On the Artificial Analysis Intelligence Index (Sept 14, 2026), Z.ai's GLM-5.3 (45) and GLM-5.3-Flash (42) and Moonshot's Kimi K3 (44) beat the top US open models: Thinking Machines' Inkling (26) and Nvidia's Nemotron 3 Ultra (23), per author Nathan Lambert.
OpenRouter's open-model traffic grew from about 1T tokenThe chunk of text a model reads and writes in — roughly three-quarters of a word — and the unit AI usage is billed in.Full definition →/week in September 2025 to about 80T tokens/week today, with Chinese models' share of that usage rising from about 70% to over 80% over the same period, Lambert reports.
Scanning arXiv's five top ML categories, Lambert found mentions of any open model rose from 2% of papers in January 2023 to 50% in September 2026, with Chinese models now cited in over 40% of papers versus 30% for the US, reversing Llama's earlier lead.
Lambert estimates that fully blocking distillationTraining a small, cheap model to imitate a big one's outputs, keeping much of the capability at a fraction of the cost.Full definition → of US model outputs, e.g. via know-your-customer checks at OpenAI and Anthropic, would widen the Chinese-to-American open-model gap by only 1-2 months, since distillation isn't the main driver of Chinese labs' progress.
Chinese open weightsA model whose trained parameters are published for anyone to download and run — unlike API-only models you can access but never possess.Full definition → models trail the closed US frontier by roughly 2-5 months while open-weight US models trail OpenAI and Anthropic by about 6-9 months; Chinese labs are closest on agentic coding, furthest behind on open-ended science like physics or biology.
Terms in this piece · Glossary
open weights — A model whose trained parameters are published for anyone to download and run — unlike API-only models you can access but never possess.
token — The chunk of text a model reads and writes in — roughly three-quarters of a word — and the unit AI usage is billed in.
distillation — Training a small, cheap model to imitate a big one's outputs, keeping much of the capability at a fraction of the cost.
Why it matters
Lays out why Chinese labs have led open-weight model releases since roughly April 2025 and clarifies the open-source vs. open-weight distinction that shapes what practitioners can legally build on.
