Comment by maxloh
3 hours ago
> 2. If the Licensee or any of its affiliates operates a Model as a Service business, the Licensee must enter into a separate commercial license with Mistral before using the Model or its derivative works for any commercial purpose. The Licensee may contact Mistral, using this form: https://mistral.ai/contact/, to request a commercial license. [0]
Calling this "open weight" is misleading. That's why we had huge backlash when Redis, Elasticsearch, and Terraform went source-available, right?
Weight-available is a better adjective for this kind of licensing. Same for Qwen, GLM, Kimi, MiniMax, etc. If they really want to be open source, they should pick an OSI-approved license.
[0]: https://huggingface.co/mistralai/Mistral-Large-4-1T-A52B/blo...
> That's why we had huge backlash w
Training a frontier model is prohibitively expensive, so it’s understandable that open weights aren’t truly open source. In fact, I worry whether open weights will even survive[1] once the current AI cycle cools down. An even bigger issue is that as long as model development remains this capital intensive, a genuinely open-source community around frontier AI is virtually impossible. That will have massive implications for our careers. The more capital concentrates at the top, the less leverage we’ll have in the job market.
[1] Arguably hardware companies like Nvidia have incentives to subsidize open models to drive GPU demand. That said, I'm not sure sustainable and sufficient that incentive can be.
We could create an open-source SETI@HOME but for training open source models?
Someone’s surely doing it atm we just don’t know yet. And then we scan all books but the stuff stays local. Perhaps possible, perhaps not. But I don’t see why everyone could not run given the epoch on his content only, reporting back findings (loss).
No it's not understandable, they were created with our stolen data.
Open weight models are kind of weird because they're usually just a bunch of weights and maybe a chat template, not even test vectors or anything. Quite odd, and probably one of the reasons why vllm, sglang, the llamas etc. so often produce buggy output. It's actually quite strange how little attention is given to verifying these setups work.
Why cant the community piece together the open-weights using open community-based like, implementation or whatever magic sauce integrates those weights
This is the new OSI Open source definition for AI models:
https://opensource.org/ai/open-source-ai-definition
Mistral Large 4 is definitely not open given the "use for any purpose without having to ask for permission" requirement.
Well, to be fair, Mistral never say its open source. They call it just open weight.
Not really. That definition also requires the training code and training data composition to be open-sourced.
No major Chinese or Western labs satisfy these requirements. The only vendors I can think of that do are Nvidia and Allen AI.
K2 horizon is the closest to actually releasing everything that I am aware of https://ifm.ai/blog/k2/
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Allen AI imposes further restrictions on their model releases, I think: https://allenai.org/responsible-use
Nobody can do that because they were all trained on stolen content
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We are now at the mercy of labs to provide frontier models as open-weight. Now that even some Chinese labs are releasing their models as weight-available, what stops them from prohibiting certain internal uses of new models? What about public chatbots?
Open models we have now will become obsolete within a few years. Imagine a world where our last open models were from the GPT-2 era.
I believe we need truly sovereign models, not in the Western sense, but from a community perspective. We need a model line that stays open-source across generations.
The problem is the massive amount of money, data, and talent to produce anything remotely competitive. Ideas have been floated about distributed training, but training requires insanely fast interconnect between nodes making it impossible with the current methodologies we have. Now if you mean funded at a national level, that seems more doable so long as the training runs are centralized in big DCs.
There's always going to be some nerds out there that want to make and release a model as open, and share their knowledge along the way. I'm not too concerned.
The fear you're sharing has been shared since day 1 of open-weight models and it has yet to come to fruition.
Further, regardless of what any of these labs license their model as, the end user who has downloaded the weights can still use them for virtually any purpose (synthetic data, classification, etc) as much as they want and there is no way to reasonably enforce a license on those outputs.
So even if you can't run a service using this model's weights (without a license), the weights still do provide utility for training new models with any other license.
*Edit, responding to the replies: Constraints give rise to ingenuity. Who knows how we'll be training models in the future. Hopefully in a distributed fashion, maybe with some kind of consensus-driven training dataset selection. Crowd funding, etc. There's too many people that want this, and the knowledge on how to do it is out there (many times by now)
I think this is a quite optimistic view... releasing a SOTA model is a collosal capital investment, and unlike free software, it's not iterative - you can't make a small model and improve it one step at a time, you need to risk the whole load of cash, expertise and GPU time up front.
It's only happening now because labs have bucket tons of VC cash to burn and need a big public flex to raise more cash, or because they're subsidised by the Chinese government. I'm not massively confident either of those will stay true forever.
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Unless "some nerds" means "billionaires" - they may want to release new models as open source, but they will not have enough money to train a worthwhile model.
We already had that world, the axis of evil stopped releasing open source models years ago. It’s only because of the Chinese that we kept getting them.
With distillation being so effective I do wonder whether we can just crowd source open alternatives.
Isn't it basically settled that model weights can't be copyrighted as they don't pass the threshold of originality?
That doesn’t sound right. The weights are incredibly valuable and expensive to train.
Looks like the consensus is much more leaning into the direction of non copyrightable.
yes. I don't understand why people are saying these licenses matter. Much of these terms are likely unenforceable.
In EU especially it's already settled, afaik, as are direct model outputs
Its actually not settled yet wrt copyright.
However, there is a more straightforward solution. The allows general use inside a company. The license blocks the "Model-as-a-Service".
So instead, any GPU holder can provide a 'Infrastructure-as-a-service' and have clients provide the model, and then tell the clients that as an optimization they can also provide just the hash and they'll load it from their memory.
