We benchmarked 18 RAG pipelines against an agent loop on Google's FRAMES. The best pipeline hit 78.9%. The agent loop hit 92.7%.

A benchmark study compared 18 RAG pipelines against an agent loop on Google's FRAMES dataset, using 824 multi-hop questions. The best RAG pipeline achieved 78.9% accuracy, while the agent loop reached 92.7%. The study investigated the impact of techniques like hybrid search, reranking, query decomposition, and query expansion. Answer accuracy was graded by LLM judges (Claude Sonnet 5 and Gemini Flash 3.8) with high agreement (Cohen's κ 0.93–0.98), ensuring answers were based on retrieved text, not model memory.