Behind Zhipu's first financial report, a new story is hard to tell

Ask AI · How GLM-5’s Technological Breakthroughs Are Reshaping Industry Pricing Logic?

The coming-of-age ceremony for commercializing large models in the industry.

Original by New Vision · Author | Li Xiaodong

On March 31, 2026, Zhiyu AI, the “First Stock in Large Models” that listed on Hong Kong Stock Exchange less than three months ago, released its first annual performance report since going public.

But for the domestic large model industry, the significance of this financial report goes far beyond the annual business review of a single listed company.

From the frenzy of the 2023 Hundred-Model Battle, to the price war and internal competition in 2024, and then to the industry’s rational shift toward commercial implementation in 2025, over three years, the market’s evaluation criteria for large model companies have shifted from “Can they build models” to “Can they build sustainable businesses.”

And this annual report from Zhiyu is a representative sample at this industry turning point.

In the past two years, market perception of Zhiyu has always been tied to a few fixed labels: a tech-driven startup backed by Tsinghua University, a large model vendor maintaining revenue through privatization projects, and an AI concept stock burning money for growth.

However, this financial report, along with Zhiyu’s series of actions in technological iteration and business strategy before and after its release, is prompting the market to reassess the true nature of this company and its position in the domestic AI large model landscape.

01

Structural Changes:

From Project-Based to Standardized Transformation

Let’s first look at the core operational data.

In 2025, Zhiyu achieved a total revenue of 724 million yuan, a year-on-year increase of 131.9%; gross profit of 297 million yuan, up 68.7%; and an adjusted net loss of 3.18B yuan, expanding by 29.1% year-on-year.

Focusing solely on revenue growth rate, this performance has already outpaced the 30% overall growth of China’s core AI industry in 2025. Even in the MaaS track with a 421.2% YoY increase, Zhiyu remains in the top tier.

But what’s truly worth attention is not just the doubling of total revenue, but the fundamental change in revenue structure. This change essentially reflects a bottom-line shift in Zhiyu’s business logic.

Breaking down by deployment mode, in 2025, Zhiyu’s localized deployment business revenue was 530 million yuan, up 102.3% year-on-year, accounting for 73.7% of total revenue, down from 84.5% in 2024; cloud deployment service revenue was 190.4 million yuan, a surge of 292.6%, accounting for 26.3% of total revenue, up from 15.5%.

By product line, revenue from enterprise general large models and open platform/API saw significant YoY growth; enterprise intelligent agent business revenue reached 166 million yuan, up 248.8%.

This set of data clearly illustrates the direction of Zhiyu’s revenue structure transformation: the localized deployment projects that once supported the company’s core are now lagging behind the growth of cloud-based standardized services; API-driven MaaS business and enterprise intelligent agents targeting complex scenarios are becoming new growth engines.

Behind this structural change is a switch in Zhiyu’s business logic.

Early on, like most domestic large model startups, Zhiyu’s revenue mainly came from privatization projects for central and state-owned enterprises and large corporations. These projects had high per-client prices and stable income, but also obvious shortcomings: project-based delivery required substantial customization and operational resources, difficult to scale, and highly dependent on clients.

The growth of cloud API business indicates that Zhiyu’s revenue source is shifting from one-time project delivery to sustainable, standardized model capability calls.

This is evidenced by the operational data of the MaaS platform: as of March 2026, Zhiyu’s MaaS API platform’s annual recurring revenue (ARR) reached 1.7 billion yuan, a 60-fold increase over the past 12 months; platform users exceeded 4 million, with 242k paying developers.

Along with the change in revenue structure, gross profit margins have diverged. In 2025, the gross margin of Zhiyu’s cloud deployment business jumped from 3.3% in 2024 to 18.9%, gross profit increased from 1.6 million to 36 million yuan, a 2,150% increase; meanwhile, the gross margin of localized deployment dropped sharply from 66.0% in 2024 to 48.8% in 2025.

