Alibaba’s reported plan to seek revenue-sharing agreements from major commercial users of its next open-weight artificial intelligence model marks an important change in the economics of open AI. The company appears to be trying to preserve the rapid adoption created by freely available model weights while capturing part of the commercial value generated by businesses that build profitable services around them. The strategy could give Alibaba a new source of AI revenue, but it also risks challenging the very openness that helped Qwen become widely adopted.

The planned approach, reported by people familiar with Alibaba’s strategy, is expected to apply to major users of the upcoming Qwen3.8-Max model. Rather than charging every developer a conventional licensing fee, Alibaba is considering requiring large commercial users to share part of the revenue generated from services built around the model. The precise rate has not been finalized, according to the report.

That distinction is important. Alibaba has historically allowed many users to download and run its open models in their own infrastructure without paying a direct model fee, while monetizing usage when customers run those models through Alibaba Cloud. The new approach would potentially extend monetization beyond Alibaba’s own cloud infrastructure and into third-party businesses that commercialize Qwen independently.

Open AI Is Becoming a Business Model

The assumption that open models must remain free is increasingly being challenged by the development of more sophisticated licensing structures. Open-weight models can be downloaded and deployed by companies without necessarily requiring the developer to provide computing infrastructure. That creates enormous opportunities for adoption, but it also creates a problem for model developers: competitors can capture the commercial value generated by the model while the original creator carries the cost of research, training and development.

Alibaba’s proposed solution is to separate access from commercialization. Developers could still benefit from the availability of the model, but companies generating substantial revenue from commercial services could face additional obligations. In economic terms, the strategy resembles a freemium structure in which widespread access is used to build an ecosystem while the largest commercial beneficiaries become the principal source of revenue.

The approach follows a similar move by Chinese artificial intelligence company Moonshot AI, whose Kimi K3 licensing terms reportedly require commercial agreements from businesses exceeding a specified revenue threshold. The model demonstrates that Chinese AI developers are experimenting with ways to reconcile open distribution with the enormous cost of developing advanced models.

For Alibaba, the attraction is obvious. Qwen has already achieved significant adoption, with Alibaba reporting more than one billion cumulative downloads by early 2026 and a large ecosystem of derivative models. The company therefore has an installed base that could potentially be converted into commercial relationships without abandoning the distribution strategy that created it.

The Real Target Is Commercial Scale

Alibaba’s reported strategy appears designed less for ordinary developers than for companies turning Qwen into businesses. That distinction could allow the company to preserve much of the openness that attracts researchers and smaller developers while concentrating monetization on organizations that have demonstrated commercial success.

This is strategically important because AI model developers are competing for ecosystem influence as much as immediate revenue. A model used by thousands of developers can become embedded in applications, enterprise systems and infrastructure. Once that happens, the model developer can potentially earn money from cloud services, support, customization, inference, partnerships and future versions.

Alibaba already has a particularly strong position in this regard because it controls more than just the model layer. Its businesses include cloud computing, AI infrastructure, proprietary chips, model services and consumer applications. The company has said that its cloud business has become increasingly dependent on AI-related demand, with external cloud revenue growing 40 percent in the final quarter of its 2026 financial year.

That makes Qwen strategically different from an independent model laboratory. Alibaba can use the model to generate demand for other parts of its technology ecosystem even when the model itself is distributed widely.

Alibaba Wants Open Distribution Without Giving Away Everything

The central challenge is finding the boundary between openness and monetization. If licensing conditions become too restrictive, developers may decide that another model offers greater freedom. Open AI users often value the ability to modify, host and distribute models without negotiating commercial arrangements every time an application becomes successful.

Alibaba therefore has an incentive to avoid making Qwen appear less open than competing models. The reported revenue-sharing strategy could be designed to target only large commercial deployments, leaving smaller users with relatively broad access.

That would create a two-level ecosystem. Developers could experiment and build applications around Qwen at low cost, while large businesses that generate significant revenue would contribute financially to the model developer. Such a system could potentially align Alibaba’s interests with those of its most successful customers: the more commercially valuable the ecosystem becomes, the more revenue could flow back to Alibaba.

The risk is that companies may respond by shifting toward alternative models or attempting to avoid contractual thresholds. Enforcement could also become complicated when businesses operate across multiple jurisdictions, combine several models in one product or generate revenue indirectly from AI-powered services.

Cloud Remains Alibaba’s Strongest Monetization Route

The reported licensing plan should not be viewed as a replacement for Alibaba Cloud. It is more likely to complement the company’s existing strategy. Alibaba has repeatedly emphasized that open models can still generate substantial economic value when customers train, fine-tune and run them on its infrastructure.

That is one of the fundamental advantages of Alibaba’s full-stack approach. Even when the model weights are available outside the company’s own cloud, customers still need computing power, storage, networking, inference capacity and technical services to operate large AI systems at scale.

Alibaba has invested heavily in those areas. The company has said that AI-related products have become a major growth engine for its cloud division and that it expects AI-related revenue to represent more than half of the division’s external revenue within approximately a year.

This means the reported revenue-sharing proposal could represent another layer of monetization rather than a fundamental change in the company’s AI strategy. Alibaba can potentially earn from the model itself, from cloud infrastructure used to operate it, and from enterprise services built around the broader AI ecosystem.

Chinese AI Competition Is Driving the Shift

The timing also reflects the increasingly competitive Chinese AI market. Chinese companies have demonstrated that high-performing open-weight models can be distributed at significantly lower prices than many proprietary alternatives. That creates pressure on United States AI companies while simultaneously forcing Chinese developers to find sustainable ways to finance increasingly expensive research.

The competition is therefore no longer simply about which company can produce the strongest model. It is also about which company can create the most effective economic system around that model.

Alibaba’s reported strategy suggests that model distribution is becoming a customer-acquisition tool. An open model can spread rapidly because developers can experiment with it without paying conventional API prices. Once businesses build products around it, however, the model creator has an opportunity to sell additional services or negotiate commercial arrangements.

That approach could become increasingly common if AI models become more interchangeable. When performance differences narrow, developers may choose models according to price, licensing freedom, computing requirements and ecosystem support rather than technical capability alone.

The Model Creator Is Becoming an Ecosystem Owner

Alibaba’s reported Qwen strategy ultimately reflects a larger change in the AI industry. The value of a foundation model is increasingly difficult to capture through model access alone. Companies therefore need to build ecosystems around their models that generate revenue at several points in the technology stack.

Alibaba has an unusually strong opportunity because Qwen sits inside a broader technology empire. Its cloud infrastructure can host the model, its chips can provide computing capacity, its enterprise tools can incorporate it, and its consumer applications can create additional demand. The company’s own disclosures indicate that AI has moved from a major investment area toward a commercialization phase across these businesses.

The reported revenue-sharing plan is therefore best understood as an attempt to capture value from Qwen’s success without sacrificing the adoption advantages of open distribution. The strategy could work if Alibaba keeps the threshold for commercial payments high enough to preserve developer interest while making the largest commercial deployments financially meaningful.

But the balance will be delicate. Open AI succeeds partly because users believe they have meaningful freedom to build on it. If commercial restrictions become too burdensome, the same openness that helped Qwen spread could become its competitive weakness.

Alibaba’s challenge is consequently not simply to monetize Qwen. It is to prove that an open model can remain widely accessible while its creator captures enough of the economic value generated by the ecosystem. If that balance can be maintained, Qwen could become more than a widely used model: it could become the foundation of a commercial AI ecosystem in which openness drives adoption and scale ultimately drives revenue.

(Adapted from TradingView.com)