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ZHIPU

ZhiPu 02513.HK Price

Closed
ZHIPU
$0
+$0(%0,00)
No data

*Data last updated: 2026-04-19 11:31 (UTC+8)

As of 2026-04-19 11:31, ZhiPu 02513.HK (ZHIPU) is priced at $0, with a total market cap of --, a P/E ratio of 0,00, and a dividend yield of %0,00. Today, the stock price fluctuated between $0 and $0. The current price is %0,00 above the day's low and %0,00 below the day's high, with a trading volume of --. Over the past 52 weeks, ZHIPU has traded between $0 to $0, and the current price is %0,00 away from the 52-week high.

ZHIPU Key Stats

P/E Ratio0,00
Dividend Yield (TTM)%0,00
Shares Outstanding0,00

ZhiPu 02513.HK (ZHIPU) FAQ

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ZhiPu 02513.HK (ZHIPU) is currently trading at $0, with a 24h change of %0,00. The 52-week trading range is $0–$0.

What are the 52-week high and low prices for ZhiPu 02513.HK (ZHIPU)?

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What is the price-to-earnings (P/E) ratio of ZhiPu 02513.HK (ZHIPU)? What does it indicate?

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What is the most recent quarterly earnings per share (EPS) for ZhiPu 02513.HK (ZHIPU)?

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Risk Warning

The stock market involves a high level of risk and price volatility. The value of your investment may increase or decrease, and you may not recover the full amount invested. Past performance is not a reliable indicator of future results. Before making any investment decisions, you should carefully assess your investment experience, financial situation, investment objectives, and risk tolerance, and conduct your own research. Where appropriate, consult an independent financial adviser.

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ZhiPu 02513.HK (ZHIPU) Latest News

2026-04-15 05:32

Hong Kong AI Concept Stocks Fall in Afternoon Trading, Zhipu AI Down Over 10%

Gate News message, April 15 — Hong Kong AI concept stocks (Hong Kong Stock Exchange) fell sharply this afternoon (April 15), with Zhipu AI dropping over 10%. MINIMAX-W and Xunce also declined more than 5%.

2026-04-15 05:15

TradFi Fall Alert: ZHIPU (ZhiPu 02513.HK) Falls Over 8%

Gate News: According to the latest Gate TradFi data, ZHIPU (ZhiPu 02513.HK) has dropped by 8% in a short period. Current volatility is significantly higher than recent averages, indicating increased market

2026-04-15 02:34

TradFi Fall Alert: ZHIPU (ZhiPu 02513.HK) Falls Over 6%

Gate News: According to the latest Gate TradFi data, ZHIPU (ZhiPu 02513.HK) has dropped by 6% in a short period. Current volatility is significantly higher than recent averages, indicating increased market

2026-04-14 03:49

Gate TradFi launches 15 Hong Kong stock pairs and 6 forex CFD trading pairs, supporting up to 20x leverage

Gate News message. According to the official announcement, the Gate TradFi Stocks section has launched 15 stock CFD trading pairs, including Tencent, Meituan, Xiaomi, Kuaishou, AIA Insurance, Geely Auto, Zhipu, MINIMAX, JXQ, Lenovo, Kangfang Bio, CITIC Shares, Sunac China, China Biopharmaceutical, Anta Sports, all of which support 4x fixed leverage, with a minimum order size of 0.1. At the same time, the Gate TradFi FX section has launched 6 forex CFD trading pairs: EUR/Hungarian Forint, USD/Hungarian Forint, USD/Indonesian Rupiah, USD/Indian Rupee, USD/Thai Baht, USD/New Taiwan Dollar. All of them support 20x fixed leverage, with a minimum order size of 0.01.

2026-04-02 02:02

Hong Kong stocks: Most OpenClaw concept stocks fall; Zhipu drops more than 15%

Gate News message, April 2, Hong Kong stock OpenClaw concept stocks (AI open-source model related concepts) mostly fell. Zhipu (02513.HK) fell more than 15%, MINIMAX-W (00100.HK) fell more than 9%, Kingsoft Cloud (03896.HK) and Xiaomi Group (01810.HK) fell more than 3%, Alibaba (09988.HK) and Meituan (03690.HK) fell more than 2%.

