RAG vs Fine-Tuning: Decision Bench

SOURCE–

FT CUTOFFJAN 2026

RETRIEVAL HIT–

TRAINING AGE–

LATENCY R·F–

LATENCY SIMULATED · BARS ILLUSTRATIVE

Bench parameters

Source date MAR 2026

FT CUTOFF JAN 2026 · SLIDE PAST IT

RAG·corpus 80%

RAG·retriever 75%

FT·strength 70%

FT·data q 80%

Teaching simulation

Scores and latency here are illustrative rules, not benchmarks. Real choices depend on model, data, privacy, evals, and budget. Prompting, tool calls, and structured outputs often beat both, and RAG plus a fine-tune is a common pairing, not a rivalry. Base models have cutoffs too; RAG freshness comes from the index. Tap any bar, tag, or chip for why.

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