State of Open Models: Summer 2026 Observations
Hugging Face 2. Attention ≠ Adoption 3.
Open weights shift where value accumulates 4. Qwen has become the community’s base model 5. Small models remain the practical layer 6. Agents are the new user Looking forward Notes on method In the AI world, time feels compressed. A few months after our spring report in our biannual analysis worked through the ecosystem, there are quite a few findings that we have observed until this summer. This report lays out these observations from January to August 2026 and presents the data behind each one. Models and datasets on HF hub are growing on a daily basis. Public model repositories grew from 2.43 to 2.96 million over the period, datasets from 711,000 to 1 million, Spaces from 1.00 to 1.44 million. The distribution underneath stays extreme, roughly 85.6% of models have fewer than 200 lifetime downloads, and 1.5% of repositories account for 99.2% of all downloads. Everything below happens inside that shape. There used to be a clear progression path: labs would start by releasing smaller models and gradually work their way toward the top end of the scale. In 2026, several Chinese labs skipped this progression entirely. In almost every month of 2026, the largest and most performant open model from a Chinese lab was larger than anything an American lab released of its own. China’s monthly ceiling ran between 754B and 2.78 trillion parameters; America’s own ceiling stayed under 130B in five of seven months, the exception being NVIDIA’s Nemotron 3 Ultra at 561B in May and June, and Inkling from Thinking Machines Lab. The chart splits the labs into two camps.
