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Synthetic Data Token Budget Planner

This planner estimates the token volume required for a synthetic data generation run. It combines the number of records, average prompt and generated-response length, repeated generations, and a reserve for retries or rejected samples. The result helps teams size API quotas, compare model options, and avoid stopping a dataset build because the token allowance was set too low.

Use it during experiment design or before a production batch. The estimate is especially useful when one source prompt can produce several candidate records or when quality filters cause part of the output to be regenerated. It reports the base token demand, reserve tokens, total generation attempts, and the final planned budget. Actual usage can differ when prompts vary substantially or the model produces shorter or longer outputs than expected.

Synthetic data generation assumptions

records
tokens
tokens
runs
%
Result
—
planned tokens
Base tokens—
Reserve / overhead tokens—
Total turns or generations—
Tokens per turn or generation—

1. Set the record target
Enter the number of accepted synthetic records you want at the end of the run.

2. Estimate prompt size
Use the average token count for instructions, examples, metadata, and source context sent with each generation.

3. Estimate output size
Enter the expected tokens in one generated record before post-processing.

4. Include candidate generations
Specify how many candidate outputs are produced per accepted record.

5. Add a reserve
Allow for retries, safety-filter rejections, malformed output, or quality-screen failures.

6. Review the budget
Use total planned tokens for quota requests and cost modeling, then refine the assumptions after a pilot batch.

Base tokens = Volume × Turns or generations × (Input tokens + Output tokens) Total budget = Base tokens × (1 + Reserve % ÷ 100)

Volume is the number of records or tickets in the planning period. The reserve covers additional context, retries, or rejected outputs depending on the workflow.

What the result means

The main result is the full token allowance implied by the entered workload and reserve. It is a planning estimate, not a provider invoice.

Use separate input- and output-token prices when converting this volume into cost.

Given: 100,000 accepted records, 220 prompt tokens, 380 output tokens, 2 generations per record, and a 12% reserve.

Calculation:
Tokens per generation = 220 + 380 = 600
Base generations = 100,000 × 2 = 200,000
Base tokens = 200,000 × 600 = 120,000,000
Reserve tokens = 120,000,000 × 0.12 = 14,400,000
Total token budget = 134,400,000 tokens

Result: Plan for about 134.4 million tokens. The reserve covers roughly 24,000 extra generation attempts at the same average token size.

Should rejected records count toward the token budget?

Yes. Tokens are consumed even when an output is later rejected, so expected rejection and retry volume belongs in the reserve percentage.

How do I estimate tokens before running the job?

Tokenize a representative sample of prompts and outputs, then use the sample averages. A larger and more varied sample is better when record formats differ.

Does the planner include embedding or fine-tuning tokens?

No. It covers generation input and output tokens only. Add separate budgets for embeddings, training, evaluation, or moderation when those steps are part of the pipeline.

What happens if generations per record is below one?

That input is invalid because each accepted record requires at least one generation attempt. Use a value above one when several candidates are created and only one is retained.

How should I choose the reserve percentage?

Base it on pilot-run rejection, timeout, and retry rates rather than a generic benchmark. Increase it when output validation is strict or source prompts are inconsistent.