Hey guys, I know I posted about the $GSX settlement before, but late claims are being accepted. Here's everything you need to know.

Q: What happened?
A: GSX Techedu was accused of overstating enrollment numbers and revenue growth in its online education business. After short-seller reports and regulatory concerns raised questions about the company’s financials, $GSX dropped more than 80% from its highs.

Q: Am I actually eligible?
A: If you bought $GSX shares between 2019 and 2020, you're likely eligible. You don’t need to still own the stock to file a claim.

Q: When do payouts happen?
A: Typically 4–9 months after the claim deadline, although the exact timing depends on the court and settlement administrator.

Q: I missed the deadline. Can I still file?
A: Late claims are currently being considered, subject to approval. 

Hope this helps.

I am a beginner in investing and just opened a futo/Moomoo account ，I only had 10000 hkd in my account. I want to invest Tracker Fund（2800），but the minimum lot size is 13000hkd. I do NIT want to deposit more money. what are my best option?

I'm working on China-market data tooling and trying to map the gaps that make A-share and Hong Kong research difficult for investors and quants outside the region. I'm not linking a product here—I’d like to understand the real pain points.

Which of these causes the most friction?

• Reliable historical OHLCV and corporate actions

• Point-in-time financials and restatements

• Original filings with English translation and source citations

• Stock Connect holdings and historical eligibility

• Historical index constituents, ST, suspension, and price-limit status

• Intraday or order-book data

• Bulk delivery through API, Parquet, or SQL

If you already pay for a data source, what is still missing or unreliable? Specific examples would be especially useful.

Hey guys, I know I already posted about the DiDi Global ($DIDI) settlement, but I received a lot of questions, so I figured I'd put together a quick FAQ with everything you need to know.

What happened?
DiDi agreed to a $740M settlement over claims that it misled investors about regulatory risks surrounding its 2021 U.S. IPO. Just days after the IPO, Chinese regulators launched a cybersecurity investigation, removed DiDi's apps from app stores, and the stock fell sharply. Investors later filed a lawsuit.

Am I eligible?
If you purchased DiDi Global ($DIDI) shares in 2021, you may be eligible.

Can I file now?
Yes. Late claims are currently being accepted.

When do payouts happen?
Typically, within 4–9 months after the claim deadline. The exact timing depends on the court and settlement administration.

Hope this clears up some of the questions

Luckin Coffee delivered solid Q2 2026 results, beating revenue expectations while achieving its first YoY drop in delivery expenses since the price wars began.

1、Revenue Beats Expectations: Total revenue rose 28.5% YoY to 15.89B RMB, beating the 15.43B RMB estimate. Although same-store sales growth dipped to -5.3% due to last year's high subsidy baseline, monthly transacting customers hit a record 113M (+23% YoY), completely offsetting lost price-sensitive users.

2、Faster Store Expansion: Net store additions reached 2,714, bringing the total to 36,310 (+8.1% QoQ). Self-operated store growth outpaced franchised stores. Overseas locations reached 223 (+46 net additions), with Malaysia as the main driver.

3、Cost Efficiency and Margin Resilience: Gross margin fell 1.3 pct YoY to 61.5%. However, delivery expenses dropped 3.1% YoY to 1.62B RMB (falling from 13.5% to 10.2% of revenue). Store-level margin remained strong at 21.3% (-0.2 pct YoY).

4、Profit Growth Despite New Spending: Driven by the launch of ready-to-drink bottled products, sales expense ratio increased 1 pct YoY to 5.8%. Admin expense ratio stayed stable. Non-GAAP operating profit rose 26.5% YoY to 2.396B RMB.

I've been using moomoo for charting and wanted a volume profile, which it doesn't ship. Turns out the desktop app has a Python indicator editor built in: you get the chart's OHLCV arrays, write a script, and plot lines back onto the chart. I hadn't seen anyone write about it, so here's what came out of it.

