Alibaba tests new business model for Qwen open-source AI

Alibaba plans to introduce revenue-sharing terms for some commercial users of its next Qwen open-weight AI model, Reuters reported, citing two people familiar with the company’s plans.

The arrangement would require larger companies that generate revenue from offering the model as a service to reach a commercial agreement with Alibaba. The exact revenue-sharing rate has not been finalised, the sources said.

Alibaba is expected to introduce the measure with its next open-source model. The company has previously charged developers to access models hosted through its cloud platform, while generally allowing customers to deploy its open-source models in their own data centres without paying licensing fees.

The proposed arrangement would differ from the licensing used for the current Qwen3 open-weight models, which Alibaba says are released under the Apache 2.0 licence. The licence permits commercial use, modification, and redistribution subject to its conditions.

Open-source versus open-weight

Open-weight models make their trained parameters available for download, but that does not necessarily mean every part of the AI system is open or that all forms of commercial use are unrestricted.

Under the Open Source Initiative’s Open Source AI Definition, an open-source AI system should allow users to use, study, modify, and share it for any purpose without seeking permission. OSI’s definition also requires access to information about training data, relevant code, and model parameters.

Alibaba and other Chinese AI developers have released large models with downloadable weights. OpenAI, Anthropic, and Google, by comparison, primarily distribute their main commercial models through closed systems and hosted services.

Alibaba’s planned terms resemble the licensing model adopted by Chinese AI developer Moonshot for Kimi K3, an open-weight model released last month. Its licence includes separate conditions for companies operating Model-as-a-Service businesses above certain revenue thresholds.

Under Kimi K3’s published licence, a company operating such a service must reach a separate agreement with Moonshot when the combined revenue of the company and its affiliates exceeds $20 million during any consecutive 12-month period. The provision applies to commercial use of Kimi K3 and derivative models.

The licence contains another requirement for large consumer-facing deployments. Commercial products exceeding either 100 million monthly active users or $20 million in monthly revenue must prominently display the Kimi K3 name, with exemptions covering internal use and services offered through Moonshot or certified inference partners.

According to two people familiar with Moonshot’s commercial arrangements, those agreements can include revenue sharing. One source said Moonshot can require partners to share up to 30% of the revenue involved.

Chinese IT services company Chinasoft International disclosed a revenue-sharing agreement with Moonshot in a regulatory filing last month. It did not disclose the percentage involved.

DigitalOcean Holdings is also among the companies offering Kimi K3 and other Chinese models. Chief Executive Paddy Srinivasan confirmed that DigitalOcean has a commercial agreement with Moonshot but declined to provide details.

Srinivasan described the approach as an open-source “freemium” model, where companies can access software at little or no initial cost before paying for larger-scale commercial use, technical services, or earlier access to future releases.

The cost of running open models at scale

Companies can download an open-weight model without paying for access to an API, but large models still require substantial computing infrastructure when deployed at scale.

Kimi K3 contains 2.8 trillion total parameters and 104 billion activated parameters, according to Moonshot. Its mixture-of-experts architecture includes 896 experts, with 16 selected for each token.

The model’s size still places substantial hardware requirements on operators. Moonshot temporarily stopped accepting new Kimi K3 subscriptions in July after saying usage had placed pressure on its available GPUs, while Reuters reported that relatively few users were expected to self-host a model of that scale because of the infrastructure required.

Alibaba is using a similar architectural approach with Qwen3.8-Max. The model contains about 2.4 trillion parameters but activates around 95 billion parameters for each request, according to Reuters.

Moonshot says its mixture-of-experts design improves scaling efficiency by activating only a subset of the model’s experts for each token, rather than the full model.

Cloud providers can charge for hosting and inference, while AI infrastructure companies can generate revenue from deployment and optimisation services.

Dan Fu, vice president of kernels at Together AI, said companies providing AI services can differentiate their offerings through areas such as more efficient token use and deployment optimisation.

“At the application layer, there’s value out there for how you use it, how you actually get the models and the tokens to do something useful,” Fu said.

Model development presents a separate cost challenge. Research involving Epoch AI and Stanford researchers estimated that the cost of the most compute-intensive training runs had risen by about 2.4 times a year since 2016, while Stanford’s 2025 AI Index found that the price of accessing models at a given capability level had fallen sharply.

At published API prices at the time of release, Kimi K3 was priced at about one-third of Anthropic’s Fable model based on listed input and output token rates. Pricing is only one part of the deployment cost, particularly for companies running models on dedicated infrastructure or handling high volumes of requests.

These costs sit alongside the licensing arrangements being tested by model developers. Alibaba already charges developers that access Qwen through Alibaba Cloud. The proposed arrangement would also allow it to collect revenue from some companies deploying Qwen independently on their own infrastructure or through third-party services.

Moonshot has already attached commercial conditions to Kimi K3 while keeping its model weights available for download. DigitalOcean and Chinasoft International have both disclosed commercial arrangements with Moonshot, although the financial terms have not been made public.

The commercial arrangements are developing alongside wider tensions between China and the US over AI technology. The White House has accused Moonshot of using technology taken from Anthropic while developing its models, an allegation Chinese officials have rejected.

Interest in releasing models with downloadable weights is not limited to Chinese developers. Thinking Machines Lab, the San Francisco AI company founded by former OpenAI Chief Technology Officer Mira Murati, released its first open-source model last month.

Lin Qiao, chief executive and co-founder of Fireworks AI, said there was no fundamental technical barrier preventing US developers from releasing more capable open-source models. Fireworks AI works with models from developers including Moonshot, although Qiao declined to discuss its commercial arrangements.

Alibaba has not publicly announced the final licence for its next Qwen model or the revenue-sharing percentage it plans to seek from large commercial users.

(Photo by: Alibaba)

See also: Alibaba, DeepSeek push China’s AI model race towards lower costs

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