Best-performing embedding models?

I've been looking for up-to-date information about how various pre-trained models compare for clustering and topic modeling with BERTopic – rather than semantic search which is all the rage these days with RAG pipelines.

According to the official pre-trained model evaluations, all-mpnet-base-v2 is best overall, while sentence-t5-xxl is best for sentence similarity. However, both of these models are quite old. Surely there are better pre-trained models available for similarity/clustering?

Looking at the MTEB leaderboard, mxbai-embed-large-v1 appears to be the leading open weights model currently. Should I expect this model to be superior to all-mpnet-base-v2 or sentence-t5-xxl for BERTopic? I've done some informal tests, but I'm not convinced it results in better topics.

The issue names no repository files or tests. Start with the linked Sentence Transformers evaluations and MTEB leaderboard, then compare embedding models specifically for BERTopic clustering and topic modeling rather than semantic search. Done means documenting a current, evidence-based recommendation and explaining how it compares with all-mpnet-base-v2 and sentence-t5-xxl.