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ZHIPU

ZhiPu 02513.HK Price

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

*Data last updated: 2026-04-24 00:37 (UTC+8)

As of 2026-04-24 00:37, 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

Learn More about ZhiPu 02513.HK (ZHIPU)

Gate Learn Articles

Initial Listing: Gate Futures to Launch Stocks with 6 USDT-M Perpetual Contracts, Including TENCENT and XIAOMI

Gate's Futures Stocks will officially launch live trading of TENCENT (TENCENT 00700.HK), MEITUAN (MEITUAN 03690.HK), XIAOMI (XIAOMI 01810.HK), KUAISHOU (KUAISHOU 01024.HK), XUNCE (XUNCE 03317.HK) and ZHIPU (ZhiPu 02513.HK) perpetual contract (USDT-M) at 06:00 (UTC) on April 13, 2026, supporting long and short positions with leverage from 1x to 20x. Leverage can be selected at the time of order placement.

2026-04-13

2026: The AI sector has entered a new phase—how can entrepreneurs adjust their strategies to optimize their algorithms?

This article starts by examining Meta and Manus, along with the public listings of Zhipu and MiniMax, to break down the criteria for AI products transitioning from interesting demos to meaningful deployment—shifting from specialized applications to general-purpose platforms.

2026-01-14

The Gate contract stock section will launch the first trading of 6 perpetual contracts including TENCENT (Tencent Holdings 0700.HK) and MEITUAN (Meituan 03690.HK)

It is reported that Gate's traditional asset category layout is comprehensive, covering the widest range on the entire network.

2026-04-13

Blogs

How to Trade Zhihu Stock on Gate TradFi? April Market Snapshot for ZHIPU

The market continues to validate the logic of simultaneous growth in both token supply and price, making it the core narrative supporting Zhipus stock price.

2026-04-22

The Rise of Chinese AI Unicorns and a Battle with OpenAI

Geopolitical Tension May Inhibit the Growth of the AI China Sector

2024-05-15

ZhiPu 02513.HK (ZHIPU) FAQ

What's the stock price of ZhiPu 02513.HK (ZHIPU) today?

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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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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

2026-04-23 02:02

Zhipu Stock Hits Record High, Up Over 5% at Market Open with 800% Gains Since IPO

Gate News message, April 23 — Zhipu (02513.HK) surged over 5% at market open, reaching a new all-time high. The stock has gained nearly 800% since its listing.

2026-04-22 17:00

OpenClaw, Hermes, and SillyTavern Confirmed in GLM Coding Plan Support

Gate News message, April 22 — Zixuan Li, a product manager at Zhipu AI, announced on X that OpenClaw, Hermes, and SillyTavern have been officially marked as supported projects under the GLM Coding Plan. Other general-purpose tools will be evaluated on a case-by-case basis. Li also advised users not to share account credentials or use subscriptions as API access. Users who encounter error code 1313 while following the guidelines are encouraged to contact Zhipu's support team for assistance.

2026-04-22 07:13

Zhipu AI Discontinues GLM Coding Plan Unlimited Weekly Quota Subscription on April 30

Gate News message, April 22 — Zhipu AI announced that it will discontinue automatic renewal of the GLM Coding Plan unlimited weekly quota subscription starting at 10:00 AM Beijing time on April 30, 2026. The discontinuation affects users currently subscribed to the legacy plan with auto-renewal enabled. According to the company, the decision was driven by sustained growth in usage, which has made the original unlimited weekly quota model difficult to sustain long-term. Affected users will receive two months of equivalent new plan benefits as compensation. Current subscription cycles and pricing remain unchanged, and the two-month compensation will be automatically issued on April 30. After the compensation period expires, users who wish to continue using the service must manually subscribe to the latest available plan at that time.

2026-04-21 03:20

TradFi Fall Alert: ZHIPU (ZhiPu 02513.HK) Falls Over 4%

Gate News: According to the latest Gate TradFi data, ZHIPU (ZhiPu 02513.HK) has dropped by 4% in a short period. Current volatility is significantly higher than recent averages, indicating increased market activity.

