Cheaper Chinese and open-source models reshape enterprise AI budgets

Soaring token bills are reshaping how businesses choose AI models, pushing enterprises toward cheaper open-source and Chinese alternatives. According to Reuters, the four most popular models on OpenRouter are all Chinese, with DeepSeek in the top spot at as little as 18 cents per million tokens — a fraction of frontier US API pricing. Coinbase is experimenting with GLM 5.2 and Kimi 2.7 as defaults to cut costs, and CEO Brian Armstrong has spoken publicly about maintaining token usage while lowering AI spend.

The cost pressure is acute: Uber reportedly burned through its entire 2026 AI budget in four months, and on r/Anthropic a SaaS operator vented about crossing $35k/month in token burn (182 upvotes). Hugging Face CEO Clement Delangue amplified the shift, citing a Stanford study showing 71.3% of ChatGPT queries could be accurately answered by a local model, and arguing a major part of enterprise workloads could run locally for free versus 'massive' frontier API costs.

This is arguably the theme of the week: economics, not raw capability, is driving model selection. As frontier labs raise record capital (OpenAI's $122B) and gate their best models, cost-conscious enterprises are quietly defaulting to good-enough open and Chinese models — a dynamic that could erode the premium-API business even as headline valuations soar.

In a related move, Alibaba affiliate Ant Group made its 12th humanoid-robotics investment in 18 months, leading a $73.6 million round in Zeroth, extending Chinese tech's aggressive push into physical AI. The convergence — cheap Chinese LLMs plus heavy Chinese robotics investment — signals a broad, well-funded competitive front. Watch whether US labs respond with cheaper tiers (as Anthropic did with Sonnet 5) and how enterprise switching accelerates.