RAG vs Long-Context Calculator
When is RAG cheaper than stuffing context?
📚 Learn more — how it works, FAQ & guide Click to expand
Learn more — how it works, FAQ & guide
Click to expand
RAG vs long-context calculator
Compare cost of RAG pipeline vs long-context stuffing at your scale.
How to use this tool
- 1
Enter your corpus
Total document tokens to search.
- 2
Enter query volume
Queries per month.
- 3
Pick models
Chat model + embedding model.
- 4
See break-even
Which strategy wins at your scale.
Frequently Asked Questions
When is RAG cheaper?
When corpus × queries × context-size > embedding cost + retrieval cost. Small docs or low query volumes: just stuff it in context. Large docs or high query volumes: RAG wins dramatically.
When is long-context better?
Quality: full-corpus reasoning, low-latency needs. Cost: <1K queries/month over <50K corpus. Setup: no infrastructure overhead. With 1M context models, the line keeps moving toward long-context for medium workloads.
Hybrid approach?
Most production systems use RAG + long-context together: retrieve top-K chunks, stuff retrieved-chunks into a still-generous context (20-50K). Best of both worlds — precision + context.
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100% Privacy. This tool runs entirely in your browser. Your data is never uploaded to any server.