From $300 million to $35 billion, Moonshot AI Knocks on the Door of Global Top-Tier AI with Open-Source Models

Original author: Sleepy

Kimi has just open-sourced the model weights for K3, and Moonshot AI's new financing round has also been finalized.

According to an exclusive report from a reporter at the STAR Market Daily, Moonshot AI has completed its Series F financing round, raising over $3.5 billion, with a post-money valuation reaching $35 billion.

This round was not originally planned to raise this much capital. Reports indicate that due to investor subscriptions exceeding the original target by more than three times, Moonshot AI closed its Series F round early. Consequently, the Series G round, originally scheduled to launch in August this year, has also been brought forward.

The Series G round will serve as the Pre-IPO round before Moonshot AI's listing, with the pre-money valuation already rising to $50 billion.

Just a week ago, the market rumor was that Moonshot AI would complete a financing round at a pre-money valuation of approximately $31.5 billion, followed by a final private placement round in August. Now, the Series F round has ultimately raised over $3.5 billion, achieving a post-money valuation of $35 billion, with the next round no longer waiting until August. Both the capital and the valuation have arrived faster than originally planned.

Since its founding in 2023, Moonshot AI has taken only a little over three years to propel its valuation from $300 million to $35 billion. The ongoing Pre-IPO round has already placed the next price tag at $50 billion.

Over a dozen funding rounds in three years, valuation surges from $300 million to $35 billion

Moonshot AI was founded in April 2023 by Yang Zhilin, Zhang Yutao, Zhou Xinyu, and Wu Yuxin.

About two months after its establishment, the company completed an angel round of over $200 million, with a post-money valuation of around $300 million. For an AI startup whose product was not yet officially launched, this was an exceptionally large early-stage financing round.

What truly propelled Moonshot AI to the center of the capital table was its Series A+ financing round completed in February 2024.

This round raised over $1 billion, led by Alibaba, with participation from institutions and industrial capital including Sequoia China, Xiaohongshu, and Meituan, pushing Moonshot AI's valuation to approximately $2.5 billion. Half a year later, a Series B round raised over $300 million, and the company's valuation continued to rise to $3.3 billion.

However, after that 2024 financing round, Moonshot AI's fundraising pace once slowed down.

That year witnessed significant changes in China's large model market. Tech giants like ByteDance and Alibaba persistently lowered model prices, DeepSeek rapidly rose with its open-source approach and cost efficiency, and competition among general chat products gradually shifted from user growth to model capability, inference costs, and commercial revenue. Kimi initially stood out with its long-context capabilities, but relying on a single product label had become increasingly difficult to sustain a higher valuation.

It wasn't until the end of 2025 that Moonshot AI completed a $500 million Series C round, achieving a post-money valuation of $4.3 billion. Subsequently, the company's fundraising significantly accelerated.

In the first two months of 2026, Moonshot AI completed multiple financing rounds in succession, with its valuation climbing from the previous $4.3 billion to $10 billion, and further reaching $18 billion.

In May of this year, the company completed a Series D round of approximately $2 billion, reaching a post-money valuation of $20 billion. Participants were no longer limited to internet companies and market-oriented investment institutions; China Mobile, Guozhitou, CPE Yuanfeng, and several state-backed funds also joined the shareholder list.

Shortly after the Series D round concluded, a new round was launched in June. At that time, the market rumor placed the pre-money valuation at $31.5 billion. Now, this round has ultimately closed with a fundraising scale exceeding $3.5 billion, raising Moonshot AI's post-money valuation to $35 billion.

Looking back at this fundraising curve, the most significant changes have occurred in the past six months.

At the end of 2025, Moonshot AI's valuation was still $4.3 billion. Over six months later, that figure has reached $35 billion, a more than seven-fold increase. If the next round is completed at a pre-money valuation of $50 billion, Moonshot AI's valuation growth over its three-plus years of existence will exceed 160 times.

The reasoning from capital providers is also becoming more direct. Previously, investors were betting on Yang Zhilin and a team of Tsinghua-affiliated technical talent. Now, they are betting on whether Moonshot AI can become one of the few Chinese companies remaining at the table with globally cutting-edge models.

