Report data: how big did China's generative AI grow in six months
CNNIC's Generative AI Applications Development Report (2026) gives a panoramic figure: by H1 2026, China's generative AI user base broke through 700 million, with penetration above 50%. That means roughly one in every two Chinese netizens now uses a generative AI tool, while half a year ago the figure was still under the halfway mark. CNNIC draws this curve pretty steep.
Breaking down user behavior, 76.0% of users say they let generative AI answer questions — Q&A is still the dominant entry point. The real incremental growth comes from multimodality: 47.8% use AI for image and video work, 37.6% for text generation, and 32.5% write AI into work summaries, meeting notes, and PPT workflows. AI has seeped into the three high-frequency office scenes.
Hardware entry: wearables and 3C digital gear are the penetration battlefield
Another frequently overlooked figure in the report — 38.7% of netizens bought smart hardware devices online in the past six months. Wearables account for 20.2%, while smartphones, tablets, and other 3C digital products take 18.2%. The soft-hard collaboration path for generative AI is not starting from new form factors like AR glasses, but eating its first wave of dividends from already mature smart watches and mobile devices.
Lining these two figures up, the logic becomes clear: wearables and 3C digital gear are the hardware entry, generative AI is the software entry, both ends accelerating. A user may have bought a new smart watch and frequently call the AI assistant from their phone — both ends got official endorsement in the CNNIC report.
Chinese vendors take the entire top six on the call rankings
The report's most sensitive data point: on the global mainstream LLM call rankings, the top six models all come from Chinese teams. The report names DeepSeek and Moonshot (kimi), noting that local firms have successively released multiple trillion-parameter open-source large models.
This claim requires careful reading. The specific institution and ranking behind "call rankings" is not named in the CNNIC reposted version. But if the data is real, the direction is clear: in the past two years, Chinese large models have firmly stood at the global forefront across engineering metrics like inference call volume, Token consumption, and developer adoption. Open-weight models play a role here that's completely different from closed-source APIs — they provide a low-cost, locally deployable, fine-tunable base that pushes call volumes to the first tier.
A few judgments beyond the data
First, the 700 million users and 50% penetration figures come from CNNIC sample surveys, not operator or payment platform level hard data. The strength is broad coverage; the weakness is the loose definition of frequency — "have used" and "use daily" are two different things. A more accurate reading of "broke through 700 million" is that the number of Chinese netizens who have used generative AI exceeds 700 million.
Second, 76% Q&A, 47.8% multimodal, 37.6% text, 32.5% office — these ratios can stack on the same user, with the total far exceeding 100%. It shows AI tools are not single-point penetration but scene stacking.
Third, the top-six-all-from-China claim is directly tied to the open-source ecosystem and price war. Open-weight models like DeepSeek-V3, Kimi K2, and the Qwen3 series have pushed inference unit prices down to a fraction of closed-source API costs, with developers voting with their feet — but whether "global call top six" counts internal testing traffic, the report does not address.
So what
What makes this CNNIC report most worth reading is not the 700 million figure itself, but how it strings together the three-layer structure of "users, hardware, model supply." When user scale passes 700 million, smart hardware penetration approaches 40%, and domestic open-source models occupy the global call rankings' top spots, all happening simultaneously, the soft-hard-integration logic of China's AI industry chain moves from PPT into CNNIC data.