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Comment by simonw | Hacker News Reader

Absolutely not "open source" - here's the license: https://huggingface.co/MiniMaxAI/MiniMax-M2.7/blob/main/LICE...

> Non-commercial use permitted based on MIT-style terms; commercial use requires prior written authorization.

And calling the non-commercial usage "MIT-style terms" is a stretch - they come with a bunch of extra restrictions about prohibited uses.

It's open weights, not open source.

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It's not even open weights as generally understood, the non-commercial restriction is pretty severe. The earlier M2.5 model will still be preferred for many purposes.

I've flagged the post, the title is editorialized, the title on the blog post is "MiniMax M2.7: The Agentic Model That Helped Build Itself" (at least at the time of writing this).

"Helped build itself" is arguably also a stretch as noted in another comment.

I've yet to see a convincing explanation of what make such a “license” legally bounding in the first place.

There's no copyright on model weights themselves (because they are produced purely mechanically without involving human creativity, the same way there's no copyright on compiled artifacts of a piece of software or an h264 encoded movie file). For software and movies the copyright cover the source material, not the resulting binary, and for LLMs the source material can also be protected by copyright. The problem, is that LLM makers don't own most of the copyright on the source material and worse they claim the training process is transformative enough to erase the copyright of the source material so even the part of the training data for which they own copyright couldn't extend their copyright protection to the weights.

It's very likely that these licenses are entirely devoid of legal value (and I don't think Meta engaged in any legal actions (not even a DMCA takedown) on any of the bazillions llama finetunes violating the llama license on huggingface).

Even the MIT-licensed weights are just that: open weights. Let's not call the weights "source", because they're emphatically not. I can't retrain Qwen from the ground up with different pre-training algorithms, for example.

Model weights are source because they are "the preferred form for modification", e.g. you can use them for fine-tuning. Training a new model from raw data (1) gets you something very different from the original and (2) is computationally unfeasible for most, compared to simpler fine tuning.

I disagree. Fine-tuning, while useful, feels more like patching executables than source code. Besides, just because most people don't compile e.g. Android for themselves doesn't mean that Android should only be distributed in binary form.

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