2026-04-20 05:07

TradFi Rise Alert: ZHIPU (ZhiPu 02513.HK) Rises Over 8%

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

Hot Posts About ZhiPu 02513.HK (ZHIPU)

GateUser-bd883c58

GateUser-bd883c58

3 hours ago
How does AI · Intelligent Agent Application Ignite a Surge in Token Demand? Tokens are the "new currency" in the AI era. In 2024, the AI price war has begun, with tokens priced in "cents"; by 2026, demand for computing power will explode, and model vendors and cloud providers will collectively raise their token prices. Over the past two years, the large model industry has experienced a dramatic shift from price wars to value wars, and the value of tokens is being reevaluated. Beyond wages, bonuses, and equity, tokens have even become a new bargaining chip in Silicon Valley engineers' salary negotiations. The ecological layout and resource competition around tokens have already begun. **From Price Drop to Price Increase** By 2026, model vendors and cloud providers will collectively raise their token prices. This year, Zhipu has issued two price increase notices. On March 16, Zhipu launched the base model GLM-5-Turbo optimized for deep scenarios in OpenClaw, with API prices increased by 20%. In the "Lobster" packages for individual and enterprise users, Claw experience monthly cards are 39 yuan/month, including 35 million tokens; Claw advanced monthly cards are 99 yuan/month, including 100 million tokens. In February, Zhipu announced a price adjustment for the Coding Plan, stating, "Due to the sustained strong market demand for the GLM Coding Plan, with rapid growth in user scale and call volume," deciding to cancel the first-time purchase discount, while retaining quarterly and annual subscription discounts, with overall package prices increasing by at least 30%. Besides model vendors, cloud providers are also collectively raising prices. Due to the popularity of Coding Plan subscriptions, Alibaba Cloud's model API calls surged, and on March 4, they announced a phased adjustment of first-time purchase discounts, with limited daily supply, while supplies last. On March 18, Alibaba Cloud stated that due to the global AI demand explosion and supply chain price increases, the costs of core hardware procurement in the industry have risen significantly, and from April 18, prices for AI computing power, CPFS (Intelligent Computing Edition), and other services will be adjusted. Services related to Pengtougexin Wu 810E and other computing cards increased by 5%-34%, and CPFS (Intelligent Computing Edition) increased by 30%. Baidu Smart Cloud also announced that from April 18, AI computing power-related products and services will increase by about 5%-30%, and parallel file storage and other services will increase by about 30%. Tencent Cloud announced that from March 13, the public testing of models GLM 5, MiniMax 2.5, and Kimi 2.5 has ended, transitioning to official commercial services billed based on model calls. The prices of the Hun Yuan series models have also been adjusted: Tencent HY2.0 Instruct model input price increased from 0.0008 yuan/1,000 tokens to 0.004505 yuan/1,000 tokens, output price from 0.002 yuan/1,000 tokens to 0.01113 yuan/1,000 tokens. However, just two years ago, the "price reduction wave" of tokens is still fresh in memory. In the 2024 "Hundred Model Battle," the large model industry was still in the midst of fierce price wars, with cloud and model vendors competing by lowering prices and giving away tokens. In May of that year, ByteDance launched a price war with a price of 0.0008 yuan per 1,000 tokens, followed by Alibaba Cloud, which announced a maximum discount of 97% on Tongyi Qianwen. At that time, the main model Qwen-Long of Tongyi Qianwen, comparable to GPT-4 level, saw input prices drop from 0.02 yuan/1,000 tokens to 0.0005 yuan/1,000 tokens. Meanwhile, Zhipu's newly registered user bonus increased from 5 million tokens to 25 million tokens. DeepSeek, which trained high-performance large models at lower costs, revealed key information behind its V3/R1 inference system in March last year. By optimizing throughput and latency, if all tokens are priced according to DeepSeek-R1, the cost-profit ratio can reach 545%. Technology is the confidence behind model price reductions. Tan Dai, President of Volcano Engine, ByteDance's cloud service platform, stated during the 2024 AI price reduction wave that the basic logic of price cuts is confidence in reducing costs through technical means, and the market also needs lower-priced large models. "Two years ago, demand for computing power was mostly from enterprises; now, individual demand is 'hungry,' driving AI startups and large companies to shift their business models toward token consumption," said Tian Feng, President of the Fast and Slow Think Tank and former founding director of SenseTime's AI industry research institute. In the past two years, models have rapidly iterated, and intelligent agent applications have grown significantly, driving continuous increases in computing power demand. High-cost inference GPUs have limited capacity, and costs for core hardware like memory and related infrastructure have risen sharply. Bernard Golden, CEO of Navica, a Silicon Valley tech analysis, consulting, and