"Attention is all you need" - the larger bet is that by releasing your models open-weight, you'll get more attention and mindshare than if you tried to jump in to compete with the major closed providers, and the value of that attention will outweigh the cost of the training run.

So far, it's really only the Chinese labs (and FAIR or whatever Meta's project is called now) that are doing this. Oh yeah, and Google's Gemma.

At the moment, this is all massively distorted by the prestige and investment money flowing into the space. None of the labs have to charge the real cost of inference let alone the marginal cost of training because they are instead lighting investment money on fire to cover that.

One imagines (though I have not investigated in detail) that there's a degree of national prestige work going on too. The Chinese labs are trying to show that they can build better and more efficient models and are releasing open to undercut the US labs.