Lucky you! I need to check my university's current GPU power but sadly my thesis won't be needing that kind of horsepower, so I won't be able to give it a try unless I pay AWS or someone else for it on my own dime.

nVidia's new Digits workstation, while expensive from a consumer standpoint, should be a great tool for local inferencing research. $3000 for 128GB isn't a crazy amount for a university or other researcher to spend, especially when you look at the price of the 5090.

Intriguingly, there's reason to believe the R1 distills are nowhere close to their peak performance. In the R1 paper they say that the models are released as proofs of concept of the power of distillation, and the performance can probably be improved by doing an additional reinforcement learning step (like what was done to turn V3 into R1). But they said they basically couldn't be bothered to do it and are leaving it for the community to try.

2025 is going to be very interesting in this space.

I use 14b and it's certainly great for my modest highschool physics and python (to help the kids) needs, but for party games and such it's a drag its pop culture stops at mid 2023