役割を強調した。同社は顧客の好みに応じたモデルを提供しつつ、自社の計算能力とインフラ能力を活用して利益率とサービスの信頼性を維持することができる。

価格設定に関して、経営陣はストレージおよび計算力サービスの値上げが顧客におおむね受け入れられていると述べた。一部のケースでは、上昇したコストを転嫁するだけでなく、収益性を向上させることもできた。同社はまた、よりアセットライトなマネージドサービスプロジェクトを追求している。

経営陣は、リターンがプロジェクト、回収の確実性、利益率、固定資産、減価償却方針によって異なるため、MaaSと計算力サービスの個別のROIC数値を提供しなかった。それでも、営業レバレッジの向上と固定費の希薄化に伴い、全体的なROICは緩やかに回復していると述べた。

決算説明会文字起こし全文

決算説明会の完全なトランスクリプト

経営陣による説明

Operator

Good morning, ladies and gentlemen, and thank you for standing by for Kingsoft Cloud's Second Quarter 2026 Earnings Conference Call. [Operator Instructions] Please note that today's call is being recorded. I will now turn the call over to Mr. Jackie Zou, Senior Director of Capital Markets at Kingsoft Cloud. Jackie, please go ahead.

Unknown Executive

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 DuoReswire. Joining us today are Ms. Zou Tao, Chairman and CEO; Ms. Yi Li, CFO, Mr. Liu Tao, Senior Vice President; Mr. Ken Kayan, Senior Vice President; Mr. Yu Jung, Vice President Mr. Joe Rio, Batumi Vice President; and Mr. Clark Ken, 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 APs prudency, 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 tax of [indiscernible]. 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 could cause actual results to differ materially is included in the company's filings with the U.S. SEC. The company undertakes no obligation to update any forward-looking statements, except as required by [indiscernible] Unless otherwise stated, all financial figures discussed on today's call are denominated in renminbi.

With that, it is my pleasure to turn the call over to our Chairman and CEO, Mr. Zou. Mr. Zou, please go ahead.

Tao Zou

[Interpreted]

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 mission of bringing AI to every industry becoming a reality through a combination of model as service, agent as service and FTE 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 mass 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.

Mass revenue also rose strongly with Q2 revenue up more than 12x from the Q1 level. Second, profitability improved significantly. Adjusted gross margin rose to 15.4%, up 2.4 percentage points quarter-over-quarter. Operating profit turned positive for the first time with adjusted operating margin reaching a record high of 4.0%. This reflects our continued efforts to capture AI opportunities, improve revenue quality and drive greater operating efficiency.

Third, our customer mix continued to improve with stronger momentum both within and outside our ecosystem. Revenue from the [indiscernible] Kingsoft ecosystem reached RMB 810 million, up 28% year-over-year and accounting for 26% of total revenue. Revenue from our top 5 nonecosystem customers grew 51%.

Our AI cloud business now serves a broad range of sectors, including internet services, front care AI labs, embody AI, autonomous driving, AI foci, 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.

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 on ecosystem, while WPS AI continues to advance. As the only strategic 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 who connected transactions with Xiaomi. The combined HEPS for 2026 and 2027 now total RMB 10 billion, 39% higher than the full year adjustment. In the first half, public cloud revenue from Xiaomi and Kingsoft grew 54% year-over-year. Second, we further strengthened the mass capabilities of our [indiscernible] platform. [indiscernible] 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 defend cooperation with leading customers in emerging sectors. We delivered large-scale computing clusters to leading embody AI and autonomous driving customers, supporting rapid model iteration and expanded our cooperation with a leading AI for science customers to support the growth of this new business.

In Enterprise Cloud, revenue reached RMB 710 million. In public services, we signed an agreement with the [indiscernible] Communications Administration of the Yang Zou River to build Zanghai Cloud, a dedicated digital infrastructure platform for Young River shipping. We also followed a strategic partnership with the Wuhan municipal data bureau and Wuhan Cloud across computing resource interconnection, digital governance, 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 natural [indiscernible] In Enterprise Services, we defend our cooperation with [indiscernible] to jointly build and operate the Guangzhou Provincial Public Services Cloud under an integrated investment, construction and operations model.