investment firm, said the entire industry is frantically seeking more computing power. Under the imbalance of supply and demand, price increases are inevitable. "A smarter model performs more complex tasks and consumes enormous resources," said Zhang Peng, CEO of Zhipu, when responding to price hikes. He explained that the reasoning and thinking chains behind agent tasks are longer, and they interact with underlying infrastructure through code writing, constantly debugging and correcting errors. The token volume needed to complete a task is ten or even a hundred times that of answering a simple question. The essence of price adjustment is changing costs—"bigger models, stronger capabilities, and higher service costs—so we want to gradually bring it back to a normal commercial value range. Relying on low prices long-term is not good for industry development." **Token Call Volume Grows a Thousandfold in Two Years** Over the past two years, software vendors have integrated text, image, and speech generation capabilities into existing products such as customer service platforms, marketing material creation, and service robots through standardized API interfaces. Enterprise users call large model capabilities via APIs, billed by usage or subscription, lowering entry barriers and upfront investments. After all, a single H100 GPU costs about $25,000, and deploying multiple GPUs in one system costs even more. This service model allows large models to reach vast numbers of users quickly, causing token call volumes to soar. Liu Lihong, Director of the National Data Bureau, recently disclosed that by the end of 2025, over 100k high-quality data sets had been built nationwide. By March this year, China's daily token calls exceeded 140 trillion, a more than 1,000-fold increase from early 2024's 100 billion, and a 40% increase over the 100 trillion at the end of 2025 within just three months. Tian Feng told The Paper that in 2024, the demand for training compute power increased by over 50%, but by 2025, the situation reversed completely. If two years ago was the hundred "model" battle, now it is the hundred "shrimp" battle. The explosive growth in reasoning demand, with reasoning services deeply tied to token consumption, is the largest and fastest-growing compute scenario. Continuous improvements in model performance drive token consumption skyrocketing, and widespread adoption of AI programming, "OpenClaw" (Lobster), and other intelligent agent applications cause token demand to explode. OpenClaw is jokingly called a "token black hole." For companies and individuals using Lobster, tokens are the biggest cost bottleneck. Tian Feng said that the token consumption of intelligent agents executing tasks is 4-15 times that of traditional Q&A. AI entrepreneur Luo Xuan used OpenClaw to complete complex research tasks, consuming millions or even more tokens. To find cheaper tokens, his experience is to register as a new user with cloud or model vendors to get free tokens, but he still laments, "tokens are too expensive." Programming, chatting, office work, and other compute tasks also consume tokens. From a broader perspective of compute consumption, image generation priced by image count and video generation priced by duration and resolution also consume massive compute resources. OpenAI shutting down the Sora video app is an example. Running video generation services requires huge computing power and electricity, which is a massive expense for any company, and shutting down Sora frees up substantial compute resources. The demand for compute power not only drives GPU demand but also causes related hardware to fluctuate and become a limiting factor. "Cooling, lighting, server electricity, and data center power costs account for about 60%. Now, energy prices for oil, natural gas, and other sources are rising, and memory has a five-year upward cycle," said Tian Feng. Energy and hardware costs drive compute power price increases. Huang Zhiming, Vice President of Cisco and CEO of Greater China, told The Paper that in the short term, hardware investments and factory construction cannot be completed in a month or two, and supply-demand fluctuations will continue for some time. Hou Shengli, Senior Vice President and CTO of Cisco Greater China, added that catching up with demand generally takes about two years; "memory factory adjustments take at least two years, and there won't be improvement before the end of 2027. Rebuilding factories and laying out production lines isn't that fast." However, Huang Zhiming believes that as the user base expands and applications become more widespread, costs will gradually become more affordable and accessible. Yao Xin, founder of Piao Cloud Computing (Shanghai), told The Paper that today, the bottleneck limiting AI and compute power is not the most advanced chips but the ordinary IT technologies and traditional supporting components. Over the past decade, the traditional IT infrastructure industry chain—memory, hard drives, switches—has maintained steady growth aligned with global GDP growth, with long-term stable demand driving moderate capacity expansion. But the explosive growth of AI has broken this balance. GPU shipments have surged, and supporting peripheral components are