Hot Posts About ZhiPu 02513.HK (ZHIPU)

链研社

链研社

04-17 15:34
DeepSeek is valued at over $1 billion USD, raising $300 million USD. Among unlisted companies, compared with Moon’s Dark Side, kimi’s most recent round raised $1 billion USD, with a valuation of $18 billion USD. There are also two already-listed companies: Zhipu and Minimax. 1. Zhipu AI Listing fundraising amount: Net amount raised is approximately 4.17 billion HKD, equivalent to about 530 million USD Listing market value: The IPO issue price is 116.2 HKD; the overall valuation at the time of issuance was approximately 51.8 billion HKD. Current market value: 891 HKD, with the total market value maintained at around 400 billion HKD. 2. MiniMax Listing fundraising amount: IPO fundraising amount is approximately 4.82 billion HKD, equivalent to about 616 million USD Listing market value: The IPO issue price is set at the upper limit of 165 HKD, and the issuance valuation exceeds 46 billion HKD. Current market value: 859 HKD, with a total market value of about 270 billion HKD.
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GateUser-bd883c58

GateUser-bd883c58

04-17 12:51
**Source: Zhitu IPO, Text/Wang Fei** The first stock of large models, delivering its first annual report after listing. On March 31, independent large model manufacturer Beijing Zhipu Huazhang Technology Co., Ltd. (hereinafter: Zhipu) released its 2025 annual report: revenue of 724 million yuan, up 131.9% year-over-year; net loss of 4.72B yuan for the year, an increase of 59.5% compared to the previous year; adjusted net loss of 3.18B yuan, up 29.1% year-over-year. On April 1, Zhipu opened 15.00% higher at HKD 797.5, reaching a high of HKD 938 during trading, demonstrating the market’s recognition of it. By the close, Zhipu’s share price rose 31.94% to HKD 915, with a total market value of HKD 407.95B, compared to HKD 52.83B on the first day of trading, an increase of approximately 672.23%. However, on April 2, Zhipu’s stock price began to retreat, closing down 14.86% at HKD 779, with a market value of HKD 347.31B, and a low of HKD 764 during trading. Annual revenue of 720 million yuan, the largest domestic large model revenue scale ------------------- As an independent manufacturer focused on foundational model research and development, in 2021, Zhipu released China’s first proprietary pre-training large model framework, GLM framework, and launched its model-as-a-service (MaaS) product development and commercialization platform, mainly offering four types of models: language models, multimodal models, agent models, and code models, as well as integrated tools for model fine-tuning, deployment, and agent development. In 2022, Zhipu open-sourced its first 1000-billion-parameter model (GLM-130B). With its original GLM (General Language Model) pre-training architecture, Zhipu built a full-stack model matrix covering language, code, multimodal, and agents, with models adapted to over 40 domestic chips. As of June 2025, Zhipu has a research and development team of 657 members, with R&D personnel accounting for 74%. Its team members have backgrounds and experience in natural language processing, complex decision-making systems, multimodal semantic analysis, and related fields. The core scientific research team and academic advisors have published 500 top-tier influential papers, with over 58,000 citations. Supported by this, Zhipu’s model update frequency follows a hybrid rhythm of “base models every 3–6 months, specialized/open-source models more frequently.” On April 2, Zhipu released its first native multimodal Coding base model, GLM-5V-Turbo. The model’s biggest breakthrough is its deep integration of visual and programming capabilities, capable of native processing of text, images, videos, and other multimodal information, while excelling at programming, long-term planning, and complex task execution. According to reports, GLM-5V-Turbo achieved leading performance on core benchmarks such as multimodal coding and agents. It introduced visual capabilities while maintaining comparable text-only programming and reasoning abilities. The model is deeply adapted to Claude Code and the “Lobster” scenario, enabling OpenClaw Lobster to have true visual ability and understand on-screen information. Based on the prospectus and latest annual report, from 2022 to 2025, Zhipu’s R&D investments were approximately 84.4 million, 529 million, 100B, and 3.18 billion yuan respectively, totaling nearly 6 billion yuan. Supported by this, Zhipu’s GLM series models are iterated every 3–6 months. It is worth noting that Zhipu has achieved revenue doubling for four consecutive years. From 2022 to 2025, Zhipu’s revenue was approximately 57.49 million, 125 million, 312 million, and 724 million yuan; gross profit was approximately 31.36 million, 80.48 million, 176 million, and 297 million yuan, with gross profit margins of 54.6%, 64.6%, 56.3%, and 41.0%; annual net losses were approximately 144 million, 788 million, 130B, and 2.19B yuan, with total accumulated losses around 8.6 billion yuan; adjusted net losses were approximately 97.42 million, 621 million, 2.96B, and 4.72B yuan. With an annual revenue of 724 million yuan, Zhipu has become the largest domestic large model company by revenue. By comparison, in 2025, MiniMax’s revenue is approximately USD 2.47B (about 544 million yuan). Specifically, in terms of