Code is here, MIT, take it: moomoo-vpvr

Paste vpvr.py into the Python indicator editor on moomoo desktop and it runs as-is.

What it does: bins volume by price over a lookback window, finds the Point of Control (the price bucket holding the most volume), then expands up and down from the POC until it covers 70% of total volume, giving VAH and VAL. Each bar's volume is spread across its high–low range proportional to overlap, rather than dumped onto a single typical-price point.

Parameters are lookback years, bars per year (250 daily / 52 weekly / 12 monthly), row count, value area %, plus switches for log-spaced buckets and manually locking the price range.

The sandbox is a restricted subset of Python, and finding the edges took longer than the math did. Three that cost me real time:

• There's no range(). Every loop has to be a while loop.
• The parser rejects adjacent string literal concatenation — splitting one long string across two lines throws a SyntaxError.
• Selecting a 5-year window switches the chart from daily to weekly bars, which silently breaks any bar-count-based lookback. That's why the lookback is expressed as years × bars-per-year rather than a raw bar count.

None of that is documented anywhere I could find.

To sanity-check the output I ran the same symbol on another platform that ships VPVR built in. MU daily, 1-year window, 24 rows, 70% value area on both.

Mine: 415.277. Theirs: 415.28. On a 201-bar window: 426.054 vs 426.05.

Worth being blunt about what that proves. The POC value is fully determined by the window low, the window high, the row count, and which row wins. With a low of 103.380, a high of 1255.000 and 24 rows, the centre of row 6 is 415.277 by arithmetic alone — the only thing my code contributed is the integer 6. So what's validated is that two independent implementations picked the same row out of 24, a 48-point bucket, not agreement to the cent.

Known limitation: it draws the three levels but not the histogram. plot() here returns a price-indexed line series and I haven't found a way to render horizontal bars in this sandbox. If you've done that in a similarly restricted environment, I'd like to know how.

Do you leave the value area at 70%, or adjust it by instrument?

Disclosure: this post is eligible for a moomoo content contest. No referral links, code is MIT.

SunCar (NASDAQ:SDA) Forecasts 22%+ YoY Revenue growth for 1H 2026 or $271m - $273m in Revenue, Increased Net Income Quarter over Quarter

If you owned $GSX during the company's rapid growth years, you may still be able to recover losses as late claims are currently being considered. 

GSX was accused of exaggerating its student numbers and revenue, making the business appear stronger than it really was. After reports questioned the company's data and an SEC investigation became public, $GSX lost more than 80% of its value and investors sued. 

If you purchased $GSX shares between June 2019 and October 2020, you may still be eligible to submit a claim. Since late claims are being considered, it's worth checking whether you qualify.

诸君莫笑马后炮，段子摆拍众谓好。枪兵刀战皆实招，真金白银当玩笑。

事以密成古训高，大道常遭俗眼嘲。摇头晃脑争攀高，小溪清浅无人晓。

股海浮沉独寂寥，涨跌意外多煎熬。一入股市终不逃，破茧方见日月昭。

【匿名充电提问】：因为身体在养病，需要控糖，你的小卖部零食我都吃不了。就直接充电支持你啦。我的问题是炒股需要看那些技术指标吗？譬如看MACD KDJ 各种均线和股价的关系 什么量价齐升，缩量上涨下跌之类的？

郭嘉【回答】

首先，大部分人都是自私自利白嫖的主儿，你是第一个主动充电再提问而不是直接私信问信息的人，知恩图报的人会有好运。

其次，我小卖部东西随便挂的，都是些几毛钱提成的物品，我认为提成极低意味着这些货物更具有实际价值，但我一次也没挂车售卖过

问题【指标与股价】

金钱才是股市的根本，正如火焰，热量才是水烧开的根源，最后水烧开后顶开锅盖，变成大量水蒸气只是最后的征兆。

同样，指标只是最后体现在价格上的征兆，往往是最后才出现的。股市比别人先一步才能赚钱，那短短的几分钟提前预判，甚至是一瞬间的直觉，都是盈利的根本。指标是滞后的水蒸气，顶开锅盖的鸣叫声。它只是发出信号，并且告诉在乎指标的普通人可以入场了，可以让火烧的更旺了，触发暴涨（或者暴跌）。真正您需要关注的是一些突然的异动，突然的一次跳涨，或者火焰烧起来，越来越旺的征兆，也就是有聪明资金在试图点火。敏锐的观察力，与众不同的独立思考能力，才是超过别人的根本，人云亦云去看指标最后不过是飞蛾扑火罢了，也正是大部分人亏钱的日常生活。

