LLM primer: Critical point of intelligence for global proliferation: NAVIGATING CHINA AI MODELS

Research evidence excerpt

LLM primer: Critical point of intelligence for global proliferation: NAVIGATING CHINA AI MODELS

EQUITY RESEARCH | 10 July 2026 | 2:45AM HKT

NAVIGATING CHINA AI MODELS

LLM primer: Critical point of

intelligence for global proliferation

From DeepSeek's moment last year (on cost efficiency) to Zhipu's GLM moment

this year (on model intelligence)

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, in our view. We evaluate How these models

achieve such performance at low costs/tight computing resources; Why they pursue

an open-source/open-weight approach and how they monetize; What the key

addressable markets are, as global enterprises shift from 'token-maxxing' to ROI-

first, where we highlight two favored ARR quadrants for Chinese models; and Who

the potential long-term winners will be under our Competitive Positioning

framework. We note any stricter access to China's future most frontier models for

overseas markets, Western markets' policies on China models, and access to high-

end computing in model training as three key swing factors/risks to our China AI

model token/revenue growth trajectory.

We introduce our Chinese AI model Competitive Positioning framework based on

pricing power, cost advantage and financial strength, overlaying with token scale

and market share progressions, and identify Knowledge Atlas (Zhipu, initiation) and

DeepSeek (private) as the strongest positioned in foundation models, and

Bytedance (private) in multi-modal.

Ronald Keung, CFA Eric Sheridan Allen Chang Lincoln Kong, CFA Timothy Zhao