Meta is selling their now excess compute, other compute has been on the market for a while. The current hardware cost bubble is temporary, especially once people are forced to pay the real inference price instead of majorly subsidized subscriptions.

You may be correct but the combination of local models when they are fast enough and work, combined with paying close to zero for deepseek v4 flash from US providers is pretty good. When you need it, glm5.2 is cheap to use and very good for working with larger projects.

For the near future it seems that the new models will consume whatever improved hardware capacity we have. Competing with that is challenging, but I also think there will be strong economic incentives towards cheaper but adequate models on other providers.

I don't think we'll see home users being able to match even the low end clouds for a long time.

Longer term I think we'll see these uses of AI cluster into a few groups:

- maximal code / reasoning quality, at high prices (Fable)

- typical code / agents (sub-Opus, Terra)

- cheap but decent enough quality (think Deepseek / GLM / Luna)

- so cheap I don't care about utilization (Deepseek, and friends)

And also more niche ones:

- ultra fast with high quality answers (typically sub-SOTA). Cerebras / dedicated silicon type approaches, expensive.

- ultra fast with mostly-adequate answers, and an openness to retries, moving up to better models

I think the open models will dominate (not with individuals, but low cost providers) all except the top 1-2 of those categories, and there will be a continuous erosion on the big player's moats. The top categories are also where all the money is, but I'm not sure it can justify those investments long-term. I also think they will have to squeeze more money out of them to justify the investments, which will also drive people down the list.

Edit: clarifications.

There will be plenty of model providers with prices that undercut Anthropic/OpenAI's prices.