An open-frontier-competitive model for under $20M, all in

today um so look forward to that talk um but in this case they trained a model this is a fully open um US-made model um uh on 17 trillion tokens that we curated from public uh data sets no proprietary data involved here um and no closed model usage so no asking Claude uh to do this for you Um, and with that, RC was able to train a model that is competitive with the Open Frontier. Um, matches uh, GLM5 and and Kimmy on many tasks. Um, and even outperforms Claude on a couple tasks. Um, but I think what's most exciting about this is that the RC team um, had not trained a model prior to uh, the middle of last year when they started working with us. Um and critically in total across salaries, across compute, across R&D, um across everything for this and several other models, they were able to get to a model that's competitive with the open frontier, um for less than $20 million total. That includes all the repetitions, that includes compute, that includes everything. So if you hear this story over and over again, oh, if I want to customize a model, it's going to cost hundreds of millions of dollars. That's just not true. you can train an immensely powerful model especially in a narrow domain for high six figures million dollars. It's very doable to get a model that's extremely performant. Um this is for a general purpose. So this is kind of the upper bound of that. Um and data quality is how you can do that.