The current balance of power in open models
Chinese openâweight models now outpace U.S. ones in downloads, benchmarks, and industry use, reshaping the AI landscape.

Why Now
The article reports that since midâ2025 Chinese labs have overtaken U.S. labs in openâweight model performance and adoption, highlighted by download stats and benchmark scores.
What Happened
Chinese openâweight models such as GLMâ5.3, GLMâ5.3âFlash, and Kimi K3 lead the Artificial Analysis Intelligence Index with scores 45â44, while top U.S. models score 23â26. Downloads on Hugging Face show Chinaâs lead grew to 1.6âŻB out of 3.2âŻB total, double the U.S. share. Openâweight models are widely used by U.S. companies (e.g., DoorDash, Airbnb) and in academia, with Chinese models cited in 30% of recent arXiv papers.
Why It Matters
This shift gives Chinese labs a competitive edge in agentic coding and other highâimpact tasks, while U.S. firms increasingly rely on Chinese models for costâeffective AI features. It also raises regulatory and security concerns, as openâweight models are harder to control and can be used by bad actors.
The Limitation
The analysis relies on public download and benchmark data, which may not fully capture private deployments or the true quality of models across all tasks.
What You Can Do
Benchmark your own workloads against Chinese openâweight models to assess performance gaps and consider sourcing models from U.S. openâsource projects for greater control.
Source
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