Which API fits the job?
The useful comparison is not 'neural search versus agent search.' It is whether either API supplies the right evidence with fewer calls and predictable cost. Keep extraction and generated-answer options separate from the source-retrieval request.
When to consider Exa
Consider Exa for a mode-specific retrieval workflow, with Contents called only for URLs the agent needs to read. Start with a low-cost mode, then measure whether more expensive retrieval improves task completion.
When to consider Tavily
Consider Tavily for a search/extract workflow where search depth is an explicit credit decision. Basic and advanced are not the same number of requests for a given credit balance.
What is measured and what is documented?
This page compares checked documentation and product contracts. We have not completed a matched All Them APIs run for this pair and assign no synthetic winner or composite score.
External evaluations can help choose a first configuration, but they use different models, topics, result limits and cost definitions. Review the source register before importing a ranking into your own decision.
Request shape, pricing and agent integration
| Decision | Exa | Tavily |
|---|---|---|
| Retrieval choices | Lite, Instant, Auto, Fast and deeper research options | Basic and advanced depth; inspect automatic parameter selection |
| Published entry retrieval rate | Lite / Instant: $4 per 1,000, up to ten results | PAYG basic: $8 per 1,000; advanced: $16 per 1,000 |
| Known-URL reading | Contents endpoint | Extract endpoint |
| Trial accounting | Monthly credit balance plus onboarding-dependent bonus | Monthly API credits; advanced consumes twice basic |
| What we measured | Nine successful source-retrieval attempts, August 23 | No equivalent All Them APIs run yet |
Prices are published USD list rates or explicitly labeled credit calculations, not observed costs from a new test. Extra results, content options, model tokens, account limits and minimum commitments can change the total. Check the linked source for the exact configuration.
A useful evaluation before switching
- Disable optional generated answers while comparing source retrieval. Otherwise you are pricing and timing different jobs.
- Try an ambiguous query and an exact known-source query. Compare useful evidence, not just the number of URLs returned.
- Record content/extraction requests after Search and include them in the total. A cheap initial lookup is not the whole workflow.
Keep the same acceptance criteria across providers and save failures as failures. Avoid changing the target source, query or score threshold after seeing which vendor wins. Measure both useful evidence and the total workflow needed to obtain it.
Sources and review dates
Documentation review: October 27, 2026. Our own measured retrieval runs: August 23, 2026. External reports retain their publisher and measurement window.
Corrections: email faizank@docsalot.dev with an official source.