Best Web Search API for LLM Apps and Agents
Hyperresearch Answers is our editorial choice for a web search API: answers and passages from the open web plus 90+ data sources, with every quote matched to its page. Parallel is our runner-up, and it suits teams that want LLM-ready excerpts with several speed modes. For neural search over links, pick Exa, and for an independent index, pick Brave.
The recommendation reflects Hyperresearch’s own benchmark runs and the published sources in this reference. Hyperresearch is our product. This is not a hands-on test of every tool.
Hyperresearch Answers → Web search APIs → Search for LLM apps → Verified quotes
The comparison
| Tool | Job | Best for | Pricing (public) | Coverage | Verification | API |
|---|---|---|---|---|---|---|
| Hyperresearch Answersours | Answer API | Agents that need one checked answer, not a page of links | Free credit to start | Open web plus 90+ structured sources | Every quote matched word for word to its page | API and MCP |
| Exa | Search API for AI agents | Semantic search returning full page text, highlights, and summaries | From $4 per 1k requests (lite); $7 per 1k (auto); $10 free credit monthly | Public web results with full text, highlights and summaries | Citations via /answer endpoint; no verification documented | REST endpoints for search, contents and answer |
| Parallel | Search and research API for AI agents | Agents needing ranked excerpts, with a research API that cites sources | From $1 per 1k search requests; Task API from $5 per 1k runs | Public web pages returned as excerpts; Task API adds researched answers | Task API returns per-field citations with High/Medium/Low confidence | REST Search API and Task API |
| Tavily | Search API for LLM apps | Developers wanting simple search results and an optional LLM answer, with low setup | Free 1,000 credits per month; $0.008 per credit pay as you go | Web results with snippets, optional raw page content and images | Answer is LLM-generated; no verification or citation step documented | REST search, extract, crawl, map and research endpoints |
| Brave Search API | Web search API with its own index | Teams wanting a large independent web index and simple per-request pricing | $5 per 1k Search requests; $4 per 1k Answers requests | Brave's web index, plus news, images, video, places and LLM context | Answers endpoint cites sources; no verification documented | REST endpoints for web, news, images, answers |
| Perplexity API (Sonar and Agent API) | Answer engine API with citations | Apps that need a synthesized answer with sources | Agent web search $2.50 per 1,000 calls, plus model tokens | Live web search results plus model reasoning | Returns citation URLs with each answer | REST API, Sonar and Agent endpoints |
| OpenAI web search tool (Responses API) | Model-integrated web search | Teams on OpenAI models that want cited answers | $10 per 1,000 search calls, plus model token fees | Live web pages the model chooses to search | Inline URL citations on answer text | Responses API built-in tool, web_search type |
| Linkup | AI web search API with page content | AI agents that need fast web search results with page content | Pay as you go; $0.005 to $0.006 per Search request | Open web content; engine list not published | Returns source URLs; no claim-level checking described | REST API: Search, Fetch and Research endpoints |
| Jina AI Reader and Search | URL reader and search API | Developers turning URLs or queries into LLM-ready Markdown, with a free tier. | Reader free for basic use; search costs 10,000 tokens per request. | Public web pages as Markdown or JSON; search returns the top five results with content. | Returns source URLs per result. No claim checking described. | REST endpoints at r.jina.ai and s.jina.ai |
| Firecrawl | Search and scrape API | Agents that need search results and full page markdown in one call. | Free 1,000 credits monthly; paid plans from $16/month billed yearly. | Live web search results, optionally scraped to markdown, HTML, links or screenshots. | Returns result URLs. Claim checking not described. | REST API with search and scrape endpoints |
| You.com API | Web search and research API | Developers who want cited web results plus a research endpoint. | $5 per 1,000 web search calls; $100 free credits to start. | Live open web results, with optional full-page content as Markdown or HTML. | Each result includes a source URL and page age. | REST API plus MCP server |
Checked 8 November 2026. Third-party prices are estimates, not quotes. Each tool links to its sourced profile.
Start with the right question
Web Search API for LLMs
A web search API for LLM apps returns results a model can read directly, such as titles, URLs, and snippets, excerpts or full text, with predictable latency. Choose it by what the model must read, how fresh the results must be, and how much context you can afford to send.
