Alibaba's Qwen models have surpassed the 3 billion download mark: the phenomenon of open AI
Chinese tech giant Alibaba has reached an impressive milestone: over the past six months, the total number of downloads of their open-source AI models from the Qwen family has exceeded 3 billion. The company made this announcement during an official release, highlighting the scale of global adoption of its developments.
To date, the corporation has provided the community with more than 460 neural networks in open access. Moreover, developers worldwide have created about 300,000 derivative models based on them, indicating the deep integration of Qwen into the AI development ecosystem.
Hugging Face Analytics: Numbers and Trends
The Hugging Face platform, which serves as the main hub for open-source AI, has published its semi-annual report shedding light on this phenomenon. According to the platform's data, over seven months of the current year, the Qwen model was downloaded 2.05 billion times, and the number of forks (derivative repositories) created from it reached 151,448. For comparison, Google's corresponding figure stands at 82,506.
Hugging Face statistics also show that Google model downloads in 2026 amounted to 418 million, while Meta's totaled 227 million. It is important to understand that these figures reflect activity only within the platform itself, excluding API requests, private cloud deployments, and corporate use outside the Hugging Face ecosystem. The report's authors rightly caution against interpreting this data as a direct market share, yet the trend is evident.
The dynamics deserve special attention: the number of Qwen derivative repositories is growing by 180–210 daily. The community's contribution is also telling: out of 28,531 GGUF conversions of these models (a format for local deployment), only 54 were created by Alibaba itself, with the rest being the work of enthusiasts. As noted at Hugging Face, "Qwen has become part of the standard workflow for developers choosing which model to fine-tune and deploy."
The Secret to Success: Scaling Strategy
Qwen's superiority over competitors is explained by three key factors. First, a regular update cycle. Second, coverage of all scales—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 removes all restrictions on modification and commercial use.
The decisive factor turned out to be the breadth of the model lineup. According to Hugging Face data, versions with fewer than 1 billion parameters account for a massive 83% of all downloads in the platform's history, while giant neural networks exceeding 100 billion account for only 1%. This explains the lag of laboratories focused solely on large LLMs. For example, Moonshot AI, which releases almost no models smaller than 70 billion, gathered only 37 million downloads over the year—roughly 55 times fewer than Qwen.
Alibaba also dominates the local deployment segment: its GGUF builds are downloaded 39.6 million times per month, while Gemma (Google) stands at 20.8 million and Llama (Meta) at just 7.5 million.
Geopolitics of Open AI
The report revealed a shift in the balance of power: in almost every month of the current year, the largest open model from China surpassed all US releases in size. The parameter ceiling for Chinese models ranged from 754 billion to 2.78 trillion, while for American competitors it did not exceed 130 billion in five out of seven months.
Licensing policies also differ radically. In China, 59% of models with more than 20 billion parameters are released under Apache 2.0, 22% under MIT, and none of them have restrictions on commercial use. In the US, the picture is different: only 29% are under open licenses (Apache/MIT), 41% under proprietary terms, and 30% without any license specified at all.
Interestingly, in the US, the leaders in the number of new open models were not AI laboratories but chip manufacturers: AMD and Nvidia each released more than 200 repositories, noticeably outpacing Google and Meta.
My view: Qwen's success is not just statistics but a demonstration of a paradigm shift. Chinese companies have bet on the future of AI lying in edge computing and local deployment, not only in giant data centers. Alibaba's strategy, offering models for every taste under the most open license possible, creates a network effect that competitors will find extremely difficult to overcome. This is not a race for flagships but a war for the developer ecosystem, and for now, China is winning it.