Control cost and credits

The five levers, in order of impact

1. Depth

A deep_review search costs 60 credits; standard costs 5. Nothing else you do matters as much. Default to standard and escalate only when the cheap pass is genuinely thin — in practice that is a small minority of questions.

2. max_papers

Lower ceilings cost less and return faster. Defaults are the tier maximum, so set it explicitly when you only need a direction rather than a survey.

3. Caching

Reads are free, so cache the resource, not just your rendering of it. Key answers on the normalized query plus depth, and honour the storage limits in content-licensing — generated answers you may keep indefinitely; licensed full text you may not.

4. Idempotency

Every POST takes an Idempotency-Key. Without one, a retried request after a timeout is a second charge. This is the cheapest bug to prevent and the most annoying to discover on an invoice.

5. Batching

One extraction over 500 documents costs 2 credits per source and one concurrency slot. Five hundred single-source runs cost the same credits but 500 slots — you will hit rate limits long before you finish.

Worked example

A product answering 1,000 questions a day:

At $10 per 1,000 credits, the middle row is roughly $3,150/month and the last is $18,000 — from one default value. Make depth a product decision, not a default.

Guardrails to put in before launch

• Per-key monthly caps so a batch job cannot starve production (api-keys)

• Alert on X-Credits-Remaining at 20% and 5% of your monthly grant

• Daily reconciliation against usage with group_by[]=endpoint&group_by[]=api_key

• Handle 402 as a product state, not a 500 — degrade to cached or standard results

• Cap agent loops. An LLM with a search_literature tool and no budget will spend it

Measuring

X-Credits-Cost is authoritative per call. /v1/usage is the daily record and may lag live traffic by up to five minutes, so reconcile daily rather than per request.

Related

credit · usage · depth · pricing-and-credits · rate-limits