Moonshot AI IPO Buzz Builds After Kimi, Alibaba Jolt Bitcoin

Just days after the Kimi K3 model shook semiconductor stocks, Moonshot AI is accelerating plans for a Hong Kong IPO that could value the company at over $30 billion, while Alibaba is pushing ahead with an open-weight release of its Qwen model.

Moonshot AI is targeting a public listing within the next six months, moving quickly to access capital markets following the strong impact of its Kimi K3 launch, which challenged perceptions about how far China’s AI capabilities lag behind global leaders.

According to a Bloomberg report on Monday, the company has circulated a shareholder resolution seeking approval for a Hong Kong listing — a clear signal that an IPO could materialize within half a year. At the same time, Moonshot is finalizing a new funding round that may lift its valuation beyond $30 billion, up from the $20 billion mark set during a Meituan-backed round in May.

The push comes alongside rapid growth in key business metrics. Moonshot’s annual recurring revenue climbed to $300 million in June, rising sharply from $200 million in April.

Demand for its K3 model has surged so quickly that the company briefly halted new subscriptions over the weekend, as capacity struggled to keep up. Daily sales have reportedly increased at least sixfold since the model’s debut last week.

K3 is central to the company’s momentum and explains why its IPO outlook looks markedly stronger than it did just a month ago. The open-weight model has outperformed nearly all competitors — trailing only Anthropic’s Claude Fable 5 and OpenAI’s GPT-5.6 on select benchmarks — and even led a widely followed coding test. Its release triggered a selloff in semiconductor stocks on Friday, a move that also weighed on crypto markets.

Moonshot is not the only player making moves. Alibaba announced on Sunday that its Qwen3.8 model will also adopt an open-weight approach. The system, which features 2.4 trillion parameters, is positioned by the company as second only to Fable 5 among leading-edge models. A preview version, Qwen3.8-Max, is already available through Alibaba’s developer platforms.

Open-weight models allow users to run AI systems without paying licensing fees, putting pressure on the pricing strategies of U.S. providers that charge based on usage.

Parameters, which refer to the internal variables adjusted during training, are often used as a rough indicator of a model’s scale and capability. Today’s most advanced systems contain billions or even trillions of these parameters.

Meanwhile, Bitcoin has increasingly traded in line with the AI investment cycle throughout the month. Many crypto mining firms have repositioned themselves as data center operators for AI workloads, making their revenues closely tied to sustained demand for computing power.

The next major signal will come this week, as companies like Alphabet, Tesla, and Intel release earnings reports that could reveal whether AI spending continues to rise — and whether the miners pivoting toward AI infrastructure can maintain their momentum.