Which LLM wins at RAG Q&A?
Which LLM wins at RAG Q&A?
RAG (Retrieval-Augmented Generation) helps reduce hallucinations by grounding answers in source documents. This study tested five 7B-class models on computer science literature Q&A to compare accuracy and speed.
- GPT‑3.5 + RAG answered both yes/no and long-form questions effectively.
- Mistral‑7B‑Instruct + RAG led the open-source pack on both question types.
- Orca‑mini‑v3‑7B was fastest (lowest average latency); LLaMa2‑7B‑Chat was slowest.
How they measured it: accuracy and precision for binary questions; human expert and Gemini rankings; and cosine similarity for long answers.
Big picture: With the right RAG setup and infrastructure, open-source LLMs can stand shoulder to shoulder with proprietary models like GPT‑3.5.
Paper by Ranul Dayarathne, Uvini Ranaweera, and Upeksha Ganegoda. Read more: http://arxiv.org/abs/2511.03261v1
Paper: http://arxiv.org/abs/2511.03261v1
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