DD-滴滴

Kimi’s latest model, K3, has climbed to the top of several key benchmarks this month.
The 2.8-trillion-parameter open-weight system from Moonshot AI now matches or beats leading closed models from OpenAI and Anthropic on coding and long-context tasks.
That breakthrough has drawn fresh attention to China’s generative AI race.
Moonshot, founded in 2023 by former Meta and Google researcher Yang Zhilin, built its name on the Kimi chatbot. The company moved fast: it released the trillion-parameter K2 series in 2025, then pushed K3 in July 2026 with a million-token context window and native multimodal support. Full weights are due out by late July. Early users and independent tests show strong results in agent workflows and complex coding.
Revenue has kept pace. Annual recurring revenue crossed $200 million in April, with API sales making up more than 70 percent. Growth came from both consumer subscriptions and enterprise deals. Investors noticed. After a $4.3 billion valuation at the end of 2025, Moonshot raised roughly $2 billion in May at over $20 billion post-money, led by Meituan’s venture arm. It has now pulled in nearly $4 billion in six months and is reportedly targeting a $30 billion valuation in the next round. Backers include Alibaba, Tencent, and China Mobile.
The company is still private but has floated the idea of a Hong Kong listing. Its story shows how quickly private capital and open-weight models can scale in China when compute constraints push teams toward efficiency.
Two Listed Peers in Hong Kong
Two close rivals have already gone public on the Hong Kong exchange, giving investors direct exposure.
MiniMax focuses on multimodal generation across text, image, video, and audio. Its latest open model, M3, handles a million-token context. The company listed in January 2026 and raised about $619 million. Shares surged on debut but later pulled back sharply. In July it announced plans to raise another $2 billion through new shares and convertible bonds to fund infrastructure and model work. Customer numbers have grown quickly on both the enterprise and consumer sides.
Zhipu AI , known for its GLM models, listed around the same time. GLM-5.2, released and open-sourced earlier this year, ranks among the strongest open models globally, especially in coding and long-horizon tasks. Shares climbed fast after listing, briefly pushing market value above HK$1 trillion before moderating. In July the company raised roughly $4 billion in a share placement and is preparing a possible Shanghai STAR listing. Founder Tang Jie has signaled a long-term push toward advanced agents and AGI-level capabilities rather than quick monetization.
Both stocks have been volatile, typical for early-stage AI names. Zhipu has held up better on model momentum; MiniMax has faced more pressure from dilution and lock-up expirations.
Established Player and Broader Exposure
SenseTime offers a more mature route into the same theme. The company built its business on computer vision and has expanded into generative models through the SenseNova line. Revenue rose 33 percent last year, with generative AI contributing strongly. Analysts generally rate the stock a buy, seeing room for further gains as multimodal tools move into commercial use.
Hong Kong’s broader AI theme also includes exposure through Tencent, Alibaba, and chip names such as SMIC and Biren. Many of these groups have invested in or compete directly with the startups above.
What Wall Street Banks Are Saying
Major banks have started coverage and see clear differentiation among the players.
Goldman Sachs initiated on Zhipu with a target around HK$1,880 and picked Zhipu, DeepSeek, and ByteDance as its top Chinese model names. The bank is constructive on the full China AI value chain — power, chips, infrastructure, and models — noting that global funds remain underweight despite China’s roughly $4 trillion in related market value.
Bank of America started both Zhipu and MiniMax with Buy ratings (targets HK$1,250 and HK$500). It describes a “two-speed” global market: the U.S. leads on raw frontier performance while Chinese models win on cost and efficiency for high-volume work. BofA also flags big long-term spending on Chinese AI data centers.
JPMorgan has been the most bullish on Zhipu, raising its target multiple times to HK$2,000 and higher while keeping an Overweight rating. The bank argues the sector is moving into a “winner-takes-more” phase where the strongest open models convert wide distribution into better monetization. It has been more cautious on MiniMax.
Morgan Stanley has also lifted Zhipu targets. Other houses have issued Buys on MiniMax at times. Common threads across the reports: open weights are accelerating adoption, Chinese teams are optimizing around domestic chips, and enterprise demand is strong even as compute remains tight.
Investment Angles
Direct plays sit in the two pure-play listings. Zhipu currently carries the strongest bank support tied to its enterprise focus and open-model upside. MiniMax offers multimodal leverage but comes with more near-term share supply pressure. SenseTime gives a steadier, vision-heavy alternative with improving margins.
Indirect routes run through Tencent and Alibaba, both investors in several of these companies and developers of their own competing models. Infrastructure names add another layer for those wanting exposure to the compute build-out.
The bullish case rests on cost advantages, open-source momentum, and practical enterprise use cases. Chinese models are gaining traction on platforms outside China and in cost-sensitive markets. Continued model leadership from names like Kimi and GLM could drive further revenue growth.
Risks are straightforward:
Fierce competition inside China, repeated capital raises that dilute shareholders, high valuations, and ongoing limits on advanced chips. Execution on turning open models into sustained profits remains unproven at scale.

Russell 2000 $XIWM index analysis
As of mid-July 2026
The Russell 2000 index, made up of about 2,000 U.S. small-cap listed companies, is one of the most commonly used benchmarks for tracking U.S. small-cap stock performance. The most representative related ETF in the market is the iShares Russell 2000 ETF, ticker IWM.
Recent performance
In the first half of 2026, the Russell 2000 performed very strongly, with cumulative gains of roughly 19% to 22%, posting the best first-half performance since 1991.
In the same period, the S&P 500 index rose by about 9%. The Russell 2000 clearly outperformed large-cap stocks, and the gap in their first-half returns was also the largest since 2003.

Actually, since yesterday afternoon, many teachers and scholars—seeing the premium—were thrilled and urged people to arbitrage it.
Then it’s what’s shown in the figure.
From 1,300 points all the way down to—
Why does this happen?
Isn’t it arbitrage? Won’t it converge?
To start with the conclusion: this arbitrage is mechanically constrained by a “one-way conversion,” making the path of directly buying the primary Seoul-listed shares, converting them into ADRs, and then selling them not feasible. This is also an important reason why the SK Hynix ADR premium can persist in the long term.
This year, in July, SK Hynix issued sponsored ADRs on Nasdaq with the ticker SKHY at an offering price of $149. On the first day of listing, the ADR traded at a premium of about 16% versus the Seoul-listed ordinary shares. On Monday of this week, the premium widened to roughly 37%, but by July 14 it had narrowed to about 19%. Therefore, the 30% premium people see in the market is closer to a short-term peak; the actual price spread changes very quickly.