Premium pricing is the real statement. You don't get treated as a frontier player if you price like the cheap alternative, so K3's $15-per-million tier is a brand move as much as an economic one.
It's also the mirror image of what's happening in Chinese consumer brands. Going global there now means leaning into Chineseness, guochao, heritage, proudly-from-China. In frontier AI, the "cheap Chinese" label is the liability, so the play is to shed it and carry yourself like a global company. Same goal with a different approach and both come to the same conclusion: the old "cheap Chinese" default is finally breaking down.
Exactly, it happened to smartphones, EVs and is now (commoditized) AI’s turn. To compete toe-to-toe, Chinese AI models have to keep scaling and change its positioning.
Agreed, and positioning is the hardest part. Scaling is a budget problem; getting the market to read you as premium is a brand one, and that's the muscle Chinese tech is only now starting to build now.
I am thinking that a lot (or a meaningful amount) of cost-conscious users (individuals and otherwise) who knew what they wanted from LLMs were using the model company-hosted APIs. The added friction of signing up for a subscription plan or API from these companies also filters out low effort users. This way, these companies should have a better view into tasks that power-users need done at volume and maybe less dross to sift through when cleaning data. If institutional power-users also use these APIs or take things local, Anthropic and OpenAI might have a growing blind spot for how to optimize for workhorse workloads.
Premium pricing is the real statement. You don't get treated as a frontier player if you price like the cheap alternative, so K3's $15-per-million tier is a brand move as much as an economic one.
It's also the mirror image of what's happening in Chinese consumer brands. Going global there now means leaning into Chineseness, guochao, heritage, proudly-from-China. In frontier AI, the "cheap Chinese" label is the liability, so the play is to shed it and carry yourself like a global company. Same goal with a different approach and both come to the same conclusion: the old "cheap Chinese" default is finally breaking down.
Exactly, it happened to smartphones, EVs and is now (commoditized) AI’s turn. To compete toe-to-toe, Chinese AI models have to keep scaling and change its positioning.
Agreed, and positioning is the hardest part. Scaling is a budget problem; getting the market to read you as premium is a brand one, and that's the muscle Chinese tech is only now starting to build now.
I am thinking that a lot (or a meaningful amount) of cost-conscious users (individuals and otherwise) who knew what they wanted from LLMs were using the model company-hosted APIs. The added friction of signing up for a subscription plan or API from these companies also filters out low effort users. This way, these companies should have a better view into tasks that power-users need done at volume and maybe less dross to sift through when cleaning data. If institutional power-users also use these APIs or take things local, Anthropic and OpenAI might have a growing blind spot for how to optimize for workhorse workloads.