you can look it up in the blog. RAG is not super great because of two reasons, single embedding vector models are not that good and stopped improving and second most models are not good at looking up information. we spend great time on improving the modeling side by inventing on the indexing level [1, 2]. and now we trained our model to be very good at search. it is matching the quality of Opus 5 and GPT 5.6 Sol while being faster. it helps your main agent to do the task at greater quality, while reducing cost per task.

[1]: https://www.mixedbread.com/blog/multimodal-late-interaction-... [2]: https://www.mixedbread.com/blog/wholembed-v3