Tavily: live, SERP-grounded context for factual agent queries; strongest ecosystem integrations in the category; $8–16/1k pay-as-you-go. Exa: neural index for search-by-meaning — similarity, people/company, code; $7/1k + $1/1k pages for contents; sub-200 ms fast modes. Route by query type, not by brand. If your traffic is mostly factual, also weigh the option with a public quality benchmark: SERPdive, $5/1k with extraction included.
Two architectures, two failure modes
Tavily searches the live web at query time and returns context — snippets by default, raw page content on request, advanced mode (2 credits) digging deeper. Failure mode: cost creep at scale and token-heavy payloads your LLM re-reads on every turn.
Exa embedded the web into its own index and retrieves by semantic proximity — which makes “find startups similar to Datadog” a one-liner and makes “what did the Fed announce this morning” dependent on crawl freshness. Failure mode: paying embedding-index prices (and a second contents call) for keyword-shaped factual queries that never needed similarity.
Head to head
| Tavily | Exa | |
|---|---|---|
| Retrieval | Live SERP-grounded | Own neural index |
| Query style | Questions, keywords | Meaning, similarity, entities |
| Freshness | Live web at query time | Crawl-dependent |
| Contents | Included (snippets / raw) | Billed separately ($1/1k pages/type) |
| Per 1k searches (payg) | $8 basic · $16 advanced | $7 + contents · deep $12–15 |
| Free tier | 1,000 credits/mo | Trial credits |
| Latency | ~seconds | sub-200 ms fast modes (retrieval only) |
| Signature strength | Framework ecosystem | People/company/code search |
| Owned by | Nebius (2026) | Independent |
- Your queries are factual and current — news, prices, filings, docs.
- You want framework modules (LangChain, LlamaIndex, n8n) doing the plumbing.
- You value one call returning content over minimum retrieval latency.
- Your queries are semantic — “more like this”, thematic exploration, related-work hunts.
- You search people, companies or code as first-class entities.
- You need sub-200 ms retrieval and can defer content fetching.
The question this comparison hides
If you got here with factual agent traffic, the real decision isn't Tavily vs Exa — it's which SERP-grounded API feeds your model best per dollar. That question has a measured answer: on a public 1,000-question blind benchmark, SERPdive wins 60.7% of decided duels against Tavily's default search while returning 20.2% fewer tokens, at $5/1k credits with extraction included. The full chain is replayable: the numbers are here.
Add a third column to your eval for free — 1,000 credits a month, no card, answer-ready output.
Get your free API keyFrequently asked questions
Which is better, Tavily or Exa?
Wrong axis. Tavily is SERP-grounded context retrieval for agents; Exa is a neural index you query by meaning. For factual, current-web questions Tavily's model fits better; for similarity and entity search (“companies like X”, people lookup, code search) Exa is alone in the field. Teams with both workloads often run both.
Which is cheaper, Tavily or Exa?
Depends on usage shape (July 2026 pricing). Tavily pay-as-you-go: $8/1k basic, $16/1k advanced. Exa: $7/1k search plus $1/1k pages per content type when you read the pages — about $17/1k for 10-result searches with full text. At committed volume Tavily reaches $5–10/1k. Neither is the budget option; that is a different shelf (Serper ~$1/1k for links, SERPdive $5/1k with content included).
Is Exa faster than Tavily?
For raw retrieval, generally yes — an index lookup beats live SERP work, and Exa advertises sub-200 ms fast modes. The gap narrows once you fetch page contents (a second, billed step). Tavily's and SERPdive's one-call-with-content model trades peak retrieval speed for not needing that second step.
Where does SERPdive fit in this comparison?
Same category as Tavily — SERP-grounded, extraction-native — with one distinction: it is the option whose quality claim is a public, replayable benchmark (60.7% of decided blind duels vs Tavily default search, 20.2% fewer tokens, 1,000 questions). If you land on the Tavily side of this page, that benchmark is the natural next read.