For example, 3.3 Tbyte for code reasoning, 4.5 Tbyte for mathematical reasoning, 8.4 Tbyte of pre-train behaviors, and so on.
I did not compute the sum of the dataset sizes, but it appears to be some tens of Tbyte. Nonetheless, I assume that this amount of training data is more than an order of magnitude less than what OpenAI, Anthropic and the like have used, which must have been at least many hundreds of Tbyte, but more likely several thousands of Tbyte of data.
* https://github.com/ifm-ai/xllm * https://github.com/ifm-ai/horizon-post-train
Their previous model, K2 Think V2, was release with fully open training data and recipe, so I would imagine that they are committed to that, but yeah, the repos for this new model are still just placeholders.
* https://mbzuai.ac.ae/news/k2-think-v2-a-fully-sovereign-reas... * https://github.com/LLM360/Reasoning360