Agree, I don't necessarily see a strong argument favoring OpenAI or Anthropic here. In the interest of perspective, can anyone (perhaps playing devil's advocate) give one?

The open models are now good enough for what I want to do with them, let alone any future improvements. And factoring in efficiency gains, a model in the ~70b range starting to satisfy my needs would completely obviate the need to pay others for inference. This does not seem far-fetched to me, comparing with where open models were at this time last year. What am I missing?

Hardware and electrical costs including power usage and electric wiring/outlet costs of such machine.

Unless you are spending more than a max subscription (200 a month+) its cheaper to use the cloud.

But things are priced cheaper in the cloud now to lock you in and restrictions around hosted models are getting worse.

If you only have a $300 dollar laptop its probably not worth the upgrade.

I'm personally excited by local AI but the experience for the average isn't the same. I'm willing to get .5/s running on 10-15 years old machines but what I can do with it is limited.

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coding on a laptop is only one use case

you can't create a new drug by running a model on a laptop. You can't serve a customer support bot running on a laptop. You can't generate video in bulk for many users on a laptop. So there is still a case for paying others for inference.

Does it justify the valuations? No idea, but some major use cases are still there. That's why they are rushing to implement, OpenAI creating a "deployment company", Anthropic having some pharma rumors, etc.