deployment methods, in 2025, Zhipu’s cloud deployment revenue increased from 48.48 million yuan in 2024 to 190 million yuan, a 292.6% increase, mainly due to continuous iteration significantly improving the model’s intelligence ceiling. The enhanced model intelligence further drove increased model invocation; local deployment revenue grew from 264 million yuan in 2024 to 534 million yuan, a 102.3% increase. By business line, revenue from Zhipu’s open platform and API, enterprise-level intelligent agents, and enterprise-level general large models all saw substantial growth. In 2025, these three segments generated revenues of 190 million, 166 million, and 366 million yuan respectively. Quantity and price rise together, proposing the concept of Token architecture power ----------------- Thanks to the generational leadership of the GLM series in “intelligence ceiling” and extreme cost optimization in reasoning, Zhipu achieved a comprehensive explosion from developer ecosystem to globalization in 2025: MaaS API platform’s ARR reached about 1.7 billion yuan, a 60-fold increase year-over-year; business profitability improved significantly, with API gross margin rising nearly five times to 18.9%. In February 2026, within 24 hours of the release of the flagship base model GLM-5, it was officially integrated into top platforms such as ByteDance TRAE, Alibaba Qoder, Tencent CodeBuddy, Meituan CatPaw, Kuaishou Wànqíng, Baidu Cloud, and WPS Office. Among China’s top ten internet companies, nine are deeply utilizing the GLM model. By March 2026, Zhipu’s registered enterprise and user count exceeded 4 million, serving over 218 countries and regions worldwide. Additionally, in 2025, Zhipu became the first domestic company to launch the GLM Coding Plan. With its high-quality coding capabilities, the number of paid developers worldwide rapidly surpassed 242k, and token calls increased 15-fold in six months. By February 2026, even with a 30% price increase and the removal of first-time purchase discounts, the coding plan remained in high demand, becoming one of the fastest-growing AI coding services globally. As the earliest domestic model manufacturer in the Agent field, from the world’s first mobile Agent AutoGLM to China’s first one-click install AutoClaw, Zhipu is defining the intelligent paradigm of agentic AI. In March 2026, after the Coding Plan, Zhipu launched Claw Plan, which reached 100k subscribers within two days and over 400k within 20 days. In terms of globalization, Zhipu has realized token value monetization worldwide. Its models are widely deployed on global cloud platforms such as Google Vertex AI, AWS Bedrock, Fireworks, Cerebras, and have entered international model aggregation platforms like OpenRouter and Vercel, ranking No.1 among paid models on OpenRouter. The GLM has become the default model for well-known coding platforms (like Windsurf) and coding agent platforms (like OpenCode). Notably, due to strong computing power demand, Zhipu proactively increased the price of its coding plan by 30% in February 2026, and its API call pricing increased by 83% compared to the end of last year. Thanks to the outstanding model performance, after an 83% price increase, Zhipu’s API call volume did not decline but increased, showing a rare “quantity and price rise” trend, indicating customers’ high willingness to pay for more certain productivity. At the 2025 performance briefing, CEO Zhang Peng specifically mentioned that even after the price increase, the market remained in short supply, with invocation volume growing by 400%. Regarding future development goals, Zhang Peng stated that Zhipu is not a traditional software company but a native intelligence laboratory with a belief in AGI. Its moat does not lie in stacking computing power but in the bottom-level deconstruction of the essence of intelligence and transforming this understanding into social productivity. Looking ahead to 2026, the intelligent paradigm will evolve from lightweight VibeCoding (ambient programming) to industrial-grade Agentic Engineering (agent engineering), and further into autonomous planning, environmental perception, and self-iterative digital engineers. Ultimately, this will enable multi-step iteration and logical consistency in Long-horizon Tasks, further breaking through the intelligence ceiling and exponentially increasing token calls. It is noteworthy that in this financial report, Zhipu also proposed a new concept: Token Architecture Capability (TAC)—“intelligent invocation volume × intelligent quality × economic conversion efficiency.” This is the result of reshaping core competitiveness after large models acquire long-horizon task execution in a closed-loop capability. As enterprise TAC demand continues to grow, Zhipu’s MaaS platform is becoming the infrastructure connecting foundational models with industry applications. Zhang Peng believes that in the future, the standard for measuring individual or organizational value will no longer be how much information they hold, but their role as Token architects, building complex agent systems within given budgets and driving large models to autonomously operate these complex systems. Zhipu aims to become the infrastructure that enhances society’s overall TAC, turning every drop of Token into deliverable economic value.
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GateUser-bd883c58

