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open-source models closed to within 1.70%
webred-line.ai·red-line.ai/p/state-of-open-source-ai-2025
Relevant to AI governance discussions around open-weight model release policies, export controls, and the geopolitical dimensions of AI development; provides empirical data on the shifting open-model ecosystem as of late 2025.
Metadata
Importance: 45/100blog postanalysis
Summary
A 2025 year-end analysis of open-model AI trends showing China surpassing the US in Hugging Face downloads for the first time, with Chinese models like Qwen and DeepSeek gaining significant ground. The piece examines shifts in open-weight vs. open-source dynamics, the rise of small language models, and geopolitical implications for AI governance and export controls.
Key Points
- •China surpassed the US in Hugging Face model downloads in November 2025 (17.1% vs 15.8%), with Qwen and DeepSeek accounting for 14% combined.
- •Closed models still dominate with 80% of token usage and 95% of revenue, but open-weight models set competitive baselines that affect the entire field.
- •US firms released fewer open-weight models in 2024-25 citing commercial and safety constraints, creating space for Chinese labs pursuing open-weight leadership as a catch-up strategy.
- •Open-source models closed to within 1.70% of closed model performance benchmarks, narrowing the capability gap significantly.
- •Export controls show limited effectiveness as model weights, once released, enable broad access and reverse knowledge transfer to foreign developers.
Cited by 2 pages
| Page | Type | Quality |
|---|---|---|
| AI Safety Multi-Actor Strategic Landscape | Analysis | 59.0 |
| AI Proliferation | Risk | 60.0 |
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# State of Open-Source AI, 2025
### The Brief: China ↑; US ↓; SLM/LLM ↑; open source ↓; open weight ↑; non-industry developers ↑; industry developers ↓
[](https://substack.com/@arwensmit)
[Arwen Smit](https://substack.com/@arwensmit)
Dec 04, 2025
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# The Situation: Open Model 2025 Trends Are In
As 2025 ends, open-model dynamics show a clear pattern: _US ↓, China ↑, SLM/LLM ↑, open-source ↓, open-weight ↑, non-industry developers ↑, and corporate developers ↓._
Closed models dominate 80% of token usage and 95% of revenue.[1](https://www.red-line.ai/p/state-of-open-source-ai-2025#footnote-1-180473273) Why does it matter what happens in open models?
> Because open weights determine who catches up, when, and at what cost.
* * *
# The Red Line: China Has Momentum In Open Models
## **2025 Trend I: US ↓ \| China ↑**
Until 2022, the open ecosystem was highly concentrated and US-led. Around 60% of open models originated in the US, with Google, Meta and OpenAI accounting for 40-60% of cumulative downloads. From 2022 onwards this share fell sharply.[2](https://www.red-line.ai/p/state-of-open-source-ai-2025#footnote-2-180473273)
Llama 3 outperformed Chinese open models until mid-2024. From late 2024 China’s position strengthened.
> In November 2025, Hugging Face data showed China surpassing the US in downloads for the first time (17.1% compared with 15.8%).
Qwen and DeepSeek together accounted for 14%.
Alongside these, model families such as Mistral (France), Gemma (US), Phi (US) and Yi (China) now anchor the open ecosystem.
[](https://substackcdn.com/image/fetch/$s_!wVs4!,f_auto,q_auto:good,fl_progressive:steep/https%3A%2F%2Fsubstack-post-media.s3.amazonaws.com%2Fpublic%2Fimages%2F7639bb61-9710-40e3-9f74-87d45b9a798f_1733x1009.jpeg) Paper by MIT and Hugging Face: [Economies of Open Intelligence](https://www.dataprovenance.org/economies-of-open-intelligence.pdf), November 2025
China ↑: _wh
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