The financial report explains that the decline in gross margin for localized deployment was mainly due to increased delivery resources to meet customer needs; the significant improvement in cloud gross margin was driven by efficiency gains from model inference and scale expansion of computing power, along with product price increases at the end of 2025 and early 2026. The profitability of cloud services has now entered an upward trajectory.

However, behind rapid growth, Zhiyu still faces the industry-wide “revenue growth but profit stagnation” dilemma.

In 2025, Zhiyu’s R&D expenditure reached 3.18 billion yuan, up 44.9%, accounting for 439% of total annual revenue. This massive R&D investment is the core reason for the company’s net loss expanding to 242k yuan.

Looking at the allocation of R&D spending, it mainly falls into two parts: one is employee costs and equity compensation for R&D teams; the other is payments to third-party compute resource providers.

This is a common cost pressure faced by all domestic large model vendors—whether for continuous iteration of foundational models or inference efficiency optimization, sustained investment in computing power and talent is essential.

By the end of 2025, Zhiyu held over 2.2 billion yuan in cash and cash equivalents. How to maintain technological investment while improving profitability will be a key challenge moving forward.

02

How the Upper Limit of Intelligence Translates into Market Discourse Power

If revenue structure change signifies a business model transformation, then the core confidence behind this shift comes from technological iteration that enhances model capabilities. The most tangible reflection of this is Zhiyu’s strategic decision to raise prices against the industry price war in early 2026.

On February 12, 2026, Zhiyu announced its new flagship base model GLM-5, marking its first major model iteration since going public. Just over a month later, this technological achievement was directly reflected in commercial actions: Zhiyu raised API prices twice, with a total increase of 83%, and programming package prices by 30%.

In the past two years, price wars in China’s large model industry have been characterized by price cuts, free offerings, and subsidies. Even leading companies like ByteDance’s Doubao and Alibaba Cloud’s Tongyi Qianwen have sharply reduced API prices to compete for market share.

Zhiyu’s contrarian price increase was particularly notable in this environment.

More interestingly, after the price hike, Zhiyu’s API call volume did not decline but instead showed signs of being in short supply.

Financial data shows that after the price increase, GLM model calls grew by 400%. This counterintuitive performance has prompted the market to reconsider the competitive logic of the large model industry: when model capabilities diverge significantly, customer price sensitivity gives way to demand for effectiveness.

According to official disclosures, on the technical architecture side, GLM-5 integrated DeepSeek’s sparse attention mechanism for the first time, reducing long-text processing costs by 50% while maintaining performance; it also introduced a new “Slime” asynchronous reinforcement learning framework, solving the logical decay problem in long-term agent execution and improving the efficiency of complex reinforcement learning tasks.

This technological enhancement directly translates into competitive advantages in commercial scenarios. Within 24 hours of GLM-5’s release, it was officially adopted by top platforms including ByteDance’s TRAE/Coze, Alibaba’s Qoder, Tencent’s CodeBuddy, Meituan’s CatPaw, Kuaishou’s Wanquing, Baidu Cloud, and WPS Office.

The financial report reveals that nine of China’s top ten internet companies are using GLM models.

An interesting phenomenon is that almost all these internet giants with access to GLM models also have their own self-developed large models. Their choice to adopt Zhiyu’s models alongside their own is primarily because, in specific scenarios, GLM-5’s capabilities offer differentiated advantages. Beyond the internet industry, Zhiyu’s models are also penetrating traditional sectors like finance, manufacturing, and energy.

This confirms Zhiyu’s core strategy of “Intelligent Upper Limit × Token Consumption Scale” as stated in the financial report. In the early stage of the large model industry, competition centered on parameter scale and leaderboard rankings; as the industry moves toward commercialization, the “intelligent upper limit”—the ability to solve complex problems in real production scenarios—becomes the core determinant of market discourse power.

In March this year, a wave of collective price increases swept China’s large model industry. Tencent Cloud announced a price hike for its core Mengtian series models; shortly after, Alibaba Cloud and Baidu Cloud also raised prices for AI compute-related products and services.

