Chinese AI Model Emerges as Fresh Threat to Anthropic Ahead of Planned Float

Jefferies' Christopher Wood flags a "DeepSeek moment" as cheaper Chinese models gain ground on Western incumbents The launch of a low-cost Chinese artificial intelligence model has been described by Jefferies strategist Christopher Wood as another "DeepSeek moment" for the...

Jefferies’ Christopher Wood flags a “DeepSeek moment” as cheaper Chinese models gain ground on Western incumbents The launch of a low-cost Chinese artificial intelligence model has been described by Jefferies strategist Christopher Wood as another “DeepSeek moment” for the…

chnology sector. Wood, author of the bank’s widely read Greed & fear note, said the GLM-5.2 model from Hong Kong-listed Z.ai, formerly Zhipu AI, was almost a match for Anthropic in the corporate market at a quarter of the cost per token

The challenge lands as Anthropic, the US AI developer behind the Claude chatbot, prepares for a planned stock market listing. Anthropic’s annualised run-rate revenue has surged from $9 billion at the end of 2025 to $47 billion in May, growth Wood expects to slow as companies push back against heavy token consumption. He argued the threat was greater still for rival OpenAI (Unlisted:OPAI), which has already lost ground to Anthropic among corporate customers and is also weighing a listing.

Cheaper Chinese models are already gaining share, with the top Chinese systems processing 21.37 trillion tokens on the OpenRouter aggregator platform in the week to 21 June, up from 4.37 trillion in late April, against 5.76 trillion for the leading US models. Wood sees the shift reinforcing a view that large language models will become commoditised, while giving companies an incentive to move smaller models onto their own servers to protect data. Despite the competitive pressure on the model developers, Wood remains positive on the “picks and shovels” suppliers that have driven AI-related stock gains, citing the Jevons paradox, under which cheaper tokens spur greater overall demand for computing power and memory chips.

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