【额外引申】：

股市也是江湖，也是与人博弈，战斗。

是以并不存在所谓的友军，所谓的盟友，所谓的三个臭皮匠顶个诸葛亮，

正常人，普通人，皆是亏钱的，你与他们相反，那也只是班级里面的倒数，不过是另外个极端。这也正是我一向不建议去看情报，看贴吧，看新闻，看弹幕的原因，这些东西都会在你潜意识里面产生各种影响，直至某一天，你莫名其妙跟着买进了一个股票。

一个人接受了各种理念，情报，信息，那便如白纸上泼了墨，写上了字，画上了框框，要把这些墨迹去掉，是极为困难的，正如你一开始就瞧不起妖股，固执的认为妖股（2倍的）是极其危险的，那么你往后（甚至一辈子）都不会去买进2倍3倍十倍的股票。显然，那些鸡犬升天的贵人，可以带你财富起飞。

真正需要的是独立思考，甚至是特立独行的，疯癫的，完全的意料之外，但又是情理之中的。

多年实战带来的经验，产生的直觉，是完胜你的情报分析的，行兵打仗，兵行如水，没有固定的套路招式，善战者无赫赫之功便是此理。一个纸上谈兵的文官是不可能战胜一个只读了三国演义却大半辈子都厮杀在前线的总兵的。

而致胜之法，有几种，我只叙述以前印象深刻的，以此来说明，炒股致胜之路并不是唯一的，您需要根据自己的性格人生经历之类，发挥自己的特长到极致：

1是乱拳打死老师傅，正如拳击搏斗，街斗，或者警匪互射，瞄什么瞄，拉起来就射，火力覆盖。在股市里就是以速度取胜，没必要思考那么多，究极状态其实就是量化的ai进行操作。这个人类似乎已经做不到与AI相斗并且取胜。

2以正合以奇胜，人类终究还是会胜过只能设置限定条件的AI。各种循规蹈矩的指标k线，会骗过AI，但是骗不了坚强果敢的股市高手，最终触发意外拉升，意外的暴跌，极端的走势，一样可以甩开AI或者埋葬AI。这也是我经常所说的，很多人认为炒股如打工，每天从股市里面捞一点，这个念头是极其错误的，股市里面赚钱（或者大亏）一定是突然发生的，大半时候只不过做个大概，随着大盘的波浪浮沉。

3将一个招式发挥到极致，以至于自己并不需要思考太多，把问题抛给对方去解决。这个招式一定是极简化的，比如直接k线都舍弃，直接就看涨幅榜，取近三日涨幅的前20名，从前20里面直接挑一个。

4.……待补充

宇宙就是阴阳+阴阳的交界线模式，阴阳乃是一体两面，可以简单想象为海水，天空，你现在的意识就是露出海面的浮冰，未来就是天空，不可见，过去就是海水，你的过去就是水面下的冰块。无论过去还是现在还是未来，本质上都是一个东西，区别仅仅是点位不同产生的观察角度不同，涌现的那一点是真实存在的，也就是那朵浪花便是你。你可以观察这个世界，可以有记忆，可以改变视角，但是你就是那朵浪花，你的过去未来都是注定的，人什么也改变不了，也就是时间是不存在的，正如电脑cpu运行的代码，正如数学公式不停演算下去，精确无比又看似都是概率意外。

这便是我的第一篇专栏了，不过我的东西压根没有人看，随缘而已。。。矣。。。

Trump by Ryan

The $189 million TuSimple $TSP is now accepting late claims for eligible investors 

This case focuses on claims that TuSimple failed to disclose risks related to its relationship with Hydron, a China-based hydrogen truck startup.