This industry-wide price increase indirectly confirms Zhiyu’s previous judgment: as large models evolve from toys to productivity tools, customers are willing to pay for genuinely effective capabilities, shifting industry competition from price wars to value wars.

03

Reconstructing Industry Landscape: Zhiyu’s Position and Choices

In just two years since the Hundred-Model Battle, the landscape of China’s large model industry has undergone a fundamental change.

According to China Academy of Information and Communications Technology (CAICT), at its peak, over 200 companies in China launched large model products. By the end of 2025, the number of vendors capable of sustained R&D investment, possessing independent controllable computing resources, and establishing a sustainable business logic has shrunk rapidly to fewer than 10 core players.

The current domestic large model market has formed a clear competitive hierarchy. The first tier includes internet giants with full-stack capabilities—Baidu, Alibaba, Tencent, ByteDance—who have their own foundational models, large-scale scenarios, traffic portals, and control over computing and cloud services.

According to IDC data, in the first half of 2025, China’s public cloud large model token calls reached 536.7 trillion tokens, with ByteDance’s Volcano Engine leading market share, followed by Alibaba Cloud and Baidu Cloud.

The second tier consists of startups like Zhiyu, MiniMax, and Moonshade, which focus on foundational model R&D, mainly commercializing through API services and privatization deployments. They have differentiated technological advantages but lag behind in scenarios, traffic, and computing resources compared to the giants.

In this landscape, external opinions suggest Zhiyu is following a path similar to overseas Anthropic: building a core barrier around base model capabilities, mainly offering API tokens, and developing an ecosystem through deep engagement with developers and enterprise clients, rather than competing head-on with giants in C-end traffic portals.

As a company incubated by Tsinghua’s technical team, Zhiyu is among the earliest domestic teams to invest in large model R&D. However, unlike internet giants, Zhiyu lacks a self-owned C-end traffic portal and mature cloud sales channels.

Competing directly with giants in the C-end chatbot space would be difficult to gain advantage. Instead, focusing on core base model capabilities and providing API outputs to developers, SMEs, and large internet firms with model needs allows Zhiyu to carve out its own niche.

From the current financial data, this strategy has shown initial success.

However, this path also faces challenges.

On one hand, the rapid iteration of self-developed models by internet giants means their external model needs are mainly supplementary, not entirely dependent. Once their in-house models catch up in specific scenarios, customer loss is a risk.

On the other hand, the development speed of domestic open-source large models is accelerating. Open-source models like DeepSeek are approaching the capabilities of closed-source models, significantly lowering the threshold for SMEs to use large models, which could impact Zhiyu’s API business.

Additionally, Zhiyu must contend with competition from other startups in the same tier.

For example, MiniMax, also listed in Hong Kong, launched its C-end products earlier. Startups like Moonshade and Baichuan Intelligence have also developed their own specialties in long context and vertical industry scenarios, making the market highly competitive.

This first annual report after listing is more like a coming-of-age ceremony for Zhiyu’s commercialization. Previously, market perception was more focused on “strong technology but questionable commercialization”; now, the financial report and subsequent actions demonstrate the company’s maturity in business.

From the industry’s perspective, Zhiyu’s development path offers a reference model for domestic large model startups.

Historically, doubts about domestic large model startups centered on their dependence on privatization projects and inability to establish standardized, scalable business models—risking becoming just traditional software outsourcing firms.

Zhiyu’s revenue structure change and rapid growth of cloud API business prove that, in a market dominated by internet giants, startups can differentiate through core technology and find their niche.

Of course, challenges remain: the high R&D costs and losses, customer concentration risks, and competition from internet giants and open-source models are issues to address.

In 2025, China’s large model industry has completed the shift from “Can we build it” to “Can we make it usable.” According to CAICT, the total token calls for large models on China’s public cloud providers grew 16-fold in 2025, exceeding 2 quadrillion tokens.

Behind this data is the movement of large models from labs into real-world production across various industries, becoming true productivity tools. For a listed company, the market not only wants to see growth but also a clear path to profitability—something Zhiyu needs to demonstrate.

— END —