Introduction As digital health tools proliferate, large language models (LLMs) and retrieval-augmented generation (RAG) offer promise for delivering accessible, guideline-based nutrition information aimed at preventing cardiovascular disease (CVD). This cross-sectional study investigates how different model architectures perform in providing nutrition guidance aligned with American Heart Association (AHA) recommendations, and whether grounding LLMs in vetted guidelines…