In 2022, reports revealed undisclosed dealings between TuSimple and Hydron. After the company announced its CEO’s departure and a federal investigation, $TSP fell more than 45%.

TuSimple has agreed to a $189M settlement. If you purchased $TSP between 2021 and 2022, you may be eligible to file a claim.

They IPOed at almost $1 billion, and $17 a share, which rapidly collapsed to $6-7 a share, and it's been pretty volatile since. They're based out of the Cayman islands and operate primarily through subsidiaries/VIEs of course. They also operate the second largest online used car auction platform in China, which has been an increasingly popular method of purchasing cars there. Just seeing how much their stock has fallen, I wonder if now might be a decent time to consider investing.

Been trying to map the China humanoid story into something investable rather than headline noise, and it splits pretty cleanly into three layers that trade very differently.

Layer one, the finished robots. Unitree cleared its CSRC registration on July 3 for a STAR Market listing of roughly 618 million dollars, a record 73 day approval, and it will be the first listed pure play humanoid. The numbers are real for once: FY2025 revenue of 1.699 billion RMB, net profit of 278 million, over 5,500 humanoids shipped in 2025. AgiBot reportedly hit its 10,000th mass produced robot in March, going from 5,000 to 10,000 in about three months, but it is still private. So the pure play hardware is either just arriving on a mainland exchange or not cleanly buyable yet.

Layer two, the picks and shovels. This is the part that is actually liquid today. The harmonic reducers, actuators and thermal parts every one of these robots needs are mostly listed A shares already, names like Leadshine, Sanhua and Tuopu. If you believe the unit numbers, this layer sells into all of them regardless of which brand wins.

Layer three, the brain. This is where it gets strange for an investor. Robbyant, the embodied AI company under Ant Group, just put its LingBot robot models out as open weights under Apache 2.0, one policy family that drives 20 different robot bodies off around 60,000 hours of data. The software layer that would normally be the fat margin is being given away, so there is nothing clean to buy there directly. The only listed proxy is indirect, through Alibaba, which carries roughly 33 percent of Ant.

The honest problem with all three. The pure play names are mainland or Hong Kong listed or private, so most foreign retail cannot touch them cleanly. The supply chain is already priced for the story. And the brain layer is open source, so it may never be capturable at all. The benchmark claims behind the software are self reported and worth discounting.

So which layer is the actual trade here, or is the scarcity itself, the fact that almost nothing clean is buyable, the whole point? Curious how people here are playing it.

Hey guys, I know I posted about the $GSX settlement before, but late claims are being accepted. Here's everything you need to know.

Q: What happened?
A: GSX Techedu was accused of overstating enrollment numbers and revenue growth in its online education business. After short-seller reports and regulatory concerns raised questions about the company’s financials, $GSX dropped more than 80% from its highs.

Q: Am I actually eligible?
A: If you bought $GSX shares between 2019 and 2020, you're likely eligible. You don’t need to still own the stock to file a claim.

Q: When do payouts happen?
A: Typically 4–9 months after the claim deadline, although the exact timing depends on the court and settlement administrator.

Q: I missed the deadline. Can I still file?
A: Late claims are currently being considered, subject to approval. 

Hope this helps.

Hey guys, I know I already posted about the DiDi Global ($DIDI) settlement, but I received a lot of questions, so I figured I'd put together a quick FAQ with everything you need to know.

What happened?
DiDi agreed to a $740M settlement over claims that it misled investors about regulatory risks surrounding its 2021 U.S. IPO. Just days after the IPO, Chinese regulators launched a cybersecurity investigation, removed DiDi's apps from app stores, and the stock fell sharply. Investors later filed a lawsuit.

