This comes from the same group as the EfficientViT model. A few months ago, their EfficientViT model was the only modern and small ViT style model I could find that had raw pytorch code available. No dependencies to the shitty framework and libraries that other ViT are using.
I actually tried this last year, before OpenAI released their cheaper embeddings v2 in december. From my experiments, when compared to Bert embeddings (or recent variation of the model) the OpenAI embeddings are miles ahead when doing similarity search.
One detail some might not realize is the fact that research code is often a heaping pile of garbage written by a single graduate student. Some are ashamed of their code and simply don't want to publish shit code. Also, strategically, it is probably better to _not_ publish code than risk being rejected by a future job interviewer because your research code is shitty and you didn't prioritize refactoring it.
With that being said, this is not an excuse for refusing to share paper code or making sure the experiments are reproducible.