Exa vs SerpAPI

Below, we compare what each vendor documents and charges: their API references, their pricing pages, their own product claims.

A retrieval benchmark would also be the wrong test. It asks which index finds the better answer, and SerpAPI is a proxy for Google's result page rather than an index competing on that. Scoring it here would hand Exa a win it did not earn.

One number is verifiable from both vendors' pricing pages, and it is a wide gap.

Evaluation methodology

• Exa: $7 per 1,000 search requests covering up to 10 results with text and highlights included, from Exa's published pricing.
• SerpAPI: $25 per month for 1,000 searches on its entry paid plan, from SerpAPI's published pricing.
• Both figures are list price on the smallest paid tier and were read from each vendor's pricing page on 2 August 2026.

SerpAPI is roughly 3.5x the price per call, which is the cost of a live Google SERP rather than a judgment about quality.

Exa is the stronger choice when the agent needs an answer rather than a ranking, and when content comes back ready for a model to read.

Exa returns content, not a list of links

A SERP response is a ranked list of titles, URLs and snippets. To answer a question from it, an agent still has to fetch the pages, strip the chrome, and decide which passage matters. That is three more steps and three more failure modes.

Exa returns page text or query-dependent highlights on the same call, so the passage that answers the query arrives with the result.

A support agent asked "does this plan include SSO" needs the sentence from the pricing page. Everything between the SERP and that sentence is plumbing you have to build, run and pay for.

Those intermediate steps are yours to build, run and pay for:

• After a SERP call an agent still fetches each candidate URL, which is a second round of network calls it has to budget for.
• Each fetched page arrives as raw HTML with navigation, cookie banners and footers to strip.
• Something then has to choose the passage that answers the question, which is usually another model call.

How SerpAPI compares: SerpAPI returns exactly what Google displayed, which is the right output if the SERP itself is what you need, and an intermediate step if it is not.

Exa for people, company and publication search

Exa exposes people, companies and publications as categories on the search call, backed by dedicated indexes rather than by whatever the open web ranks for a descriptive query.

"Series B fintech companies in Singapore with 50-200 employees" is a filter over a structured index for Exa. Through a SERP proxy it is a text query, and what comes back is the pages that rank for those words.

How SerpAPI compares: SerpAPI can query Google verticals, so the entity data you get is whatever Google surfaces publicly rather than a structured index you can filter.

Exa runs its own index

Exa crawls and indexes the web itself, so its results are not downstream of another engine's ranking changes, rate limits or terms.

For a product built on retrieval, that is a supply-chain question. A ranking change upstream becomes your behaviour change, and you learn about it when your output shifts.

How SerpAPI compares: SerpAPI's product is access to Google's results, so its coverage and its constraints follow Google's.

SerpAPI does something Exa does not do at all, and for some jobs it is the only correct tool.

You need to know what Google actually ranks

Rank tracking, SERP feature monitoring and competitive visibility work all require the real Google result, position by position. No retrieval index can substitute for that, including Exa's.

If you are reporting to a client that a page moved from position 8 to position 3, the number has to come from Google's actual result page. A relevance score from a different index does not answer that question and should not be presented as though it does.

How Exa compares: Exa returns what its own index judges most relevant, which is deliberately not the same as Google's ranking and cannot be used to measure it.

Google verticals and rich SERP data

SerpAPI exposes Google's specialised surfaces and the structured blocks that come with them, including knowledge panels and local results, parsed into JSON.

Shopping results, News, Images, Scholar and the answer boxes are each their own dataset. If your product depends on one of them, you are buying access to that surface rather than to web retrieval in general.

How Exa compares: Exa has no equivalent, because it indexes the web rather than reading Google's result page.

Location-specific results

SerpAPI takes an explicit location parameter and returns the SERP as it appears from that place, which matters for local search and for anything geographically ranked.

Local pack results, store availability and any query where the answer differs by city all depend on that parameter being real rather than approximated.

How Exa compares: Exa's index is not localised in that way and does not reproduce a location-specific ranking.

A unified semantic index powering Exa's API products.

Exa Search API

Exa Search provides the highest accuracy of any search API within its latency class. It processes natural language queries to deliver results optimized for token efficiency, complete with citations.

Users can select from six search types spanning budgets from ~250ms to tens of seconds. This includes instant and fast for speed-sensitive loops, auto for adaptive scaling, and a range of deep research modes: deep-lite, deep, and deep-reasoning.

Exa Agent API

The Exa Agent is a high-compute research primitive designed to synthesize information from the entire web. It automates multi-hop reasoning for complex workflows like exhaustive list-building and entity enrichment.

Compute is governed by effort levels of low, medium, high and xhigh, alongside an auto mode that scales resources to meet the task requirements.

Exa Contents API

The Contents API retrieves full-page text, summaries, and structured data according to a user-defined schema. It automatically resolves complex layouts, including PDFs and pages requiring JavaScript rendering.

Query-dependent highlights reduce token consumption significantly; just 500 characters of highlights provide the same retrieval accuracy as the initial 8,000 characters of page content, all with sub-100ms latency.

Exa Code API

The context endpoint, also called Exa Code, is tuned for coding agents and developer workflows. It searches repositories, documentation pages, Stack Overflow and related technical sources, and returns the result already formatted as usable code context.

A tokensNum parameter sets the token budget for each call. It takes a fixed number, or dynamic to let the endpoint size the response to the query.

Exa Monitors API

The Monitors API runs saved searches on a schedule and surfaces what changed since the last run.

If the SERP is the deliverable, use SerpAPI. If the SERP is a means to an answer, Exa removes the steps in between and costs less per call.

These are different products, so this is a decision about which calls belong where rather than a wholesale migration. Exa has native integrations with LiteLLM, Vercel AI SDK, LangChain, and many other providers.

SerpAPI's q becomes Exa's query, and num becomes num_results.

SerpAPI's engine parameter has no Exa equivalent. Where you were selecting a Google vertical, Exa's category is the nearest concept, though it selects an index rather than a Google surface.

Anywhere you were fetching and parsing result URLs after the SERP call, request contents.text or contents.highlights on the Exa call instead and delete that step.

Keep SerpAPI for anything measuring Google itself. Those calls have no Exa equivalent and should not be migrated.