In China’s hyper-competitive and lucrative tech industry, releasing cutting-edge artificial intelligence models for free may seem counter-intuitive – but it has become a core business strategy.

At the University of Hong Kong last November, Alibaba Group Holding chairman Joe Tsai was asked why the tech giant open-sourced its AI models.

Addressing a room full of students, Tsai said he believed open-source AI would bring global benefits by lowering costs, making it a natural fit for talent- and cash-poor countries.

The company’s flagship AI model, Qwen, has achieved nearly 1 billion cumulative downloads over the past three years, making it by far the most popular open-source model family worldwide.

Tsai’s interviewer Tang Heiwai, associate dean of the university’s business school, wanted to know what that meant in terms of profit.

“How do you guys make money by being so generous?” he asked, smiling.

“We don’t make money from AI, that’s the answer,” Tsai responded, referring to the company’s models.

His matter-of-fact remark reflects the company’s stance: while Alibaba, owner of the South China Morning Post, monetises inference and cloud services, it has still made open-source AI a central part of its corporate identity.

The question of how to monetise these models, which by their nature hold no intellectual property protections that would allow for straightforward profit-making, has been a recurrent one over the past year.

In China, the emergence of DeepSeek early last year sparked a wave of open-source models, with domestic start-ups MiniMax and Zhipu AI riding the wave all the way to blockbuster listings in Hong Kong.

The question has resurfaced in recent weeks during earnings season, as several companies – including Alibaba and Zhipu – released some of their latest models as closed-source software.

This followed the high-profile departure of Qwen’s technical lead, Lin Junyang, a fervent open-source advocate, prompting speculation that Alibaba was abandoning its previous strategy in favour of monetisation.

But open source and monetisation are not necessarily in conflict, several analysts said in interviews.

The key, said Daniel Yue – an assistant professor at the Georgia Institute of Technology’s Scheller College of Business, who researches open-source business strategies – is recognising that AI models are only one layer in a product’s broader “stack”.

Most AI companies, he noted, are pursuing a hybrid approach that combines open- and closed-source elements.

An old playbook AI models are served to users through a process called inference, in which powerful graphics processing units (GPUs) provide the computational power to run them.

While open-source models are made freely available, deploying and fine-tuning them on local hardware can cost users thousands of US dollars and demands a great deal of technical expertise.

Instead, model developers often provide the inference themselves – a form of “indirect monetisation”.

In his November talk, Tsai compared this to staying at a hotel: rather than building it themselves, customers effectively rent one and pay for additional services, such as room service or spa treatment.

Similarly, Chinese cloud giants such as Alibaba and Tencent Holdings monetise open-source models by renting out their GPUs to users.

“Most people don’t want to deal with installing, updating and debugging an open-source version of anything,” said Kevin Xu, founder of technology hedge fund Interconnected Capital and a former senior director at open-source platform GitHub.

Chinese players are ...

trying to make their models as abundant as possible, then monetising them in a more incremental way Zhang Jiang, freelance consultant advising AI startups Inference providers can also charge enterprises for premium features, such as security and optimisation.

In 2002, legendary software engineer Joel Spolsky summarised this open-source business strategy as “commoditising your complement”: that is, making one layer of the value chain cheap or free to capture the value flowing to another layer.

The approach has succeeded with other foundational software, the most famous example being Google’s open-source Android for smartphones and other devices, which helped make it the default mobile ecosystem for billions of users.

That, in turn, entrenched Google’s search engine, further cementing its grip on the market.

Alibaba’s cloud business offers another example.

According to research firm Omdia, Alibaba Cloud holds about 36 per cent of China’s market share, making it the dominant player.

Cloud revenue has been the company’s biggest growth driver since 2024, a year after it began open-sourcing Qwen.

But the strategy has limits.

Zhang Jiang, a freelance consultant advising AI startups on capital raising and former director of equity research at UBS, said open-source strategies can be challenging, as intense competition – both domestically and from US models – puts downward pressure on prices.

According to Alibaba’s latest earnings report, its cloud computing margins remain in the single digits.

By contrast, US companies that develop closed-source models, such as OpenAI and Anthropic, enjoy margins of about 40 to 50 per cent, as their exclusive control over inference gives them greater pricing power.

“What the US players are doing....