The Embedder's Dilemma: LLMs Are Better, but at What Cost?
13 Aug 2026
Should you replace your text-embedding pipeline with a large language model? We answer this with a controlled, cost-aware comparison of ten LLMs across six families and 26 embedding models (118M to 14B parameters) on 37 tasks spanning classification, semantic textual similarity…