中国政府支持的一份新报告显示，中国人工智能系统生成的推理数据量首次超过了用于训练这些系统的数据量，说明中国正在大规模采用人工智能。
For the first time, the amount of inference data generated by artificial intelligence systems in China has surpassed the amount of data used to train those systems, according to a new government-backed report, illustrating how the country is increasingly adopting AI at scale.
中国信息通信研究院（CCID）于周六发布了这份报告，该院隶属于中国工业和信息化部（MIIT）。报告引用近期官方数据称，中国日均Token（记号）调用量超过175万亿次，较2024年初增长1000多倍。
The report released on Saturday by the China Centre for Information Industry Development (CCID), which operates under China’s Ministry of Industry and Information Technology (MIIT), cited recent official data showing that China’s average daily token calls exceeded 175 trillion, an increase of more than 1,000 times from early 2024. Inference refers to the process of running trained AI models to respond to user requests, which involves processing units of data known as tokens.
推理是指运行经过训练的人工智能模型以响应用户请求的过程，涉及处理被称为Token的数据单位。随着人工智能采用加速，Token调用量——即通过公有云服务提供商使用人工智能的情况——反映出对人工智能服务需求的增长。报告未披露中国用于训练人工智能系统的数据量。
As AI adoption accelerates, the volume of token calls, which refers to AI usage through public cloud service providers, provides an indication of growing demand for AI services. The report did not disclose how much data is being used to train AI systems in China. Including estimated AI usage through private cloud deployments, China’s average daily token consumption as of June was around 500 trillion tokens, another MIIT-affiliated think tank, the China Academy of Information and Communications Technology, said in a report released on October 23.
另一家工信部系智库中国信息通信研究院（CAICT）在10月23日发布的报告中称，若加上私有云部署的预估人工智能使用量，截至6月，中国日均Token消费量约为500万亿。
China’s National Data Administration estimated in April that demand for computing power to provide AI inference could eventually reach three times that needed for training AI models, underscoring the growing need for infrastructure to support the application of AI across many different industries.
中国国家数据局在4月估计，提供人工智能推理所需的算力需求最终可能达到训练人工智能模型所需算力的三倍，凸显出支持人工智能在许多不同行业应用的基础设施需求日益增长。
Beijing has emphasised the importance of tokens in the AI era, with growing use of new phrases such as “token economy” in official policy language.
北京强调了Token在人工智能时代的重要性，官方政策语言中越来越多地使用“Token经济”等新提法。
Local governments, including Beijing’s, have announced plans to roll out development policies for the token economy, including measures to boost token consumption through token factories and token distribution platforms.
包括北京市在内的地方政府已宣布将出台Token经济发展政策，其中包括通过Token工厂和Token分发平台促进Token消费的措施。
Beijing-headquartered think tank CCID included the token-use milestone as part of its report, which listed 10 key trends in “new domains and new-quality capabilities”, a nod to the high-level government strategy of developing “new productive forces” to drive economic growth.
总部位于北京的智库赛迪（CCID）将这一Token使用里程碑纳入其报告，报告列出了“新领域新质能力”十大关键趋势，呼应了发展“新质生产力”推动经济增长的高层国家战略。
The report stressed the growing importance of these new domains – especially AI but also sectors such as quantum computing and aerospace technology – for great power competition, contrasting China’s progress with the approaches of the United States, European Union and India.
报告强调，这些新领域——尤其是人工智能，以及量子计算、航空航天技术等领域——在大国竞争中的重要性日益凸显，并将中国的进展与美国、欧盟和印度的做法进行了对比。
“We must place new domains and new qualities in a more prominent strategic position,” the report said.
报告称：“必须将新领域新质置于更加突出的战略位置。不进则退，慢进也是退。”为跟上需求，中国科技企业一直在大举投资AI基础设施。据研究机构锑元素（Rhodium Group）9月发布的一份报告，13家中国主要企业在AI基础设施上的资本支出预计今年将翻倍多，达到9320亿元人民币（约1390亿美元），并在2027年超过1.2万亿元。
“He who does not advance falls back, and even slow advancement is equivalent to falling back.”To keep pace with demand, Chinese technology companies have been investing heavily in AI infrastructure. Capital expenditure among 13 major Chinese companies on AI infrastructure is projected to more than double to 932 billion yuan (US$139 billion) this year, before exceeding 1.2 trillion yuan in 2027, according to a September report by research firm Rhodium Group.
部分开发者专注于降低推理成本。上个月，深度求索（DeepSeek）开源了DeepInfer框架，旨在更高效地运行其AI模型并降低算力成本，使竞争对手和下游用户也能从其创新中受益。
Some developers have focused on making inference more cost-efficient. Last month, DeepSeek open-sourced DeepInfer, a framework designed to run its AI models more efficiently and reduce computing costs, allowing competitors and downstream users to also benefit from their innovations.
与此同时，阿里巴巴集团控股有限公司于6月成立名为“Token Foundry”（Token铸造厂）的新业务单元，正值其推动内部Token消费及外部商业化之际。
Meanwhile, Alibaba Group Holding’s move to set up a new unit called the “Token Foundry” in June coincided with a push to boost internal token consumption as well as external commercialisation.
总部位于杭州的这家科技巨头报告称，截至6月止的季度内，其AI云和算力服务收入同比激增45%，达到71亿美元，反映出对AI服务的需求不断增长。阿里巴巴拥有《南华早报》。
The Hangzhou-based tech giant reported that revenue from its AI cloud and computing services surged 45 per cent year on year to US$7.1 billion in the quarter ended June, reflecting growing demand for AI services. Alibaba owns the South China Morning Post.
然而，AI需求的激增伴随着日益加大的财务压力，因为企业在支持AI所需的基础设施上投入巨资。
However, the surge in AI demand has come alongside mounting financial pressures, as companies spend heavily on the infrastructure needed to support it.
据Rhodium统计，凸显成本高昂的是，阿里巴巴、腾讯控股和百度在2026年上半年的合并自由现金流由2025年合并为正的1700亿元人民币，转为合并为负的160亿元人民币。
Highlighting the cost, Alibaba, Tencent Holdings and Baidu swung to a combined negative 16 billion yuan in free cash flow in the first half of 2026, from a combined positive free cash flow of 170 billion yuan in 2025, according to Rhodium.