I actually believe the amount of $ is what was missing for them to improve their fundamental flaws. They're a very competent team, but were working with a tiny fraction of the budget of US/China teams.

If Mistral aren't going to distill other people's large models they obviously need to train their own large models. This obviously requires money for optimization, tuning and training hardware.

They've started hosting GLM-5.2, that should be very telling of their capabilities at the moment. Hopefully the investment will allow them to hire the right people to become competitive.

can you elaborate what are their fundamental flaws that are not fixable by funds?

There is nothing exciting about mistral but they're the only european ai lab i've even heard off (jeppa doesn't count)

Honestly being only 1 year behind makes me an optimist. You’re telling me Europe can be slightly behind with 1000x less capex and way more sustainable economics? Awesome. The world moves slower than AI progresses, I can see a scenario where 1 year isn’t a problem.