After K3, Moonshot AI Returns to the Center of the Table

The early closure of this financing round coincides precisely with the release of Kimi K3.

On July 16, Moonshot AI released Kimi K3. On July 27, the company further open-sourced K3's complete model weights, technical report, and some key infrastructure technology.

K3 is a Mixture-of-Experts (MoE) model with a total of 2.8 trillion parameters, activating 104 billion parameters per inference. It supports a 1 million token context window and possesses capabilities in vision, coding, reasoning, and prolonged tool use.

In its technical report, Moonshot AI stated that K3 achieves cutting-edge performance on tasks involving long-context coding, agent functionality, knowledge, reasoning, and vision. Its overall capability is very close to the strongest closed-source models, Claude Fable 5 and GPT-5.6 Sol.

Leaderboards change frequently, and one must be cautious of model companies' own benchmarks. K3's more significant impact is that it has pushed forward the capability frontier of open-weight models.

For a long time, open-source models often played the role of followers. Closed-source companies trained the strongest models, and six months or a year later, the open-source community would replicate parts of that capability at a lower cost.

K3 has changed this time lag. A Chinese company has directly open-sourced a model with capabilities close to the global frontier, allowing other developers to download, modify, deploy it, or continue training their own models based on it.

This certainly doesn't mean the model has become cheap. K3's weight files exceed 1.5 TB, and simply loading the complete model requires multiple high-end accelerator cards. Deploying it for production environments could involve substantial hardware investment. Its "openness" primarily addresses whether enterprises can truly own and control the model and avoid dependence on a single API provider; it doesn't imply everyone can run it on their home computer.

Even so, open weights will inevitably impact the business of closed-source companies.

When a sufficiently capable model can be downloaded, enterprises gain the opportunity to deploy it on their own servers, keep data in-house, customize the model, and avoid perpetually paying token prices set by a single company. The barriers that closed-source models previously relied on due to their leading capabilities will be eroded more quickly.

Therefore, after K3's release, the debate quickly moved beyond technical leaderboards into a clash of policy and commercial interests within the US AI industry.

Behind the Open-Source vs. Closed-Source Debate

On July 24, companies and institutions including OpenAI, Google, Microsoft, Nvidia, AMD, Meta, and Hugging Face publicly expressed support for open-weight models, opposing the US government's rush to restrict AI models available for download and deployment.

Anthropic and Amazon were absent from the signatory list. This immediately led to external speculation that Anthropic might be using security and national security as a pretext to limit the development of open models and shield its own closed-source business from competitors.

On the very day K3's weights were open-sourced, Anthropic CEO Dario Amodei published an article addressing the controversy.

He stated that Anthropic never advocated for a blanket ban on open-weight models. Open models that lack dangerous capabilities are a public good, reducing usage costs and creating value for enterprises, developers, and researchers.

However, Amodei's core position remains unchanged.

He continues to advocate for restricting the flow of advanced chips and chip manufacturing equipment to China, combating what he calls "industrial-scale model distillation," and requiring mandatory safety testing for sufficiently capable models before release, regardless of whether they are open or closed source.

While ostensibly about security, this debate also has a very tangible business dimension underneath.

Closed-source companies want to continue controlling the strongest models, charging fees through APIs and subscription services. Open models, on the other hand, disseminate capabilities to more companies, drive down prices, and shorten the distance between latecomers and industry leaders. The faster the open-sourcing, the harder it is for a few companies to lock away the most advanced capabilities within their own servers indefinitely.

K3 originates from China, is of significant scale, and its capabilities are already close to the frontier. For supporters of open models, K3 proves that the open route can still produce top-tier models. For Anthropic, it also signifies that the capability advantages built by US companies at immense cost could potentially be diffused at a faster pace.

As a result, Moonshot AI has gained a new form of capital value it previously lacked.

It is no longer just an AI application company with a large Chinese user base, nor is it merely a foundational model startup awaiting a mature business model. After the release of K3, it began to be revalued within the context of multiple competitions: global open-source versus closed-source, US versus China, and model capability versus computing power control.

The $3.5 billion financing round and the $35 billion valuation are the capital market's answer to this new reality.

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