In products and technology, we continue to upgrade our full-stack AI capabilities for intelligent computing and AI application deployment. This quarter, we further optimized the model deployment on [indiscernible] 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 kits, 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 service cloud products such as database and storage, easier for agents to access and use. We enhanced the [indiscernible] 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.

So private deployment of domestic AI infrastructure, our Galaxy Stack platform completed deep integration and full life cycle mutual 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.

Yi Li

Thank you, [indiscernible] and thank you all for joining the call today. I will now discuss the second quarter financial results [indiscernible]. Before we go through the details of the financial results for the second quarter, I would like to highlight [indiscernible]. First, our quarter revenue reached over RMB 3 billion for the first time in our company's history, up year-over-year for the last consecutive quarter. In particular, our AI cloud gross billing increased 82% year-over-year to RMB 1.33 billion, accounting for over 43% of our total revenue 31% a year ago. This reflects a continued structural shift in our business leading towards AI. Second, our profitability has improved. Our adjusted gross margins were 15.4%, up 2.4 percentage points quarter-over-quarter at 0.5% parentage points year-on-year.

Our adjusted EBITDA margin reached 36% up from 32% in the same quarter last year and 82% last quarter. Mostly when we had to break even at operating income level this quarter and recorded adjusting operating profit margin of 4%. These unconvalidate our ability to strong AIDC demand into healthy profit growth.

Third, we continue to invest to accelerate the buildout of our AI compute capacity. Capital expenditures, together with right of use assets of tenant through third party financing and the finance leases reached RMB 3.3 billion this quarter versus RMB 2.9 billion in last quarter and RMB 2.8 billion in the same quarter last year.

Now let me walk you through our financial results for the second quarter of 2026. This quarter, total revenue were RMB 3.72 million, up 31% year-over-year or 40% quarter-over-quarter. Of these revenues from [indiscernible] cloud service were 2,358 billion up 45% from 1,625 million in the same quarter last year.

Revenues from enterprise [indiscernible] reached RMB 740 million, compared with RMB 724 million in the same quarter last year, down [indiscernible] by 1% year-on-year. Total quarter revenues was [ 606 ] million, representing a 30% year-over-year or increase, mainly due to a continued investment in a cloud infrastructure.

IDC costs increased by 23% year-over-year from RMB 803 million to 1190 million this quarter. The increase was mainly due to the increase of [indiscernible]. Preamortization costs increased by 75% year-over-year from RMB 732 million in the same quarter of 2025 to RMB 964 million in quarter, largely due to the deterioration of newly acquired and listed AI infrastructure, including servers and network equipment.

Solution development and service costs increased by 4% year-over-year from RMB 564 million in the same quarter of 2025 to RMB 786 billion this quarter. The modest increase was mainly due to higher costs incurred in AI transformation in solution development and delivery. [indiscernible] costs and other costs were approximately $66 million in total this quarter [indiscernible] RMB 92 million in the same quarter last year.

Our adjusted profit for the quarter was RMB 472 million, increased by 35% year-over-year and 34% quarter-on-quarter. Adjusted gross margin was 15.4%, up from 14.9% in the same quarter last year and from 30% last quarter. The increase was driven by higher gross margin in public cloud business, thanks to strong demand tailwinds.

On the expense side, excluding share-based compensation cost expenses, our total adjusted operating expense were RMB 391 million decreased from RMB 761 million in the same quarter last year and from RMB 455 million last quarter, mainly reflecting our disciplined cost and expense control of which are adjusted risk and development expenses were [indiscernible] 84 million, up 1% year-over-year. Adjusted selling and marketing expenses were $102 million, down 7% year-over-year.

