> They are all still very subsidised.

I think the opposite: I think the frontier labs have good margins on their inference unit costs.

We can already see what it costs to run near frontier-size models. There are independent business pivoting to serving these models at reasonable prices and they're competing on OpenRouter for costs much lower than frontier labs.

> Is there any guarantee that I'll be able to run a Opus 4.8-level model on my personal computer before the big AI labs decide to hike up the prices?

I would bet good money on prices going down significantly, not up.

If we get to the point where you can run an Opus 4.8 model on your local computer, it's going to be even cheaper for a datacenter to serve it on their hardware. That means prices crash, not that they're going to rise.

They may have good margins, but a few things are still true:

1. Much of those profits have to be immediately reinvested into model training runs to avoid being lapped by competitions.

2. Unit costs are irrelevant when the labs don't price per unit, and instead charge, for instance, $200 / month for $10k worth of tokens.

This isn't a steady state. Whatever the current situation is, I doubt it's sustainable.

The subscription based plans are heavily subsidized, but the direct API inference pricing (which larger companies need to pay) is profitable.

Using a full Claude Max 20x plan to 100% of weekly usage would easily cost you 2k through the API. While the Claude Max 20x plan is 200 a month.

Interestingly enough, geohot also has an article covering this: https://geohot.github.io//blog/jekyll/update/2026/06/18/pric...

I thought hardware prices would always just keep going down.