lagging behind in this "turning point" demand. "High-end chip capacity has increased, but other capacities haven't kept pace. Everyone has been hit hard, so traditional components like memory and hard drives are expanding their production." **Alternating Rise of Supply and Demand, Eventually Stabilizing** "Now tokens are more expensive than interns; in three to five years, they will definitely be cheaper," Tian Feng also believes that future token prices will decline. He thinks that, in the short term, the rise in compute power prices stems from supply-demand mismatches. But from a semiconductor cycle perspective, manufacturing has capacity cycles: after expansion, new capacity is released in a concentrated manner, market supply and demand are disrupted, and prices fall, even leading to overcapacity. Regarding energy, China is advancing its new energy transformation, which could further reduce energy costs. In the medium term, prices depend on the capabilities of foundational models—new versions iterated every three months often address unmet needs and release new demands, pushing up compute prices; in the long term, it depends on the evolution of reasoning capabilities, ultimately leading to a sustained decrease in compute costs. Over the past two years, supply and demand have alternated in prominence. Tian Feng said that DeepSeek represents a peak in cost reduction through innovation, while the explosive productivity of "lobster" models creates a demand peak. "But this doesn't mean that during demand surges, reasoning costs don't decrease; it just means that the speed of demand growth exceeds the rate of reasoning cost decline. In 3-5 years, overall compute costs and token fees will drop sharply." Yao Xin said that AI has entered a "singularity moment," "entering a period of tenfold or hundredfold rapid growth within the next one or two years. Industries unprepared for this growth will face shortages in the short term. But like ripples, it will gradually spread and eventually stabilize." Behind the rising token prices, the business logic is also changing. Nvidia CEO Jensen Huang has repeatedly mentioned the "five-layer cake" structure of AI: "The five layers are energy, chips, infrastructure, models, and applications, with the top layer providing the greatest economic dividends." "Current AI is like the internet in 2000—people didn't really understand what the internet could do, but countless individuals invested in building various websites," said Hou Shengli. "As applications and innovations continue, by 2005 or 2006, more 'Internet+' scenarios emerged, and various services gradually integrated." The development of AI is similarly promising. As widely predicted, 2026 will become the year of intelligent agents, with a proliferation of intelligent agent applications this year. These intelligent agents are now embedded in smartphones, computers, and even factory production lines. "Everyone's demand for AI to boost productivity is almost endless; the only limit is price. When prices rise, demand drops; when prices fall, demand rises," Tian Feng said. Even now, large companies do not treat price increases uniformly. "On one hand, they raise cloud computing prices for B-end (enterprise) clients; on the other hand, they offer limited-time free trials or token giveaways to C-end (consumer) markets." Tian Feng admitted that current situations resemble the early days of the internet: while capturing users is the ultimate goal, the more critical battle is for developers. In the past, developers were global programmers; now, many non-technical personnel possess Vibe Coding skills. They are both consumers and creators of code. When big companies lock in developers, they ensure that the results of development stay on their cloud. Major internet companies are providing token quotas to employees to encourage AI use. According to Jiemian News, Alibaba is promoting an internal program that offers token quotas to employees, encouraging them to use advanced AI models and tools in their work. Employees can use paid AI tools like Wukong and the Qoder intelligent agent programming platform for free, with the company providing token quotas. Employees purchasing Balian Coding Plan memberships or external AI development tools can apply for reimbursement. Use cases for AI efficiency are not limited to programming; broader content creation and professional office tasks also generate token demand. MiniMax has even upgraded its original Coding Plan to support MiniMax multimodal models with a Token Plan, seizing token opportunities. "Frankly, there aren't many urgent needs for model development, so most adopt a monthly subscription model. Tokens are gaining attention because metrics like monthly user growth and per-user token consumption directly reflect revenue growth," Tian Feng said. This creates strong user stickiness: as long as the product is good enough, users are willing to pay a premium for a better experience. Moreover, the same 5 million tokens can be sold for 22 yuan or 400 yuan, with the premium directly linked to the base model and agent capabilities. Tian Feng believes that fundamentally, tokens are like an untapped gold mine.
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GateUser-bd883c58

