There is a good point here:

I don’t understand one thing about Mistral, which I’m a fan being in Europe: they opened the open weights MoE show with Mixtral. Why are they now releasing dense models of significant sizes? In this way you don’t compete in any credible space, nor local inference, nor remote inference since the model is far from SOTA and not cheap to serve. So why they are training such dense big models? Dense models have a place in the few tens of billion parameters, as Qwen 3.6 27B shows, but if you go 5 times that, it is no longer a fit, unless you are crushing with capabilities anything requiring the same VRAM, which is not the case.

https://news.ycombinator.com/item?id=47949642

but it is also le chat’s main model now, so have to test it further and see how it goes!