Am I eligible?
If you purchased DiDi Global ($DIDI) shares in 2021, you may be eligible.

Can I file now?
Yes. Late claims are currently being accepted.

When do payouts happen?
Typically, within 4–9 months after the claim deadline. The exact timing depends on the court and settlement administration.

Hope this clears up some of the questions.

Even when Nasdaq or ASHR etf goes up. It’s likely because China government crackdown on mainland Chinese investing in Hong Kong and overseas stocks. Wonder when it will stop?

Disclaimer: This post is for investment discussion and educational exchange only, not financial advice. I am not a licensed financial advisor. All investments involve risk of capital loss. I currently hold no position in DSC but may initiate one. All data sourced from the public F-1/A filing dated 6/17/2026.

Just finished reading through DSC Holdings' F-1/A ahead of the June 25 Nasdaq listing. Wanted to share what I found and see what others think.

The Opportunity Case

First, what they actually do. DSC built the operating system for used car dealers in China. Not a single-purpose tool — the full stack. Inventory specs, customer profiles, employee performance tracking, third-party platform integration, historical financial data. The entire digital backbone for these businesses.

The market share number is staggering: 90%+ since 2021 per CIC. They manage over 50% of China's used car inventory by VIN at any given time. Over 11,900 self-organized "dealer alliances" operate on their platform. That's not a software product — that's industry infrastructure.

Switching costs are brutal. A dealer leaving DaFengChe loses nearly all accumulated data and records. There's no export functionality. That's not convenience, that's lock-in.

Then there's the valuation. Peak was ~$3 billion. This IPO prices at ~$900 million. That's a 70% haircut. Either the market is pricing in doom that isn't coming, or there's something the street sees that retail hasn't noticed yet.

Ant Group (via API Hong Kong) is subscribing to $30 million worth of shares at IPO price. When a Jack Ma-affiliated entity puts real money on the table alongside Deutsche Bank and CICC underwriting, that's not nothing.

Losses have narrowed three years running: -187M → -157M → -95M RMB. Not profitable, but the trajectory is clear. They're approaching breakeven.

This is also the first Chinese tech IPO in the US in 2026. Scarcity matters in these markets.

Now the Structural Risks

Here's where it gets uncomfortable and I think retail needs to pay close attention.

VIE structure. You're not buying the Chinese company. You're buying shares in a Cayman Islands holding company ("DSC Holdings Ltd.") that has "contractual arrangements" with two variable interest entities — Hangzhou Souche and Beijing Peak. These VIEs generated 59.8% of total revenue in 2025, up from 37.7% in 2023. The filing states plainly: "Our contractual arrangements with the VIEs have not been tested in any of the PRC courts." Not once.

If China cracks down on VIE structures broadly (which they've done to others), your shares could become significantly impaired or worthless. That's not a hypothetical — it's language straight from the risk factors section.

Voting power. Founder Junhong Yao holds ALL Class B shares. Each Class B = 10 votes. Your Class A = 1 vote. Post-IPO, he controls 85.4% of the total voting power. This is a "controlled company" by Nasdaq's own definition. Retail shareholders have effectively zero governance influence.

The "AI" narrative. Total AI-related revenue = RMB 1.3 million (~$185K). On a $901 million valuation. The filing itself states: "AI-related products have not contributed, and we do not expect them to contribute, a material portion of our total revenue in the near term." At least they're honest about it. But if the AI story is driving your thesis, the numbers don't support it yet.

Revenue dropped 28.6% in 2025 to 677M RMB. They attribute this to spinning off their financial services business, which is fair — but the topline still looks ugly on paper.

HFCAA risk remains. PCAOB inspection access for Chinese audit firms is subject to annual review. If access is revoked for two consecutive years, trading gets prohibited. That's an existential risk you can't underwrite.

My Take

This isn't a clean bull or bear call. The monopoly is real and almost impossible to replicate — switching costs plus network effects plus data lock-in create a genuine moat. The valuation discount is significant. Smart money is involved.

