By desk you mean that "Mac mini"? Because it is pricey. In my country it is 1000 USD (from Apple for basic M4 with 24GB). My desk was 1/5th of that price.

And considering that this Mac mini won't be doing anything else is there a reason why not just buy subscription from Claude, OpenAI, Google, etc.?

Are those open models more performant compared to Sonnet 4.5/4.6? Or have at least bigger context?

Right now, open models that run on hardware that costs under $5000 can get up to around the performance of Sonnet 3.7. Maybe a bit better on certain tasks if you fine tune them for that specific task or distill some reasoning ability from Opus, but if you look at a broad range of benchmarks, that's about where they land in performance.

You can get open models that are competitive with Sonnet 4.6 on benchmarks (though some people say that they focus a bit too heavily on benchmarks, so maybe slightly weaker on real-world tasks than the benchmarks indicate), but you need >500 GiB of VRAM to run even pretty aggressive quantizations (4 bits or less), and to run them at any reasonable speed they need to be on multi-GPU setups rather than the now discontinued Mac Studio 512 GiB.

The big advantage is that you have full control, and you're not paying a $200/month subscription and still being throttled on tokens, you are guaranteed that your data is not being used to train models, and you're not financially supporting an industry that many people find questionable. Also, if you want to, you can use "abliterated" versions which strip away the censoring that labs do to cause their models to refuse to answer certain questions, or you can use fine-tunes that adapt it for various other purposes, like improving certain coding abilities, making it better for roleplay, etc.

I have the same setup (M4 Pro, 24GB). The e4b model is surprisingly snappy for quick tasks. The full 26B is usable but not great — loading time alone is enough to break your flow.

Re: subscriptions vs local — I use both. Cloud for the heavy stuff, local for when I'm iterating fast and don't want to deal with rate limits or network hiccups.