I can't imagine a universe where a small mind with limited computing resources has an advantage against a datacenter mind, no matter the architecture.

The small mind could have an advantage if it is closer or more trustworthy to users.

It only has to be good enough to do what we want. In the extreme, maybe inference becomes cheap enough that we ask “why do I have to wake up the laptop’s antenna?”

I don't want to send sensitive information to a data center, I don't want it to leave my machine/network/what have you. Local models can help in that department.

You could say the same about all self-hosted software, teams with billions of dollars to produce and host SaaS will always have an advantage over smaller, local operations.

The advantage it might have won't be in the form of "more power", it would be in the form of "not burdened by sponsored content / training or censorship of any kind, and focused on the use-cases most relevant to the individual end user."

We're already very, very close to "smart enough for most stuff". We just need that to also be "tuned for our specific wants and needs".

Abundant resources could enable bad designs. I could in particular see a lot of commercial drive for huge models that can solve a bazillion different use cases, but aren't efficient for any of them.

There might be also local/global bias strategies. A tiny local model trained on your specific code/document base may be better aligned to match your specific needs than a galaxy scale model. If it only knows about one "User" class, the one in your codebase, it might be less prone to borrowing irrelevant ideas from fifty other systems.

The only difference is latency.

Universes like ours where the datacentre mind is completely untrustworthy.