There are no open source models, at least not useful ones (yet) [0]. Open weight is not the same as open source. The current "open weight" models are just opaque binary blobs you can run on your own computer instead of through a web API.
This viewpoint doesn't make any sense to me. The weights + inference code are the "source code" for AI. I literally don't know what else you are demanding for the "open source" label.
> I literally don't know what else you are demanding for the "open source" label.
you need to "literally" go read the definition of open source software or even ask an LLM to define it for you. Weights + inference code are not the source code they're more like the compiled binary. Making modifications to the behavior of a model with additional training is like writing a mod for minecraft. Sure, you can change things but it doesn't make it open source.
Calling these models "open source" is an old trap that software companies use to use. Free to download but then, once you're fully comitted, the trap snaps shut and you must pay up to continue.
Nemotron Super is sort of open source in the sense that Nvidia provides almost everything you need to replicate it from scratch. Of course it’s performance is not exactly stellar but it could be a good starting point for other research teams.
The open weight model providers don't provide the training data or the build tooling. You cannot reproduce the model yourself, or even really know what the model contains. They don't even provide high-level catalogues/descriptions of the training data. An improvement would be something like "trained on the entire WWW up to Aug 1 2026". Or "trained on a Wikipedia archive + Anna's Archive and everything we were able to scrape from Github". They don't provide any of this stuff.
I don't mind open-weight models, but they are not open source. It's like bringing home a dog from the rescue and just hoping that it doesn't have a history of biting kids in the face. You just can't know, because you don't know the full history. You can try to add new training (fine tune) to tell it not to bite kids, but that's it.
There is also https://apertus-ai.org/ but yeah, "not useful yet" if you were looking to replace your coding agent. Very useful if you are doing LLM research.
> long live open source models
There are no open source models, at least not useful ones (yet) [0]. Open weight is not the same as open source. The current "open weight" models are just opaque binary blobs you can run on your own computer instead of through a web API.
[0] https://allenai.org/
This viewpoint doesn't make any sense to me. The weights + inference code are the "source code" for AI. I literally don't know what else you are demanding for the "open source" label.
If you think of LLMs as programs. The weights and inference code are very much a binary.
While the training code and data are the true source. Since if you want to robustly modify the LLM that's actually what you need.
But since "compilation" (training) is extremely compute intensive this isn't something accessible to anyone without an entire datacenter.
Anyway semantics aside having the binary is still infinitely better than dealing with an api as far as privacy and control go.
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> I literally don't know what else you are demanding for the "open source" label.
you need to "literally" go read the definition of open source software or even ask an LLM to define it for you. Weights + inference code are not the source code they're more like the compiled binary. Making modifications to the behavior of a model with additional training is like writing a mod for minecraft. Sure, you can change things but it doesn't make it open source.
Calling these models "open source" is an old trap that software companies use to use. Free to download but then, once you're fully comitted, the trap snaps shut and you must pay up to continue.
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> I literally don't know what else you are demanding for the "open source" label
Training data and code.
Nemotron Super is sort of open source in the sense that Nvidia provides almost everything you need to replicate it from scratch. Of course it’s performance is not exactly stellar but it could be a good starting point for other research teams.
Nemotron is okay. Better than Olmo.
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Can you explain what's missing for the "open source" label that open-weight models like DeepSeek/Quen/GLM/etc don't release?
Is it just the supplementary data/code for how they were trained, not just the final product?
The open weight model providers don't provide the training data or the build tooling. You cannot reproduce the model yourself, or even really know what the model contains. They don't even provide high-level catalogues/descriptions of the training data. An improvement would be something like "trained on the entire WWW up to Aug 1 2026". Or "trained on a Wikipedia archive + Anna's Archive and everything we were able to scrape from Github". They don't provide any of this stuff.
I don't mind open-weight models, but they are not open source. It's like bringing home a dog from the rescue and just hoping that it doesn't have a history of biting kids in the face. You just can't know, because you don't know the full history. You can try to add new training (fine tune) to tell it not to bite kids, but that's it.
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There is also https://apertus-ai.org/ but yeah, "not useful yet" if you were looking to replace your coding agent. Very useful if you are doing LLM research.
I really like molmo 2
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