General and administrative expenses were RMB 105 million down 51% year-over-year, largely due to lower credit loss expenses. Our adjusted operating profit was RMB 124 million tolling 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 deal 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 at minus 2.2% in the last quarter. Our adjusted net loss was RMB 6 million, down from RMB 300 million in the same quarter last year at RMB 237 million [indiscernible] Our non-GAAP dBA profit was RMB 1,100 million increased by 171% from RMB 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% in the last quarter. It was mainly due to our improving growth profit as well as higher degration costs in our cost as we accelerate our AI computing capacity buildout. Ended June 30, 2026, our cash and cash equivalent totaled RMB 4,674 million compared with RMB 4,504 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 excellent growth in AI demand and further investing in infrastructure, expanding our product and service offerings, managing [indiscernible] equity risk and improving operating efficient. We remain commitment to our OEAI strategy and continue to deliver high-quality growth to our shareholders. Thank you all.

Unknown Executive

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

Operator

[Operator Instructions] Your first question comes from Liping Zhao from CICC.

質疑応答

Unknown Analyst

[Interpreted]

Let me translate by myself. So good evening, Mr. and Ms. Li. I've got 2 questions on your mass business. First, how well improvements in open store model capabilities affect the company's mass business based on your observations, what's the current usage growth trend and which use cases are driving at most? And second, given the payback period for the mass business might be shorter. Will the company allocate more resources to it?

Tao Zou

[Interpreted]

Okay. So just quickly translate. So this answer comes from our SVP, Mr. Nota. So in relation to your first question, the development in open-source [indiscernible] models have mainly 3 impacts. Number one is that we are seeing a very big demand coming from [indiscernible] traditionally flooring model, taking the lead in this area. However, once we have seen the launch of KLM and K3, kind of high-performance models, we're seeing increasingly users from Mainland China adopting and using this made in China [indiscernible] model. And secondly, the increasing use of agentic scenario also broad change to our business. And with that, we have launched, as mentioned in the prepared remarks, the agent product to satisfy such needs. And certainly, 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 opens source [indiscernible] model is actually beneficial for our business. And your second question regarding the balance between mass business and the computing power. So we basically have different business models for the 2 business. For computing power business, essentially, once we sell the computing power, the utilization is financial 100%, 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 quality of factors, including the fluctuation of the token price, the launching of new models, which the governors might prefer to use and also the operating efficiency that we're able to achieve in doing the mass business.

So therefore, we generally balance these 2 business models and hope to have each one of them complement the other one. So we generally dynamically evaluate these 2 business and at the product side, how much resources to allocate.

Operator

We will take our next question -- next question comes from Wenting Yu from CLSA.

Wenting Yu

[Interpreted] The first question is that since joined, 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 time the segment of revenue has decelerated in the past 2 quarters. How should we think about the full year enterprise growth and what's the AI transformation and medium-term positioning for this segment?

Unknown Executive

[Interpreted]

So allow me to quickly translate. So the answer comes from our -- so 3 points. Number one, actually, since 2023, it's been 3 years, and the market has always been hearing voices about the limited supply. So I would say this is actually a new norm. The tech supply on difficulty is actually a long-term kind of situation. But secondly, we should also be aware of the fact that despite of those constraints, financial constraints, the Chinese cloud computing 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 -- recently many of the many China chips are becoming public, and they are particularly good in use cases such as model interest.

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 a relatively small number of projects. So the purchase number, if you look at it on a monthly basis, is 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.

Tao Zou

Our cash expenditure includes [indiscernible] asset to lease arrangement, reaching RMB 6.2 billion in the first half of 2026 accounted for over 75% of our portfolio CapEx last year, where July stature cannot fully represent third quarters of all trends. It clearly shows tangible growth acceleration. Accordingly, we maintain our full year CapEx base case unchanged at [indiscernible] Billion. Thank you, Tintin.

Operator

We will take our next question.

Unknown Executive

Sorry, we need to continue [indiscernible]

Operator

Apologies.