I think its good that this license pushes the ecosystem towards such a generic-utility framework, but as a moat to protect a business its banking on most companies being lazy and wasteful.
That pays off more than people like to admit.
> If the Licensee or any of its affiliates operates a Model as a Service business, the Licensee must enter into a separate
Put a JEV on the output to filter out responses that might show its Mistral
Theft is the AI way
It doesn't really work like that. There are "keys" where you train in a specific response to a variety of queries. You can't really fine tune that away either.
Open weight and open source are different things. It's important not to mix that up.
Yep and it's the same for Meta's "open" models which you omitted from the list.
Is there actually a competitive proper actually open model?
I believe Meta's models were never truly frontier in the way Qwen, Kimi, etc., compare to Claude or ChatGPT.
Correct me if I am wrong.
Inkling, Nemotron Super, Beam Reflection (and of course Kimi, Qwen, etc)
> (and of course Kimi, Qwen, etc)
Latest versions of Kimi, Qwen, GLM aren't open, you need to pay them for commercial stuff and comply with PRC laws
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The weights are open, meaning publicly accessible, but you can't have a business profit off of them without paying for a license. That sounds fair and accurate.
HashiCorp has the same business model for their products: you are free to use them even in a business, except if your business is a competitor of their own cloud solutions.
Since the analogy is to source, no, that's not fair and accurate. It's misleading. The fair analogous term would be weights-available.
they are open for everything EXCEPT renting it with a neocloud type business that sells tokens. are you running a neocloud? why do you care?
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So this is "Commons Clause" effectively?
https://commonsclause.com
I don't recall their being a huge backlash to elasticsearch ELv2. Mostly people seemed receptive to blocking the major cloud providers from mooching off the project, and the need to protect their revenue.
People need to make money.
This provider exclusion licenses though.. In a world were someone can point an LLM at your software to launder it.. Not sure what's going to happen.
Unless, i am missing something they haven't claimed open source anywhere. none of them have claimed open source. open weights has never meant the same thing as open source.
To the people who demanded completely open source licensed software, or that complained about "they shove Wayland/systemd down our throats", I've said many times that this is a supply/demand problem. Open source licensed software exists because there is a lot of excess software production capacity, e.g. there are many volunteers. Non-systemd distros are rare because such production capacity is low, e.g., there are few volunteers willing to do this work. To those people I've said: stop complaining about others not doing it for you, if you so want your non-systemd distro or FOSS-licensed whatever, you gotta do it yourself and contribute to the community, or fund an effort.
I got super angry reactions.
Now, the same thing is happening with open weights models, but in on a much more extreme scale. They exist because of excess capacity for whatever reason, and they will cease to exist when this excess capacity reduces. There is no use complaining about something not being open weights. What is productive is funding an effort.
Unfortunately, most complainers want others to do things for them, for free.
Releasing weights even with permissive license, doesn't technically make it "open-source", unless all the method, data and technical inner working to do it is also released. Otherwise, it's just a binary floating in the wild, even if it's under MIT.
Nobody is going to upload 1PB of data for you to download.
I would compare them more to media released under the creative commons license.
For example, you can record yourself playing different instruments, singing, and making other sounds. Then you can go combine all these recordings into a song, and you release the song under a CC license. The CC licenses framework does not demand that you also release the component recordings. But the released song can be remixed by someone else.
(Not making a value judgement, just making an equivalence).
It's effectively shareware. What was old is new again.
No, it's open-weights, as in you can inspect them. This is not Free Software.
If they want to be open source, they also need to, y'know, open the source.
Weights are more like an executable binary. The source is the training data etc
I don't understand this demand. Isn't the training data likely petabytes in size? You want that to be available? I imagine just the index (name,date,source) is a terabyte or two.
As the training data is every written thing they can get their hands on, right?
And wouldn't making that "open source" violate every license that the original data has? You can't release someone else's work.
Unless I have a misunderstanding?
I absolutely want that to be available.
The only way to make sure that a model was trained without hiding weird biases and backdoors is to monitor this process. It also allows anybody (with the hardware resources) to experiment with the model and how it's trained. Will most people want to do that? No, but most people also don't want to recompile their own kernel, that doesn't negate the value of Linux being FOSS.
I hope that, in the long term, I'll be able to use competitive, completely open models in the same way that I can run Linux on my computer.
You're completely right that the licensing of the training data is a big issue though (and I would argue that it should be a much bigger issue right now, even for closed models). I hope that eventually our understanding of the tech will let us build competitive LLMs using purely public domain/Creative Commons-style training data.
I realize that we have a long way to go... but that's a very worthwhile goal IMO.
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I don't usually compile my kernel from scratch, but I'm very glad that the source is open.
How else do you want to reproduce a model if you don't have the training data?
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> And wouldn't making that "open source" violate every license that the original data has? You can't release someone else's work.
Tangent, and not the person you're replying to, but you just independently re-discovered why so many of us despise the AI companies.
Because that's what they are already doing. Selling a repackaged form of the stolen work of all of humanity, without credit or payment.
Can you evolve binary like you can post train weights?
You can read and edit binary code just fine, it's much easier with AI too
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Indeed.
You can hardly re-create the binary from a suitable source, just like the weights just fell from the sky. But you can change the binary (patch the machine code) just like you can adjust the weights. The comparison is quite apt.
Yes?
The whole reverse engineering and cracking scene is built upon this premise, you know.
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Hence the difference between open weights and open source.
But this is neither.