Local PubMed RAG requires hybrid search, high-end hardware

Building a production-grade local biomedical search system requires a hybrid architecture that prioritizes precise nomenclature over simple semantic similarity. Hybrid search combining BM25 and sparse vectors is mandatory for capturing medical symbols and gene IDs that dense embeddings miss. Command R (35B) is the current preferred local model for RAG due to its native citation capabilities and tool-use training. The BGE-M3 suite provides the most robust embedding and reranking performance for dense, specialized medical corpora. Qdrant or Weaviate are recommended over standard vector databases for their efficient native support of hybrid retrieval strategies. High-end hardware like the RTX 5090 enables running larger quantized models (70B+) with the latency required for interactive research tools.