Do you still need embeddings for semantic search? - my little experiment

Lax Meiyappan tested whether BM25 keyword search, with an LLM query rewrite and a reranker, could replace Qwen3-Embedding-0.6B on SciFact, NFCorpus and FiQA. Embeddings won or tied in every fair comparison, leading by about a point on the first two sets and eight to nine on FiQA once both used the same reranker. The rewrite added little after reranking. Replacing 54 FiQA names with invented codenames narrowed the gap to 1.3 points, but embeddings stayed ahead. These are one author's unreplicated results, and the cost comparison reflects his pricing.