JEV COMPARISON
Jev vs. Embedding Models.
Embeddings retrieve by similarity; Jev evaluates a candidate against explicit questions and answer choices.
JEV
✓ Understands a stated decision rubric
✓ Returns bounded answers and probabilities
✓ Useful after retrieval for semantic filtering
EMBEDDINGS
✓ Precompute vectors and search very quickly
✓ Optimized for similarity, clustering and nearest neighbours
✓ Usually the better first-stage retrieval tool
Bottom line
Do not replace a vector index just because Jev can judge relevance. Retrieve broadly with embeddings, then use Jev only when a richer decision justifies the extra call.
QUICK DECISION
Choose by the output you need
- Need prose, code or an open-ended plan? Use a generative model.
- Need nearest-neighbour similarity at very high volume? Use embeddings.
- Need a bounded judgment over known options? Test Jev.
- Need a guaranteed policy or permission rule? Use deterministic code.