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Rhodium Group published a report analyzing the financial performance of seven major Chinese AI developers, including DeepSeek, Moonshot AI, Z.ai, MiniMax, Alibaba, ByteDance, and Kuaishou. The report estimates that these companies generated a combined annual recurring revenue (ARR) of approximately US$10.7 billion between March and August. In comparison, OpenAI and Anthropic reported combined ARR exceeding US$100 billion during the same period. The report highlights a significant valuation-to-revenue disparity, noting that Chinese firms like DeepSeek and Moonshot have valuation-to-ARR multiples of 163x and 50x, respectively, compared to 34x for OpenAI and 21x for Anthropic. While revenues are growing rapidly, with Z.ai reporting a 400% year-on-year increase, the report suggests that open- strategies are complicating monetization efforts for Chinese developers.
Rhodium Group, a US-based research firm, released a report on Thursday detailing the financial metrics of seven major Chinese AI developers. The study calculated that these companies, which include DeepSeek, Moonshot AI, Z.ai, MiniMax, Alibaba Group Holding, ByteDance, and Kuaishou Technology, generated a combined annual recurring revenue (ARR) of approximately US$10.7 billion from March to August.
This figure represents roughly 10% of the combined ARR reported by OpenAI and Anthropic, which exceeded US$100 billion during the same period. Specifically, OpenAI reached US$40 billion in ARR in August, while Anthropic was at US$65 billion in July. Among the Chinese developers, ByteDance led the group with US$4 billion in ARR as of July, followed by Alibaba at US$2.4 billion in August.
The report highlights a stark contrast in valuation relative to revenue. Rhodium noted that the valuation-to-ARR multiples for DeepSeek and Moonshot stood at 163 times and 50 times, respectively. In comparison, OpenAI’s multiple was 34 times and Anthropic’s was 21 times. The report described these Chinese valuations as 'exorbitant' relative to their current revenue streams, even though they remain substantially lower in absolute terms than US counterparts.
Despite the revenue gap, Chinese AI companies are experiencing rapid growth. Z.ai reported a 400% year-on-year increase in first-half revenue to 953.9 million yuan, while MiniMax’s revenue surged 283% to US$116.6 million. However, Macquarie Group’s head of Asia internet and software research, Ellie Jiang, told the South China Morning Post that Z.ai and MiniMax could remain loss-making through 2030 due to the high costs of computing power required to maintain technological competitiveness.
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This report provides a concrete financial for the competitive landscape between US and Chinese AI industries. It reveals that despite aggressive investment and high valuations, Chinese AI companies are currently generating a fraction of the revenue of their US counterparts. This gap raises questions about the sustainability of current valuations and the effectiveness of open- strategies in generating direct revenue. For investors and policymakers, these figures offer a clearer picture of the economic reality behind the technological race, highlighting that while Chinese models are narrowing the performance gap, the business models supporting them are still maturing and face distinct monetization challenges compared to the closed-source, subscription-heavy models of OpenAI and Anthropic.
The report underscores a central challenge for China’s AI industry: converting technological parity into sustainable business models. While Chinese developers have rapidly narrowed the performance gap with US counterparts, their revenue generation lags significantly behind. This discrepancy suggests that the current investment cycle in Chinese AI is driven more by strategic positioning and market share acquisition than by immediate profitability.
A key factor complicating monetization is the widespread adoption of open-source and open- models by Chinese developers. Rhodium noted that this strategy makes it difficult for original developers to capture revenue, as third-party cloud providers can deploy these models and sell access without paying the creators. This stands in contrast to the closed-source, subscription-based models of OpenAI and Anthropic, which allow for more direct revenue capture.
The financial data provides a critical for investors evaluating the risk profile of Chinese AI stocks. The high valuation-to-revenue multiples indicate that investors are pricing in significant future growth or strategic value that is not yet reflected in current earnings. This creates a potential vulnerability if growth slows or if the cost of maintaining technological leadership continues to outpace revenue growth.
The report also highlights the evolving nature of AI business models, particularly regarding open- strategies. As Chinese firms like Moonshot and Alibaba push for revenue-sharing agreements with major users, the industry may see a shift in how open-source AI is monetized. This could have broader implications for the global AI market, potentially influencing how other developers approach open-weight releases.
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Bincika fasahar da ke bayan wannan ci gaban ta hanyar mu'amala.
Which component of an AI application is the machine-learning model itself?
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Investors should monitor whether Chinese AI companies can successfully implement revenue-sharing agreements for their open- models, as discussed by Rhodium. Additionally, the upcoming IPOs of Moonshot AI and potential listings for other major players will test market appetite for these high-multiple valuations. The ability of these firms to convert rapid user adoption into sustainable profitability without incurring unsustainable computing costs will be a key indicator of the long-term viability of the Chinese AI sector.
The implementation of revenue-sharing agreements for open- models will be a key indicator of whether Chinese AI companies can improve their monetization efficiency. Rhodium noted that Moonshot is in discussions with Microsoft, Amazon, and Google, with potential revenue shares reaching up to 30%. The success of these negotiations could serve as a model for other developers.
Upcoming initial public offerings (IPOs) for Chinese AI firms, such as Moonshot AI’s confidential filing for a Hong Kong IPO and DeepSeek’s pre-IPO funding round, will test market confidence in these high valuations. The reception of these listings will provide insight into whether investors are willing to sustain high multiples in the face of limited current revenue.
The ability of Chinese AI companies to manage computing costs while maintaining technological competitiveness will be crucial. As noted by Macquarie Group, the high cost of computing power could keep companies like Z.ai and MiniMax in the red through 2030. Monitoring their cost structures and efficiency improvements will be essential for assessing long-term viability.
The competitive dynamics between US and Chinese AI developers will continue to evolve, with both sides competing on price, performance, and open-source adoption. The report’s findings suggest that while the performance gap is narrowing, the economic gap remains significant. Future developments in pricing strategies and model releases will be key to understanding how this dynamic plays out.