Faulty reasoning signals

• Attempt to Sell a Product or Service - 61.9%
• Appeal to Authority - 59.7%
• Confirmation Bias - 56.7%

Article text

Three weeks ago, we attempted a lengthy answer of the "trillion dollar question" namely are Chinese AI models a better value than US models and, using extensive research from UBS, concluded that at almost 95% of the capability (and rising) and just 10% of the cost, the answer was a resounding yes.

Fast forward to today when Goldman analyst Ronald Keung also addressed the $64 trillion elephant in the room, and published a 50-page China AI models LLM primer (available to pro subs), in which he agrees with our conclusion, namely that "China's AI open-source/open-weight models are reaching a critical point of intelligence performance vs. global proprietary models, with a significant ramp up in domestic enterprise & global SME adoption that will enable a positive data flywheel of further model improvement."

From DeepSeek’s moment last year (on cost efficiency) to Zhipu’s GLM moment this year (on model intelligence).

Signposts for 2H 2026

How do Chinese models achieve competitive performance at low costs/tight computing resources

Why are Chinese models pursuing an open source/open weight approach, and ways to monetize?

What are the key addressable markets, domestically and internationally, and key risks?

Who are best positioned to be the long term winners? Introducing our Competitive Positioning framework

Foundation models

Appendix

China's Key Players at a Glance: Mega-caps

China's Key Players at a Glance: Key Independent Players