❯ Hugging Face: Qwen derivative models top 151,000, 2.6x Meta’s count

ECOSYSTEM DATAHugging Face’s open-source model report, published on its official blog, shows derivative models based on Alibaba’s Qwen on the platform have reached 151,448 — 2.6x the derivative count of all Meta models and 4.7x the Llama series. Google ranks second with 82,506. These are downstream products built by other developers, excluding versions released by Qwen itself.

GROWTH PACEThe report shows that in the first seven months of 2026, Qwen derivative repositories grew steadily at a pace of 180 to 210 per day — driven not by a single release spike, but by a pattern in which developers now default to Qwen as their starting point for fine-tuning. Over the same period, Alibaba reported cumulative Qwen downloads surpassing 3 billion, exceeding the open-source model totals of Google and Meta. Hugging Face also noted in the same report that Chinese open-source models’ overall share on the platform has overtaken that of the United States.

STRUCTURAL IMPACTDerivative counts reveal stickiness better than downloads: a download can be a trial run, but a derivative is committed engineering investment — quantization versions, inference kernels, and deployment scripts stacked layer upon layer on the same base model, with switching costs compounding. Teams choosing a fine-tuning base now face the option with the most complete toolchain — ecosystem depth itself is starting to dictate technical selection, rather than the other way around.

▪ SIGNALThe decisive factor in open-source competition isn’t benchmark scores — it’s how many people have already written code on your model that they can’t easily rewrite.