[stymaar]

> the implications are pretty big. It would mean you could run "frontier level" performance in one box at home.

That wouldn't surprise me at all actually, models like Qwen3.6-35B are comparable to frontier level models from a year ago and I wouldn't be surprised if we had self-hostable open weight models matching Opus 4.7 in a year. Assuming that Google has one year of advance against Chinese lab isn't far fetched given how much resources they have compared to their Chinese competitors.

[DCKing]

I think there was a leap around Opus 4/4.1 that hasn't quite been equalled by self hostable models yet. Perhaps full Kimi K2.6 and Deepseek V4 Pro can achieve Opus 4.1 levels (it's hard to compare anyway, benchmarks are largely a game nowadays), but both of these are also north of 1000B parameters and therefore really impractical to run at home for the foreseeable future.

It's not yet obvious to me that you can achieve the breakthrough performance of say Opus 4.1/4.5 in a number of parameters you can swing at home.

[stymaar]

> It's not yet obvious to me that you can achieve the breakthrough performance of say Opus 4.1/4.5 in a number of parameters you can swing at home.

People used to believe the same about GPT-4, and I'm not convinced this is going to be different this time.

You do need a very big model if you want something that remembers random trivia about everything, but I'm not convinced this is needed to do meaningful work.