Semantic Similarity Threshold Calibration Is Retrieval System's Most Impactful Parameter

The cosine similarity threshold used to filter retrieved chunks in RAG systems has more impact on answer quality than embedding model choice or chunk size.

Ablation study across 500 QA pairs, 3 embedding models (text-embedding-3-large, text-embedding-ada-002, cohere-embed-v3), and thresholds from 0.60 to 0.92. Optimal threshold varied by domain (0.72 for general, 0.81 for technical docs). Threshold miscalibration caused 40% quality degradation; embedding model swap caused 12% variation on same threshold.

Calibrate similarity threshold on a held-out validation set before shipping any RAG pipeline. Use separate thresholds per document domain. Build threshold monitoring into production: track the percentage of queries that return zero chunks — if it exceeds 5%, threshold needs lowering.