[simonw]

From that article:

> The release of DeepSeek-R1 is an amazing boon for the community, but they didn’t release everything—although the model weights are open, the datasets and code used to train the model are not.

> The goal of Open-R1 is to build these last missing pieces so that the whole research and industry community can build similar or better models using these recipes and datasets.

[boznz]

Genuine question, but how do you replicate the effort exactly without $5M in compute? and can you test that the published weights etc are actually those in the model?

Am I missing something?

[simonw]

The $5.5m in compute wasn't for R1, it was for DeepSeek v3.

The R1 trick looks like it may be a whole lot cheaper than that. R1 apparently used just 800,000 samples - I don't fully understand the processing needed on top of those samples but I get the impression it's a whole lot less compute than the $5.5m used to train v3.