中国 LLM 数据经济全景：腾讯、阿里、字节主导采购，实验室自建倾向明显
把大家都在私下聊的中国数据标注和 RL 环境市场拼出了全貌，还对比了中美花钱节奏差 6-12 个月，做训练数据的必读。
这篇文章梳理了中国 LLM 训练数据市场的结构。美国由 Mercor、Surge、Handshake 等数据供应商掌握最大的供给网络，并出现大量提供 RL-ready 环境的专门服务商。中国的主要采购方是腾讯、阿里和字节跳动，与美国由 OpenAI 和 Anthropic 主导的格局不同。美团、小红书、小米等公司倾向内部自建模型，而美国科技公司更多依赖 API 和开源权重模型。文章估计中国实验室在数据支出意愿上落后美国 6–12 个月，但正在快速追赶。
This is the best piece I’ve read to date on the Chinese data economy for LLMs, and how it compares to the US counterparts (summarized by Mercor, Surge, and Handshake having the biggest network, SUPPLY, but also many companies with specialized services, in the form of RL-ready environments). China’s leading spenders, Tencent, Alibaba, and ByteDance, don’t mirror OpenAI and Anthropic leading the US market.
The Chinese market likely has a bias similar to their “ownership” mentality of more LLM builders in house, like Meituan, RedNote, and Xiaomi, whereas major US tech services build more on APIs and existing open-weight models.
Altogether, it seems like Chinese labs were 6–12 months behind on willingness to spend on data, relative to the US, but are rapidly catching up.
I've been hearing lots of murmurings on China's AI industry, but folks are secretive, so it's hard to put this all together.
