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Chinese tech giant Alibaba has reached an impressive milestone: the total number of downloads of its open-source AI models from the Qwen family has exceeded 3 billion over the past six months. This figure is rapidly propelling the Chinese corporation to absolute leadership in the global open artificial intelligence market, leaving giants such as Google and Meta behind.

To date, Alibaba has provided the community with more than 460 neural networks in open access, based on which developers worldwide have created about 300,000 derivative models. This is a colossal ecosystem that is shaping industry standards.

Numbers that speak for themselves

Data analysis from the leading ML community platform Hugging Face over seven months of the current year shows that Qwen models were downloaded 2.05 billion times, with the number of derivative repositories reaching 151,448. For comparison, Google's figure is only 82,506. It is important to note that Hugging Face statistics only account for activity within its own ecosystem, excluding API requests and private corporate deployments, making the real gap even more significant.

Over the entire 2026 year, downloads of Google models on the platform amounted to 418 million, and Meta's to 227 million. These figures clearly demonstrate a shift in the balance of power. Notably, the growth rate of the Qwen ecosystem is not slowing down: the number of derivative repositories increases by 180–210 daily. The community is actively involved in model adaptation—of the 28,531 GGUF conversions, only 54 were created by Alibaba itself; the rest are the work of independent developers.

The secret to success: a scaling strategy

Qwen's dominance is explained by three key factors. First, regular updates to the model lineup. Second, record-breaking breadth of coverage: from compact versions with sub-billion parameters to the flagship Qwen3.8-Max with 2.4 trillion parameters. Third, the use of the Apache 2.0 license, which imposes no restrictions on modification or commercial use.

Critically important was precisely the coverage of small models. According to statistics, versions with fewer than 1 billion parameters account for 83% of all historical platform downloads, while giant neural networks over 100 billion account for only 1%. Competitors focused exclusively on large LLMs are falling catastrophically behind. For example, Moonshot AI, which rarely releases models smaller than 70 billion parameters, has gathered only 37 million downloads over the year—55 times fewer than Qwen.

In the local deployment segment, the advantage also lies with Alibaba: Qwen GGUF builds are downloaded 39.6 million times per month, while Gemma's figure is 20.8 million, and Llama's is only 7.5 million.

The geopolitics of open AI

The reporting data confirms a fundamental shift: in almost every month of the current year, the largest Chinese open model has surpassed all American releases in size. The parameter ceiling for Chinese models ranged from 754 billion to 2.78 trillion, while for US competitors it did not exceed 130 billion in five out of seven months.

The licensing aspect is especially telling. In China, 59% of models with more than 20 billion parameters are released under Apache 2.0, 22% under MIT, and none have restrictions on commercial use. In the US, the picture is the opposite: only 29% under open licenses, 41% under proprietary terms, and 30% have no specified license at all. Notably, in the US, the leaders in the number of new open models were not AI labs but chip manufacturers—AMD and Nvidia each released more than 200 repositories.

My assessment: the rapid rise of Qwen is not just the success of a single company, but a marker of the systemic advantage of the Chinese AI development model, based on openness and pragmatic scaling. While American labs try to monetize proprietary developments, China is capturing the developer community that determines the standards of the future. This is a strategic victory whose consequences we will observe for many years to come.