China Leads Open-Source AI Race | Generated by AI
Yeah, it’s definitely happening—Chinese companies like Alibaba (with Qwen3) and DeepSeek have been dropping open-source frontier models that straight-up outperform Meta’s Llama 3.1 on key benchmarks for reasoning, language tasks, and efficiency. For instance, DeepSeek-V3 and Qwen models are topping global rankings on platforms like Hugging Face, sometimes with way less compute power thanks to clever optimizations like Mixture-of-Experts architectures. By mid-2025, China was holding like four of the top five spots in open-weight LLMs.
But is it really weird? Nah, not when you zoom out. China’s been laser-focused on this for years—think their 2017 national AI plan that poured resources into talent pipelines (massive STEM grads from places like Tsinghua), state-backed funding, and a culture that treats AI like the next big infrastructure boom. They’ve got huge Chinese-language datasets for training, plus they’ve turned US chip export bans into a feature by getting super efficient (e.g., training killer models on stockpiled mid-tier GPUs for pennies compared to Western costs). Meta’s open-source push with Llama is bold, but it’s up against a whole-of-society machine in China that’s all about rapid scaling and self-reliance. If anything, it’s more surprising it took this long for them to pull ahead in the open-source arena.
China now leads the U.S. in this key part of the AI race
Why China’s AI breakthroughs should come as no surprise
The China open-source AI revolution that’s rattling Silicon Valley