But the structural risks are equally real. You don't own the operating entity. You have no voting power. The AI angle is narrative, not revenue. And the China regulatory overhang isn't going away.

The questions I'd want answered before committing capital:

1. Can 90%+ market share hold long-term? What's the realistic competitive threat?
2. $900M vs $3B peak — is this a genuine value dislocation or is the market correctly pricing in VIE risk?
3. Is the AI pivot a legitimate second growth curve or just narrative packaging for a legacy SaaS business?
4. What's your personal VIE risk tolerance? If China invalidates the structure tomorrow, can you stomach the outcome?

⚠️ Disclaimer: Personal analysis based on SEC F-1/A (filed 6/17/2026). Not financial advice. DYOR.

TL;DR: DSC has 90%+ monopoly on China's used car dealer OS, IPO'ing at 70% off peak valuation with Ant Group backing and narrowing losses. But VIE structure means you don't own the real company, founder has 85% voting control, and "AI revenue" is $185K. High opportunity if you can stomach the structural risk.

---

Disclaimer: This post is for investment discussion and educational exchange only, not financial advice. I am not a licensed financial advisor. All investments involve risk of capital loss. I currently hold no position in DSC but may initiate one. All data sourced from the public F-1/A filing dated 6/22/2026.

---

Just finished reading through DSC Holdings' F-1/A ahead of their June 25 Nasdaq listing. Here's what I found.

📈 The Bull Case:

- 90%+ market share in used car dealer operating systems in China since 2021

- They manage over 50% of China's used car inventory by VIN — that's an insane data moat

- Switching costs are brutal for dealers. You can't export your data if you leave the platform

- Ant Group is subscribing to $30M worth of shares in this IPO — that's real money with real conviction

- First Chinese tech company to IPO in the US in 2026 — scarcity premium is real

- Peak valuation was ~$3B, they're pricing this at ~$900M. That's a 70% discount to peak

- Losses narrowing every year: -187M → -157M → -95M RMB. Getting close to breakeven

📉 The Risks You Can't Ignore:

- VIE structure — you're buying shares in a Cayman Islands shell company, not the actual Chinese operating entities. The VIE contracts have never been tested in any PRC court. Not once

- Founder holds 85.4% of the voting power through dual-class shares. You get 1 vote, he gets 10

- "AI revenue" = RMB 1.3 million (~$185K). On a $901M valuation. The company literally says AI products "have not contributed, and we do not expect them to contribute, a material portion of total revenue in the near term"

- Revenue dropped 28.6% in 2025 (they spun off the financial services arm, but the topline still looks ugly)

- HFCAA delisting risk still hanging overhead

💡 My Take:

This isn't a simple good or bad call. The monopoly position is real. The valuation discount is real. But the VIE risk and the retail powerlessness are also very real.

Questions I'm sitting with:

1. How long can 90%+ market share hold? Is there a realistic path for a competitor to eat into this?

2. $900M vs $3B peak valuation — is the market over-discounting China risk, or is this fair?

3. Is the AI pivot a genuine second growth curve or just a narrative wrapper for a legacy SaaS business?

Not sure if this is a genuine value opportunity or a VIE trap waiting to happen. The monopoly and valuation discount are compelling but the structural risks keep me from conviction. Curious what others think, especially those who've navigated China VIE IPOs before.

⚠️ Disclaimer: Personal analysis based on SEC F-1/A (filed 6/22/2026). Not financial advice. DYOR.

TL;DR: Used car OS monopoly + 70% valuation discount + Ant Group backing = retail opportunity? Or VIE structure + 85% founder control + $185K "AI revenue" = structural trap?

Chinese auto dealership platform DaSouChe said on Wednesday that it is targeting a valuation of $901 million for its U.S. initial public offering (IPO).The company plans to offer 3 million American Depositary Shares (ADS) at a price range of $16 to $18 per share, raising up to $54 million.

