MODELS
Models: months behind, not years
If compute were everything, China would be years behind. It is not. We compare the best model of each country on one yardstick, Epoch AI's Capabilities Index (ECI), which combines dozens of tests into a single score.
Key points
- China's best model (Kimi K3, Jul 2026) is at a level US models first reached 4.4 months earlier. Over the past year each new Chinese best has been 4–8 months behind.
- The gap has neither closed nor opened: it has stayed at a few months since 2024, while the largest US training run used 50x more compute than China's in 2026.
- China competes by giving models away: 6 of its top 10 can be downloaded and run by anyone, against 0 of the US top 10.
The best model of each country
Source: Epoch AI (ECI)
Each new Chinese best, and how far behind it was
| Model | Released | ECI | US reached it | Months behind |
|---|---|---|---|---|
| Kimi K3Moonshot · open weights | Jul 2026 | 157.7 | Mar 2026 | 4.4 |
| Qwen3.7-MaxAlibaba | May 2026 | 153.7 | Dec 2025 | 5.2 |
| Kimi K2.6Moonshot · open weights | Apr 2026 | 151.0 | Nov 2025 | 5.0 |
| GLM-5.1Z.ai (Zhipu AI) · open weights | Apr 2026 | 149.9 | Aug 2025 | 8.0 |
| Kimi K2.5Moonshot · open weights | Jan 2026 | 148.1 | Aug 2025 | 5.7 |
| DeepSeek-V3.2DeepSeek · open weights | Dec 2025 | 146.3 | Apr 2025 | 7.5 |
| Kimi K2 ThinkingMoonshot · open weights | Nov 2025 | 146.0 | Apr 2025 | 6.7 |
| DeepSeek-V3.2-ExpDeepSeek · open weights | Sep 2025 | 145.0 | Apr 2025 | 5.5 |
| Qwen3-235B-A22B-Thinking (Jul 2025)Alibaba · open weights | Jul 2025 | 143.9 | Mar 2025 | 3.8 |
| DeepSeek-R1 (May 2025)DeepSeek · open weights | May 2025 | 141.3 | Dec 2024 | 5.3 |
| Qwen3-235B-A22BAlibaba · open weights | Apr 2025 | 139.4 | Dec 2024 | 4.3 |
| DeepSeek-R1DeepSeek · open weights | Jan 2025 | 139.0 | Dec 2024 | 1.1 |
| DeepSeek-V3DeepSeek · open weights | Dec 2024 | 132.4 | Sep 2024 | 3.4 |
| Qwen2.5-72BAlibaba · open weights | Sep 2024 | 129.0 | Jun 2024 | 3.0 |
| Qwen2.5-32BAlibaba · open weights | Sep 2024 | 128.5 | May 2024 | 4.2 |
| Qwen2-72BAlibaba · open weights | Jun 2024 | 125.3 | Mar 2023 | 14.8 |
| DeepSeek-V2 (MoE-236B, May 2024)DeepSeek · open weights | May 2024 | 124.8 | Mar 2023 | 13.8 |
| Yi-34B01.AI · open weights | Nov 2023 | 117.3 | Mar 2023 | 7.7 |
| Qwen-14BAlibaba · open weights | Sep 2023 | 112.8 | Mar 2023 | 6.4 |
| Baichuan2-13BBaichuan · open weights | Sep 2023 | 102.8 | Feb 2023 | 6.4 |
| Baichuan1-7BBaichuan · open weights | Jun 2023 | 89.8 | Feb 2023 | 3.2 |
Source: Epoch AI (ECI)
Compute used for the largest training runs
| Year | US largest | China largest | US ÷ China |
|---|---|---|---|
| 2026 | GPT-6 Astra1.0×10^27 FLOP | Kimi K32.0×10^25 FLOP | 50x |
| 2025 | Grok 45.0×10^26 FLOP | Qwen3-Max1.5×10^25 FLOP | 33x |
| 2024 | Llama 3.1-405B3.8×10^25 FLOP | Doubao-pro2.5×10^25 FLOP | 2x |
| 2023 | Gemini 1.0 Ultra5.0×10^25 FLOP | Qwen-72B1.3×10^24 FLOP | 38x |
| 2022 | Minerva (540B)2.7×10^24 FLOP | GLM-130B3.5×10^23 FLOP | 8x |
| 2021 | FLAN 137B2.0×10^24 FLOP | ERNIE 3.0 Titan1.0×10^24 FLOP | 2x |
| 2020 | GPT-3 175B (davinci)3.1×10^23 FLOP | CPM-Large2.6×10^20 FLOP | 1,205x |
| 2019 | OpenAI Five6.7×10^22 FLOP | MMLSTM (WT-2)1.9×10^17 FLOP | 345,717x |
FLOP = the number of calculations used in training. Estimates by Epoch AI; many recent models do not disclose it, so the largest known run is used.
Source: Epoch AI (models)
How many notable models come from China
Show the numbers
| Year | US | China | Other |
|---|---|---|---|
| 2018 | 27 | 1 | 9 |
| 2019 | 56 | 3 | 9 |
| 2020 | 37 | 5 | 8 |
| 2021 | 54 | 16 | 9 |
| 2022 | 68 | 8 | 15 |
| 2023 | 86 | 21 | 12 |
| 2024 | 57 | 29 | 12 |
| 2025 | 64 | 33 | 10 |
| 2026 | 47 | 29 | 6 |
Source: Epoch AI (models)
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Updated 29 Sep 2026 12:24 JST · US power to Jun 2026, China power to May 2026 · models to 9 Sep 2026