NVIDIA Nemotron 3 Ultra is a relatively big LLM for which a part of the training data is public, but not all of it.
Nobody who has trained a really good and big LLM can afford to make public all the training data, as much of it must have been copyrighted.
The weights for GLM 5.2 will be published in a few days on Hugginface.co.
While I would want very much to have access to the entire training set of a big LLM, I would want that in order to be able to run traditional search tools on it, to get accurate answers, instead of possibly hallucinated answers.
I could not use that dataset to perform the training myself, as that requires too expensive hardware.
On the other hand, with the open weights of even a very big LLM like GLM 5.2, I can run inference on any computer, with the weights stored on SSDs. Obviously, inference will run slowly, probably at less than 1 token per second at the size of GLM 5.2, but that is still useful in some cases.
NVIDIA Nemotron 3 Ultra is a relatively big LLM for which a part of the training data is public, but not all of it.
Nobody who has trained a really good and big LLM can afford to make public all the training data, as much of it must have been copyrighted.
The weights for GLM 5.2 will be published in a few days on Hugginface.co.
While I would want very much to have access to the entire training set of a big LLM, I would want that in order to be able to run traditional search tools on it, to get accurate answers, instead of possibly hallucinated answers.
I could not use that dataset to perform the training myself, as that requires too expensive hardware.
On the other hand, with the open weights of even a very big LLM like GLM 5.2, I can run inference on any computer, with the weights stored on SSDs. Obviously, inference will run slowly, probably at less than 1 token per second at the size of GLM 5.2, but that is still useful in some cases.