GateUser-bd883c58

11 hours ago
Ask AI · Why Soaring Funding for Moonshot AI Is Prompting a Reassessment of Its Listing? China Business News Reporter Li Kunkun Li Zhenghao Beijing Report Wu Qing: In less than three months, the issue of Kimi’s parent company—Moonshot AI—going public has taken a U-turn. In a company-wide letter to all employees at the end of 2025, Moonshot AI founder Yang Zhilin wrote: “We are not in a hurry to go public in the short term, and going public is not our purpose.” The backdrop is that Moonshot AI had just completed a $500 million Series C funding round at that time, with a valuation of more than $4 billion and cash on the books of over 10 billion RMB. By the end of March 2026, media outlets citing people with knowledge of the matter reported that Moonshot AI was evaluating the possibility of listing in Hong Kong and had already been in touch with China International Capital Corporation and Goldman Sachs regarding listing matters. A reporter from China Business News contacted the Moonshot AI team regarding its preparations for going public and its development plans. The company claimed, “There is no information we can provide.” However, an internal employee at Moonshot AI revealed that the company had been conducting various internal reviews since the end of last year, including cost accounting. Over the past three months, what caused Moonshot AI to change its plan? First, in February 2026, Moonshot AI completed another $700 million of financing, and it has recently been pushing forward a new round of $1 billion financing; industry chatter suggests its post-investment valuation could surge to $18 billion. Second, Zhipu AI and MiniMax—both also in the domestic “first tier” of large model companies—had already listed on Hong Kong equities in January 2026, and after listing their stock prices have continued to rise; their valuations are currently stable at around $40 billion. In addition, 2026 has been defined by capital markets as the year of IPOs: private companies with a total value of about $2.9 trillion are preparing to go public. AI is the main character here, and the market window does not wait for anyone. **Performance Reversal** According to Tianyancha, at the end of 2025, Kimi completed a $500 million Series C funding round, with a post-investment valuation of $4.3 billion. During this year’s Spring Festival period, it raised more than $700 million, with a valuation of $10 billion. It is now in the process of a new round of $1 billion financing. At the beginning of 2025, DeepSeek burst onto the scene. With its high-performance, low-cost advantages brought by the MoE architecture and its fully open-source strategy, it sparked a wave both domestically and internationally, stirring up the entire industry. The impact on Kimi was direct and obvious. At that time, the company was facing industry criticism over “burning money to acquire customers,” and later Moonshot AI significantly cut its product placement budget. According to QuestMobile data, Kimi App’s monthly active users fell from 21.653 million in Q1 2025 to 9.027 million in Q4 2025. By the end of 2025, even some tech media used “monthly active users are less than 5% of Doubao” as a standard to put Kimi into the discussion lineup of “the most fallen AI companies.” At the beginning of 2026, the Lobster OpenClaw went viral. It allows all large models to be equipped with “hands and feet,” enabling AI to make a core leap from answering questions to completing tasks. And what surprised the industry was that the one standing at the center of this wave—having taken in enormous dividends—was the long-dormant Kimi. In February 2026, OpenClaw announced that it would set Kimi K2.5 as its official flagship model. This decision became the key turning point in Kimi’s comeback. Kimi K2.5 was officially released and open-sourced—Moonshot AI’s “killer move” after shifting strategy. Built on a trillion-parameter foundation, it uses 15 trillion visual-and-text mixed tokens for native multimodal training, making important progress in areas such as agent intelligence, code generation, and visual understanding. A few weeks later, the Kimi official website also launched Kimi Claw, directly moving the agent entry point into the browser. Previously, multiple media outlets reported that since the end of January this year, under the dual impact of the explosive popularity of the Kimi K2.5 model and Kimi Claw, it was revealed that Kimi’s total revenue in the past 20 days had already exceeded its total