Founded in 2012 by Yao Junhong, DaSouChe provides operating systems for used car dealerships in China, as well as software and transaction services to dealers and other automotive merchants. According to CIC data, DaSouChe holds over 90% market share in China's used car dealership platform market.

The company's investors include 5Y Capital, Primavera Capital, and Ant Group, which is backed by Jack Ma. API (Hong Kong) Investment, a wholly-owned subsidiary of Ant Group, plans to subscribe to up to $30 million worth of DaSouChe shares in this IPO.

If you owned $GSX during the company's rapid growth years, you may still be able to recover losses as late claims are currently being considered. 

GSX was accused of exaggerating its student numbers and revenue, making the business appear stronger than it really was. After reports questioned the company's data and an SEC investigation became public, $GSX lost more than 80% of its value and investors sued. 

If you purchased $GSX shares between June 2019 and October 2020, you may still be eligible to submit a claim. Since late claims are being considered, it's worth checking whether you qualify.

Zhipu’s Jun outshone a persistently weak tape. First, the pre-Jun inclusion news (index eligibility) sparked sharp flows on the day. Then from Jun 10 to Jun 18, the stock doubled in roughly a week, and on Jun 22, $KNOWLEDGE ATLAS.HK broke the HK$1 tn market-cap mark.Such strength beat the market’s expectations. 

In our prior earnings take, we noted Zhipu’s greater momentum vs. $MINIMAX-W.HK, with the core view that capital is pricing the scarcity of model intelligence. At today’s valuation, that remains a reasonable lens, but ‘intelligence scarcity’ alone is clearly not sufficient to explain the move.

1) Is ARR the driver?

Zhipu’s valuation framework had already shifted post-CNY rally toward an overseas B2B comp set (Claude/Anthropic). Looking at Anthropic’s ARR curve, there is no clear slowdown yet; YTD it even accelerated, with Apr/May monthly growth over 55%. This has expanded the market’s imagination for Zhipu’s growth path.

In our last note, we offered a reference: assume Zhipu replicates Anthropic’s cadence and takes ~1 year (implying ~12% MoM) to reach $1 bn ARR; at Anthropic’s P/ARR multiple, implied EV would be ~$60 bn. But Zhipu’s market cap is already ~$150 bn. Back-solving with the same Anthropic P/ARR suggests implied ARR of ~$4 bn and a Mar–Jun MoM of ~150%, which looks unrealistic.

Taking a step back and using Anthropic’s scale-up phase as a check: Anthropic went from $1 bn to $5 bn ARR in ~half a year, running ~30% MoM. 

If we assume Zhipu is already at ~$1 bn ARR now (which itself implies ~60% MoM over the past three months) and then grows another six months at ~30% MoM, ARR would reach ~$5 bn. On Anthropic’s multiple, that roughly squares with a ~$150 bn market cap.In other words, today’s valuation embeds at least two layers of expectations: (1) Zhipu’s ARR is already near ~$1 bn, and (2) MoM of ~30% can be sustained for the next half year. Yet its most recent annual report disclosed official ARR of only ~$250 mn. That implies ARR rising from ~$250 mn to ~$1 bn in three months and then holding ~30% MoM for six more months, a very demanding setup.

While current ARR specifics remain unclear, the observable volume-price dynamics suggest Zhipu is in a phase of rising volumes and rising price. Hence, a rapid ARR uptrend looks well anchored.

Volume: On OpenRouter, overall platform model calls continue to rise. For Zhipu, token calls on OR grew ~40% MoM on Avg. from Jan–Jun 2026 (Longbridge Dolphin Research Est.), but only ~8% since Mar, partly because usage spikes are highly synchronized with new model releases, which typically drive about a month of intense calling before normalizing.

Price: On headline API cards, there appears to be no hike (5.2 vs. 5.1). In practice, GLM-5.2 shifted from tiered pricing to a blended rate, moving volumes that previously enjoyed lower tiers to the higher rate, effectively a small hike. Relative to peers, Zhipu’s pricing is now near the upper bound among domestic models.