Unknown Executive

[Interpreted]

Okay. So this answer comes from our [indiscernible]. 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 the linear extrapolation perspective. I will give you 3 reasons. I think number one, just to explain why we're seeking -- looking at relative business in this regard is that the upstream supply pricing hiking hike which changed quite significantly in recent quarters, has affected the -- our prospective customers, essentially the SOE companies and also the government agencies to -- they have to frequently adjust their budgeting product, which delayed 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 revenue recognition are concentrated in the second half of the 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 an operating base business model, where operating business model from a financial reporting perspective is automatically classified into public cloud. So this is not typically as it what sees as a weakening of the enterprise cloud business. So that's the 3 points I like to offer.

Operator

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

Timothy Zhao

[Interpreted]

My first question is regarding the mass [indiscernible] Just wondering compared to the peers in the market. How do you think about the Kingsoft Cloud competitive advantage in a master basis in terms of the application scenario, et cetera? And could you share more about the revenue recognition and the profitability profile of the mass service bid.

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 of months? And what have you heard 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.

Unknown Executive

[Interpreted]

So in relation to your question about the positioning, we do have a unique position in the mass business Mainly, we're different from some of the total 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 [indiscernible] models that our affiliate 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, GRM et cetera.

So that's number one. And secondly, it's quite important in today's market to have your proprietary or your own computing power, which is the only way that you can actually secure significant profitability in this business.

So in relation to your question about the price hike. So there are basically 2 products which are core solutions that we have employed increasing price -- number one, that is storage and number two, that is computing power. I'll talk about them separately, respectively. In terms of storage, storage is usual, the incremental amount of storage is actually comes with the intelligent computing demand. That is a relatively small portion of the intelligence computing our overall ticket size. And therefore, in the vast majority of the customers that we negotiated with they are relatively [indiscernible] such price hike. In which case, as a result, we're actually able to not only -- in some places, not only pack through the Nepris in our cost, but also increasing our profitability in that scenario.

And number two, in terms of computing power, because of our specific capabilities, including PAC 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 in which we are doing managed the services, which is an asset-light business model. We look forward to seeing more of that coming to [indiscernible]

Operator

We will take the next question. Your next question comes from Wes Yang from UBS.

Wei Xiong

[Interpreted]

Congrats on a solid quarter. 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?

Unknown Executive

[Interpreted]

So we believe that [indiscernible] AI cloud service providers 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 player, we are able to be in good relations with all of the top model providers [indiscernible] mono labs and be able to provide the best model according to our customers' demand. And also, we're able to -- based on our technology capabilities, we're able to provide highly available and high reliable services to them. based on out of the SLAs that we signed with them. I think thirdly, in relation to profitability question you asked, it is important to work closely with the LM terms labs to, for example, to optimize, to optimize the influence of those models. And that will include the, for example, working with them based on the undisclosed weighting of the models to increase our influence model influence efficiency.

In some of the cases, we're able to get to very close level or even reach the same level of the influence efficiency coming out from the [indiscernible] companies themselves. Thank you.

Operator

We will take our final question. Your final question comes from Yang Liu from Morgan Stanley.

Yang Liu

[Interpreted]

Let me translate my question. I would like to ask on the 2 business model, computing power leasing and Model as a service, what is the ROIC for these 2 business models? And what is the marginal change for the ROIC.

Unknown Executive

Thank you, [indiscernible] At this stage, we don't disclose separate our SD Mark and computing power services. because varies across projects, driven by payback secureness margin, fixed assets and depreciation policies. Overall, must be with much better probability than back into the core servicing at this stage. We have seen continued improvement in maintaining leverage and our business scales are fixed costs are steadily diluted and our trailing translates adjusted operating profit is trend positive, driving a gradual recovery in our overall ROIC. We adhere to demand drilling and a disciplined investment strategy with a strong focus on capital efficiency. With the continuous business structure of [indiscernible] and the material AI mediation. I think our overall LSC will keep improving steadily.

Operator

There are no further questions. Apologies. [indiscernible] the question-and-answer session. I will hand back for closing remarks.

Unknown Executive

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.

Operator

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