GateUser-bd883c58

04-17 09:06
Ask AI · How does Wave Theory explain the pricing logic of AI stock scarcity? These days, the Hong Kong stock big model sector has once again staged a dizzying "roller coaster" performance. On April 1st, after Zhipu released its 2025 financial report, the stock price surged about 32% in a single day, with a market capitalization briefly surpassing 410 billion HKD, and MiniMax also rose 14% simultaneously. However, on April 2nd, both companies reversed course and retreated, with Zhipu dropping nearly 15%, and MiniMax falling 10%. ▲Zhipu's stock price trend after listing on January 8, 2026 If you open the financial report, you'll find it almost "magical realism": in 2025, Zhipu and MiniMax's revenues were only 720 million yuan and 544 million yuan respectively, but their net losses after non-recurring gains and losses reached about 3.8 billion yuan and 1.9 billion yuan. How can such "profitable companies that lose faster" oscillate upward amid doubts? Why, even after a correction, their market value still remains in the 300 billion HKD range, far surpassing many traditional "blue-chip" stocks? The answer is: these AI newcomers have already broken free from the "valuation gravity field" of traditional manufacturing or internet companies. In the high barrier, high investment, winner-takes-all track of large models, the traditional breakeven line is no longer the only coordinate system. ▲Zhipu's net profit attributable to parent over the past four years Market pricing of them is less about paying for current profitability and more about betting on the "infrastructure of the AI era." This is similar to the internet bubble around 2000—back then, Amazon was losing money year after year, but investors were betting not on its current profit statement, but on the future it represented. The difference is, this story might be faster and more intense than the internet boom. To understand this "magical performance," PE ratios or fundamental analysis are no longer enough. Investment theorist Wave proposed a widely cited framework—the "dual commodity attribute of stocks"—which can help us clear some of the fog. In Wave's view, stocks carry two identities simultaneously: First: a normal commodity. Stocks represent a company's productive capacity, and their "use value"—that is, profitability—determines stock prices. This is the traditional value investor's perspective. Second: a scarce commodity. Stocks are trading chips, and their "market price" determines exchange value, which in turn "calibrates" their use value. This is the game theory perspective. When a stock's scarcity is fully recognized by the market, its pricing logic undergoes a qualitative change: it is no longer determined by "how much it's worth," but by "how much someone is willing to pay." Hermès' Birkin bag is a typical example of "price calibration value": not something you can buy just because you want it; it requires "waiting list"; buyers' first reaction is often not "how much can it hold," but its "value retention and status pricing" in the second-hand market. Currently, the reality of the Hong Kong stock big model sector is—purely representative of China's frontier level of general artificial intelligence and capable of large-scale commercialization—extremely scarce. Zhipu and MiniMax are almost the only two options available in the market right now. For long-term funds and hedge funds in the secondary market, they are no longer just financial statements but an irreplaceable "era chip." When an asset is extremely scarce, the pricing logic becomes: because everyone is willing to pay a high price, it must be worth that much. This seemingly crazy pricing logic is not just hype about chips. There is actually a positive feedback mechanism behind it. When a company's stock price is driven to an extremely high level, this "premium" translates into real resource allocation rights. Take Zhipu as an example: its current market cap of 350 billion HKD is not just a number on the books—it means the company can raise equity at lower costs, attract top global scientists with richer options packages, and more easily persuade governments and large enterprises to purchase its services. This is what Wave calls the "discovery of exchange value": capital markets first give a "sky-high" price through speculation, which grants the company a certain market "legitimacy." The company then uses the resources gained from the premium to refine products and push the model's intelligence "upper limit," solidifying its position as an industry leader. In short: it’s not because it’s powerful that it’s expensive, but because selling high first provides the "ticket" to become stronger. The market believes that Zhipu and MiniMax may form a clever closed loop: high R&D investment creates technological scarcity, scarcity attracts market premium, and high market value then feeds back into real R&D. Under this logic, Zhipu is no longer just a company selling API services; it’s more like an "intelligent entity" evolving within the capital market. In this battle for pricing power, traditional accounting standards are no longer keeping pace with AI's speed. However, Wave also offers a sober footnote: the profit from investing in scarce commodities is ultimately a game played by a very few. For ordinary investors, profiting from this game detached from fundamentals faces two harsh physical limits. Limit one: the maximum investment horizon. The time the stock price diverges from its intrinsic value often exceeds what investors can tolerate in holding periods. A company's bottoming and "bubble" persistence may surpass most people's patience. Many exit amid doubts, only to fall prey to the wave of dawn’s early light. Limit two: the minimum reaction time. The jump in price and the return to value of scarce commodities are often "leap-like." For stocks like Zhipu, which can rise 30% in a day and fall 15% the next, key corrections often happen within minutes. Without extremely fast reactions and steel-like mental resilience, participants are mostly reduced to "buying high" or "selling low" spectators. But remember, scarcity is the only support of this logic, and it’s also the reason many high-market-cap companies eventually end up with nothing. Once the competitive landscape shifts—new strong competitors emerge, diluting the "uniqueness," or massive R&D investments fail to sustain technological leadership—the "leap-like" return to value may be even more rapid and ruthless than the rise itself. The pricing power granted by the market is never free. It can elevate an era, but it can also wipe it out in an instant. From Zhipu to MiniMax, this battle for pricing power is far from over. In the relentless arena of money, every valuation point is a bet. Ordinary people, just watch the show!
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