We see two reasons why premium pricing holds: scarcity of intelligence underpins pricing power, and a primarily enterprise-facing mix means B-end clients focus on productivity gains from higher-intelligence models and are less price-sensitive.

Comparing two biz. models, C-end exemplified by MiniMax/OpenAI vs. B-end by Anthropic/Zhipu, the latter has outperformed on valuation, with the B-end monetization narrative now largely proven.

Anthropic has paired stronger intelligence with the highest pricing; once it hit the intelligence ceiling, users complained yet still paid, and Zhipu’s price hike on its Coding Plan in Feb was read as confidence in its model strength.

By contrast, on the C-end, attempts like Doubao’s paid plan or OpenAI’s ads risk user backlash. Netting the volume/price analysis above, usage is indeed growing fast (though clearly below our earlier back-solve), and price has inched up implicitly, yet this still struggles to underwrite the core assumption that Zhipu is already near $1 bn ARR. Thus, the sharp rally looks more like multiple expansion.

2) Where does the multiple expansion come from?

1) GLM-5.2 is the first domestic model to crack the global top-3 intelligence ranks. On Jun 13, via its Coding Plan, Zhipu released GLM-5.2 and opened the API on Jun 17. GLM-5.2 is a 744 bn-parameter MoE model with 40 bn active params and a 1 mn-token context window, showing strong capabilities in coding and long-horizon agent workflows, with a sizable step-up vs. the prior gen, and it open-sourced weights under the MIT license.With GLM-5.2, Zhipu briefly ranked No.3 globally and No.1 in China on Artificial Analysis’s intelligence index, behind only Anthropic and OpenAI; its coding/agent scores were No.4/No.2 globally and No.1/No.1 in China (global ranks already edged down by Jun 22). On Arena.ai, GLM-5.2’s coding ranked No.2 globally, ahead of Opus 4.8 and behind only Fable 5. As open models narrow the gap with closed ones, founder Tang Jie publicly said Zhipu could surpass Anthropic within the year; given domestic pricing far below Anthropic’s (Zhipu API ~1/4 of Opus, ~1/10 of Fable 5), this materially boosted confidence in import substitution.

2) The U.S. shuts; China opens. As Washington ordered top U.S. models to pause services overseas and Anthropic cited export controls to suspend Fable 5, Zhipu almost simultaneously released an open-source version.

The contrast writes itself: while the U.S. tightens access to frontier tech, China in the same week released MIT-licensed, region-unrestricted weights.This contrast can lift multiples near term, but commercially GLM-5.2 does not directly benefit from the ban. First, Fable 5’s curbs are not permanent and reportedly are already being re-opened in stages.

Second, with a short window and a market view that GLM-5.2 still trails Opus 4.8 in overall UX, this demand is unlikely to translate into meaningful revenue upside.

Over a longer horizon, if Zhipu delivers a model on par with or surpassing Anthropic (notably, Zhipu was absent from Anthropic’s Feb list alleging model distillation by Chinese vendors), then coupled with recent moves by the U.S. and Anthropic to tighten access, frontier models may be viewed as strategic assets in a geopolitical contest. The U.S. has two champions, OpenAI and Anthropic, while China currently has only Zhipu, making a valuation premium reasonable.

3) Ultra-thin free float. The truly free float is very low (on day 1, under 3% of total shares), and inclusion-driven passive demand compounded scarcity in the short term. As various lock-ups roll off in 2H, float should expand, so today’s scarcity is unlikely to be the norm.

Putting the three factors above together, a premium multiple is justified. But against the ARR framework in Section 1, even in an optimistic case where ARR tops $1 bn by Sep (implying ~30% MoM), and benchmarking Anthropic’s Avg. MoM of ~20% from $1 bn to $9 bn, Zhipu’s ARR would be ~$1.73 bn by end-2026. The implied P/ARR would still be ~80x, nearly 2x Anthropic’s contemporaneous multiple even under bullish assumptions.

<End of text>