#745 · AI & Technology Tool

Retrieval Augmented Generation Token Budget Calculator

Plan the token demand of a retrieval augmented generation workload before estimating cost or capacity. Enter the fixed prompt, retrieved context, expected answer length, request volume, planning period, and a safety buffer. The calculator separates retrieval tokens from other input and output tokens, then reports both the base workload and a buffered budget so you can size quotas without hiding the assumptions.

Calculator

RAG workload assumptions
requests
Expected production requests each day.
tokens
System prompt, user query, and non-retrieved context.
chunks
Average number of passages placed in the prompt.
tokens
Average tokenized size of one inserted passage.
tokens
Expected generated answer length.
days
Number of workload days to budget.
%
Extra capacity for variation, retries, and estimation error.

How to use this calculator

  1. Enter expected daily RAG request volume and the number of days in the planning period.
  2. Separate fixed prompt tokens from retrieved chunks and their average token size.
  3. Add the expected generated output length and a safety buffer.
  4. Use the buffered total as the planning budget; use the component totals to identify optimization targets.

Formula

Retrieved tokens/request = chunks × tokens/chunk
Base tokens = requests/day × days × (fixed input + retrieved + output)
Budget = base tokens × (1 + buffer% ÷ 100)

What the result means

The main result is the total buffered token allowance for the selected period. Retrieval share shows how much of the input is attributable to inserted passages, while tokens per request is useful for model-context and throughput planning.

Token counts depend on the selected model tokenizer. Use measured production averages when available; this is a planning estimate, not a billing invoice.

Example calculation

For 10,000 requests/day over 30 days, with 800 fixed input tokens, 5 chunks × 300 tokens, 500 output tokens, and a 15% buffer:

Retrieved/request = 1,500
Tokens/request = 2,800
Base = 840,000,000 tokens
Budget = 966,000,000 tokens

Tips for better results

  • Measure chunk token counts after tokenization, not by character count.
  • Track retrieved passages that are later truncated by the context window.
  • Use separate scenarios for routine and long-form queries.
  • Reduce duplicate context before reducing answer quality.
  • Include retries or fallback-model calls in the buffer if they are common.

Frequently asked questions

Does the RAG token budget include embedding tokens?

No. This calculator covers tokens sent to and generated by the language model. Add embedding workload separately if your provider bills it.

How are retrieved context tokens calculated?

They equal the average retrieved chunks per request multiplied by the average tokens in each inserted chunk.

Should reranker input be included?

Include reranker tokens separately if it uses a billed language model; this page models the final generation request only.

What if requests retrieve different numbers of chunks?

Use a measured average for baseline planning and increase the safety buffer or run a high-volume scenario for peaks.

Can the result exceed a model context window?

The period total can, but the per-request total must fit the model context limit after accounting for any provider-specific overhead.

Variables and units

VariableMeaningUnit
RRequests per dayrequests/day
FFixed non-retrieved inputtokens/request
C × TRetrieved chunks × tokens/chunktokens/request
OGenerated outputtokens/request
BSafety bufferpercent

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