Decoding Embedding Models: Why Your RAG Is Only as Good as Your Vectors

Embedding models serve as the foundation of RAG systems by converting text into mathematical vectors, where poor vector quality leads to failed retrieval regardless of LLM performance. Popular options include Hugging Face's privacy-focused models like all-MiniLM-L6-v2 for speed and OpenAI's text-embedding-3-small for enterprise scale accuracy.