Reuters reports that ByteDance plans to spend about 100 billion yuan (~$14.3 billion) on Nvidia AI chips in 2026, up from roughly 85 billion yuan in 2025, if U.S. export rules allow H200 GPU sales to China. Chinese media say the chip budget is part of a broader 160 billion yuan ($23 billion) AI capex plan covering processors and infrastructure for large‑scale model training.
This article aggregates reporting from 5 news sources. The TL;DR is AI-generated from original reporting. Race to AGI's analysis provides editorial context on implications for AGI development.
If the numbers hold, ByteDance is positioning itself as one of the largest single‑company buyers of AI compute on the planet. A 100‑billion‑yuan GPU budget, on top of this year’s already massive spend, essentially turns its recommendation and generative systems into a sovereign‑scale compute project. That level of demand, focused heavily on Nvidia, both reinforces Nvidia’s dominance and intensifies the global scramble for high‑end accelerators in a world already constrained by U.S. export controls.([reuters.com](https://www.reuters.com/world/asia-pacific/bytedance-spend-about-14-billion-nvidia-chips-2026-scmp-reports-2025-12-31/?utm_source=openai))
Strategically, this is China’s consumer internet champion saying out loud that it intends to keep pace with, or potentially leapfrog, Western peers on large‑scale models and AI‑native products. Half the 2026 capex reportedly goes to processors, with the rest into data centres and supporting AI infrastructure, which will feed everything from Doubao and CapCut to ByteDance’s emerging enterprise tools and overseas expansions. For the race to AGI, the message is that non‑U.S. platforms are not conceding the frontier: they are quietly building compute bases that, if sanctions loosen or domestic chip alternatives mature, could support frontier‑class research and deployment at scale.


