static embedding models im finding quite fast
lee101/gobed https://github.com/lee101/gobed is 1ms on gpu :) would need to be trained for code though the bigger code llm embeddings can be high quality too so its just yea about where is ideal on the pareto fronteir really , often yea though your right it tends to be bm25 or rg even for code but yea more complex solutions are kind of possible too if its really important the search is high quality
lee101/gobed https://github.com/lee101/gobed static embedding models so they are embedded in milliseconds and on gpu search with a cagra style on gpu index with a few things for speed like int8 quantization on the embeddings and fused embedding and search in the same kernel as the embedding really is just a trained map of embeddings per token/averaging