RAG vs Long Context Calculator
Compare retrieving top-k chunks vs stuffing the whole corpus.
Results update automatically as you type.
Result
RAG (retrieve top-k) is cheaper
$0.00762 vs $0.1290 per query
- RAG input tokens
- 2,900 tokens
- Long-context input tokens
- 100,000 tokens
- RAG / query
- $0.00762
- Long-context / query
- $0.1290
- RAG / month
- $457.50
- Long-context / month
- $7,743.00
Should you retrieve a few relevant chunks (RAG) or just paste the whole document into a long-context model each call? Compare the per-query and monthly cost of both approaches.
How this is calculated
This calculator uses the rag formulas described in our methodology. All figures are estimates for planning; verify current pricing with each provider before relying on them.
Worked example (defaults)
With the default inputs above, here is the result:
Result
RAG (retrieve top-k) is cheaper
$0.00762 vs $0.1290 per query
- RAG input tokens
- 2,900 tokens
- Long-context input tokens
- 100,000 tokens
- RAG / query
- $0.00762
- Long-context / query
- $0.1290
- RAG / month
- $457.50
- Long-context / month
- $7,743.00
Frequently asked questions
When is long context cheaper?+
Only when the corpus is small or query volume is very low. Stuffing a big corpus into every call gets expensive fast.
Does RAG have hidden costs?+
Yes — embedding, storage and retrieval infrastructure. But per-query generation is usually far cheaper than long context.