revenue for all of 2025. According to data from global payments giant Stripe, the number of payment orders from Kimi’s individual subscription users surged 8,280% month-over-month in January 2026, and rose another 123.8% month-over-month in February. Kimi’s ranking on Stripe’s global leaderboard jumped from outside the top 100 to 9th place, becoming the first Chinese AGI product to enter the top ten of that list. As reported by Jiemian News on March 30, just one month after the release of K2.5, Moonshot AI’s ARR (annual recurring revenue) had already exceeded $100 million, making it the first company among the “AI Six Little Tigers” (Zhipu AI, MiniMax, Baichuan Intelligence, Moonshot AI, Step Star, and Zero One All Things) to reach that milestone. Worth noting is that after the launch of K2.5, Kimi’s overseas revenue has surpassed domestic revenue: overseas API revenue grew 4x, and the month-over-month growth rate of global paying users exceeded 170%. **A Bright Future Ahead** Now, CoreWeave has already gone public on the U.S. stock market, raising $1.5 billion. Anthropic’s valuation has soared to $380 billion, and it is planning a super IPO to raise more than $60 billion. OpenAI, with a valuation of $830 billion, is pushing forward with its listing plan. Global AI companies are collectively sprinting toward capital markets. Meanwhile, Zhipu and MiniMax both listed on the Hong Kong stock market in January 2026. After listing, their stock prices continued to rise, and their market caps have remained stable at around $40 billion—demonstrating that the Hong Kong Exchanges and Clearing’s Chapter 18C (the listing mechanism for specialized technology companies) is a feasible channel for unprofitable AI companies. But the window for Hong Kong listings may not stay open forever. Currently, besides overseas markets, there are also many domestic large model companies. How can Kimi stand out? Speaking about Kimi’s strengths and weaknesses, senior columnist Ma Jipeng told reporters: “I think this large model is, at present, moving from general-purpose toward differentiation. It can roughly be divided into two tiers: one is the big internet companies, including Tencent, ByteDance, Alibaba, and Baidu; the other is startups, including Kimi, Zhipu AI, and so on. Compared to them, Kimi’s advantage mainly lies in its handling of long texts. In academia—and in some fields where there is strong demand for long-text processing—there is still substantial demand. Doubao’s influence on the consumer side, including its ability to process videos and images, might be even stronger.” Regarding its development goals for 2026, Yang Zhilin also mentioned in a public letter at the end of 2025: “Achieve growth in revenue scale at a magnitude level; in product and commercialization, focus on Agent; do not take absolute user numbers as the goal, but pursue the ceiling of intelligence and create greater value in productivity.” Yang Zhilin recently also said that starting from 2026, and in the coming years, the way AI R&D is conducted will undergo major changes: more of the research will be led by AI itself. Each researcher will be equipped with a large number of AI Tokens, and these AI Tokens can help them synthesize new tasks, synthesize new environments, help the company define what the best and most suitable reward function is in that environment, and even help the company explore what new network architectures could look like. “Personally, I’m still optimistic about Kimi’s future prospects. Because its current operating performance is good, and its development momentum is also quite strong. This is a relatively good path to verticalize within its own domain, avoiding direct competition with these giants. Its total user base may not be that large, but by going deep into an industry and fully understanding it, there is still real potential,” Ma Jipeng said. For Kimi, if it wants to achieve a high valuation in the market after listing, it must prove to the market that the growth in its Token consumption is sustainable and not dependent on short-term explosive surges in a single agent scenario; that its revenue growth can be translated into a continuous improvement in gross margin, rather than simply chasing volume by cutting prices.
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Chainwire

Chainwire

15 hours ago
Zhipu shares rose more than 5% at the open and reached another all-time high. The stock has gained nearly 800% since listing.
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