If I publish a massive quantity of source code — to the point that it’s very expensive to compile — it’s still open source.

If the training data and model training code is available then it should be considered open, even if it’s hard to train.

> the training data

This will never be fully open

Maybe not for some closed models. That doesn’t mean truly open models can’t exist.

I doubt you’d say that if one run of compiling the code would cost you $400M.

If it was only feasible for a giant corporation to compile the code, I would consider it less than open source.

Free software means that you have the ability - both legal and practical - to customize the tool for your needs. For software, that means you have to be able to build the final binary from source (so you can adapt the source and rebuild), for ML models that means you need the code and the model weights, which does allow you to fine-tune that model and adapt it to different purposes even without spending the compute cost for a full re-train.