Originally published on AI Tech Connect.
What you need to know Qwen leads every distribution metric in the report. 2,045M downloads in 2026 across repositories with declared parameter counts; 39.6M GGUF pulls a month against Gemma's 20.8M and Llama's 7.5M; 151,448 derivative models on the Hub against Google's 82,506 and Meta's roughly 58,000. The licence split is the decision-relevant fact. Of Chinese releases above 20B parameters, 59% are Apache 2.0 and 22% are MIT. Of American labs' releases, 29% are Apache or MIT, 41% carry custom terms and 30% declare no licence at all. Nobody downloads the frontier. Models under 1B parameters account for 83% of all-time downloads. Models above 100B account for 1%. In 2026 alone, only 3% of download volume came from anything above 70B. The parameter ceiling gap is real but nearly irrelevant…
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