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There is no universal best web search API for an AI research agent. For a new project, Tavily is the clearest fit when you want search and page extraction or crawling in one workflow; Brave fits teams that prioritize results from an independent search index and are prepared to fetch full pages separately. Google Custom Search JSON API is closed to new customers, and the standalone Bing Search APIs have retired, so neither is a straightforward choice for a new build.
Choose based on what your agent needs after a search call, then test candidates on your own queries. Vendor feature lists and prices do not establish which service will produce the best answers or lowest end-to-end cost for your workload.
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How the four options compare now
| Service | Availability as of October 4, 2026 | Best fit | Main decision point |
|---|---|---|---|
| Tavily | Active API product; verify current pricing and terms on Tavily’s pricing page. | An agent that needs search plus extraction, crawling, mapping, or a more integrated research workflow. | Usage is metered in credits, and credit consumption varies by request type and complexity. |
| Brave Search API | Active API product; verify current plan rights and terms on Brave’s pricing page. | An agent for which web search results from an independent index are the main need. | Search responses provide structured snippets rather than raw page content, so full-text use may require another fetch or extraction step. |
| Google Custom Search JSON API | Closed to new customers. Existing customers must transition by January 1, 2027, according to Google’s API overview. | Existing customers who still need the documented API during its transition period. | Do not plan a new integration around an API that is closed to new customers. Google describes Vertex AI Search as an alternative for up to 50 domains, not as a general full-web replacement. |
| Bing Search APIs | Retired August 11, 2025, according to Microsoft’s lifecycle notice. | Not an available standalone API for a new integration. | Microsoft points customers to Grounding with Bing Search in Azure AI Agents for public-web grounding; assess it as a different Azure offering, not continued access to the retired APIs. |
The table describes current product status and documented product fit, not a measured quality ranking.
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What an agent gets from Tavily and Brave
Tavily: search with adjacent research tools
Tavily groups search, extract, research, crawl, and map endpoints in its product overview. Its Search API reference describes reranked, information-rich snippets and documents controls for search depth, result count, date, domains to include or exclude, country, and language. The endpoint can also return optional answer and raw-content fields.
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That breadth can simplify an agent that must find sources and then obtain usable page text. It does not, by itself, prove that Tavily’s results are more relevant or that its workflow costs less than a search API paired with a separate extraction service; compare the complete task your agent performs.
Brave: an independent search index, with extraction to consider
Brave says its API is powered by its own independent web index rather than simply reselling Google or Bing results. Its API product page describes web URLs and text, as well as news, images, video, and model-oriented context. Brave’s comparison guide characterizes search responses as structured snippets rather than raw page contents, which matters if your model needs full article text.
The comparison guide is published by Brave, so claims there about index scale, speed, or relative advantages are vendor claims rather than independent head-to-head findings. An independent index may be a useful property for source diversity, but test whether it improves coverage and answer quality on your application’s actual queries.
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Prices are not directly comparable
These published figures use different meters. A credit, a search request, and a completed research task are not interchangeable units.
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| Service and scope | Published allowance or rate | How to interpret it |
|---|---|---|
| Tavily pay-as-you-go | $0.008 per credit and 1,000 free API credits monthly, as listed on Tavily’s pricing page checked in 2026. | Requests consume differing numbers of credits depending on type and complexity; calculate from the endpoints and workflow you will actually use rather than treating one credit as one answer. |
| Brave Search plan | $5 per 1,000 Search requests, $5 in monthly credits, and capacity of 50 requests per second, as listed in Brave’s pricing documentation checked in 2026. | These figures are for the Search plan. Brave’s separately priced Answers plan has different metering and capacity. |
| Google Custom Search JSON API, existing customers only | 100 free queries per day, then $5 per 1,000 additional queries, with a limit of 10,000 queries per day, according to Google’s documentation, last updated February 18, 2026. | This documented pricing applies during the transition period for existing customers; the API is not open to new customers and is scheduled for discontinuation by January 1, 2027. |
| Standalone Bing Search APIs | No current standalone API price to compare: Microsoft retired the APIs on August 11, 2025. | Evaluate Microsoft’s Azure AI Agents offering separately; the retirement notice does not make its commercial terms equivalent to the former APIs. |
For an agent, measure total cost per accepted answer. Include repeated searches, extraction or page fetches, reranking, and model tokens, rather than comparing only the first search call’s price.
Independent reader supportYour contribution helps us test, update, and keep practical guides available for everyone.How to choose for your workload
- Define the output the model needs. If URLs and concise snippets are sufficient, focus first on search relevance, coverage, freshness, and latency. If the model needs the contents of pages, include fetching and extraction in the design and cost comparison.
- Filter by availability before benchmarking. A new project cannot sign up for Google Custom Search JSON API, and the standalone Bing Search APIs have retired. Existing Google customers should plan around the January 1, 2027 transition deadline.
- Match the retrieval model to the source scope. For work constrained to approved sites, check whether a domain-restricted option is appropriate; Google describes Vertex AI Search as covering up to 50 domains. For broader web retrieval, compare active APIs against the same query set.
- Build a representative query set. Include common questions, obscure or technical queries, and the languages and regions your users need. For each provider, assess relevant-source recall, source quality, freshness, returned URLs, content depth, and performance on those cases.
- Test the whole pipeline under realistic load. Record latency under concurrency, rate-limit behavior, retries, extraction overhead, failures, and total cost per answer your team accepts. A search result that looks good in isolation may not reduce the work or token use needed to produce a reliable response.
- Review operational and content terms. Check privacy, logging, retention, allowed storage, and training rights in the current plan and contract. Brave explicitly says storage of results requires a plan with storage rights, and API access does not grant rights to third-party webpages.
The reviewed vendor materials do not establish a neutral shared benchmark of factuality, recall, latency, or end-to-end agent cost across these four names. Treat vendor descriptions as evidence of advertised features and published terms, not proof of comparative performance.
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