Four labs build the models; one cloud keeps the money.四家实验室造模型,一朵云把钱收走。

IDC's 26H1 tracker, out today (Oct 29), shows Alibaba Cloud took 46.6% of China's LLM MaaS revenue, first by far; Zhipu, a lab known for its models, sits at 10.6%, and Volcano Engine at 10.2%.
The mechanism is plain: to call a large model, an enterprise calls through the cloud where its data, credits and compliance already live. Whoever holds that calling entry point collects the money; how good the model is sits one layer down. That opens a gap: the models leading the benchmarks and the names leading the revenue are two different crowds. Second-order: a pure-model company with no cloud has only two roads left, burn cash to build its own cloud, or become a supplier wholesaled on someone else's.
The strongest counter: maybe Alibaba Cloud leads precisely because Qwen is both good and cheap, capability driving it rather than the entry point. Even so, a company with an equally strong model but no cloud can't convert that into comparable revenue. Where the money lands is still decided by the entry point.
What it means for you: don't just chase the strongest capability; own the layer where the task gets requested. Capability keeps getting cheaper; the entry point compounds.
This breaks if, within a year, a model company with no hyperscaler cloud takes more than a fifth of China's LLM MaaS revenue.
IDC 今天(10 月 29 日)发布的 26H1 追踪显示:中国大语言模型 MaaS 市场上,阿里云拿走 46.6% 的收入排第一;而以模型见长的智谱只有 10.6%,火山引擎 10.2%。
机制很朴素:企业要调用大模型,走的是自己数据、额度、合规已经落地的那朵云。谁握着这条『调用入口』,谁就收走这笔钱,模型好不好是下一层的事。于是裂开一道口子:榜单上领先的模型,和账面上领先的收入,是两拨人。二阶效应随之而来,没有云的纯模型公司只剩两条路,要么自己烧钱建云,要么沦为别人云上被批发的供应商。
最强的反方:阿里云第一,也许正因为通义千问(Qwen)又好又便宜,是能力在驱动,而不是入口。可即便如此,一家模型同样强、却没有云的公司,拿不到同量级的收入;钱落在哪里,仍由入口决定。
对你的含义:别只盯最强的能力,去占住『任务被发起』的那一层。能力会越来越便宜,入口会越滚越厚。
什么会推翻它:一年内,某家没有大厂云的模型公司,在中国 LLM MaaS 收入里占到五分之一以上。
Built on the WAKENEX concept:所用的 WAKENEX 概念: How knowledge is called and tasks get done知识调用与任务执行
Add WAKENEX as a preferred source on Google在 Google 把 WAKENEX 设为首选来源