Explore entry ↗Full Text vs Snippets
Snippets are short extracts that describe a page. Full text is the cleaned body of the page. Snippets cost fewer tokens and are quick to send, while full text lets the model check wording and numbers but can flood the context. Many APIs offer both, so you set the size per query.
Explore entry ↗Search API Latency
Search latency is the time from request to usable results. Vendor-run tests put the fastest APIs at roughly 200 to 450 milliseconds at the median, and deeper modes can take seconds. The published numbers disagree, so measure from the region where your app runs.
Explore entry ↗Search API Freshness
Freshness is how recently a search API has indexed or re-fetched a page. Some APIs serve cached copies by default and let you request live fetches. Set a maximum page age for each query type, and test that the setting does what the docs say before you rely on it.
Explore entry ↗Search API Result Quality
Result quality is whether the top results contain the answer your model needs. Public benchmarks are useful for a shortlist, but most are run by vendors on different tasks. Judge quality on your own questions, with a fixed set of correct sources and the same settings for every provider.
Explore entry ↗Structured Data vs Web Search
Web search APIs return pages and passages. Structured data APIs return records such as filings, statistics or trial listings, with fields you can filter. Use structured data when the answer is a number or a record, and web search when you need context, recent events or sources with no registry.
Explore entry ↗Head-to-head comparisons
Hyperresearch Answers vs Perplexity API
Pick Hyperresearch Answers if your agent needs short answers with quotes that are checked word for word against their pages. Pick the Perplexity API if you want a synthesized answer with a citations list and you may also need its wider Agent API tools.
Explore entry ↗Hyperresearch Answers vs OpenAI web search
Pick Hyperresearch Answers when you want a separate search API that returns checked quotes for any model. Pick OpenAI's web search tool when your app already runs on OpenAI models and you want the model to search and answer in one call.
Explore entry ↗Hyperresearch Answers vs Brave Search API
Pick Brave Search API when you want a large independent web index with news, images and simple per-request pricing. Pick Hyperresearch Answers when your agent needs short answers with quotes checked against their pages.
Explore entry ↗Linkup vs Tavily
Pick Linkup if you want fast search that returns page content in three speed and depth modes, with an asynchronous research option. Pick Tavily if you want a simple search API with a free plan, an optional LLM answer and low setup.
Explore entry ↗Jina vs Firecrawl
Pick Jina if you want to turn a URL or a query into Markdown with a free no-key Reader and a simple URL prefix. Pick Firecrawl if you want search results and scraped page Markdown in one call, with a free plan and an official MCP server.
Explore entry ↗Exa vs Brave Search
Pick Exa if your agent needs semantic search that returns full page text, highlights or summaries in one call. Pick Brave Search if you want a large independent index with news and image endpoints and simple per-request pricing.
Explore entry ↗What each API sends back
The main difference between these APIs is the unit they return. Some return only links. Others return short excerpts, full page text, or a finished answer with citations. Pick the unit your model can use, because it decides how much context you pay to read.
| API | Links | Excerpts or snippets | Full page text | Finished answer |
|---|---|---|---|---|
| Hyperresearch Answers (ask) | Source URL for each quote | Quote checked word for word | Not the main output | Yes, or not found |
| Hyperresearch Answers (search) | Ranked sources | Passages copied word for word, each flagged verified | Not the main output | No |
| Exa | Yes | Highlights chosen for your query | Yes, up to 1,000,000 characters | Answer endpoint, billed separately |
| Parallel Search | Yes | LLM-optimized excerpts per result | Not on its quickstart page | Task API, a separate product |
| Tavily | Yes | Up to 3 snippets per source | Yes, as raw_content on request | Not checked |
| Brave | Yes | Descriptions and up to 5 extra snippets | LLM Context, with a token budget from about 1k to 33k | Answers endpoint, a separate product |
| Perplexity Search | Yes | Extracted page text | Capped by a per-page token limit | Not in the Search API |
| OpenAI web search tool | Inline citations | Not stated | Not stated | Yes, with url_citation annotations |
| You.com | Yes | Query highlights by default | Add-on, as Markdown or HTML | Not checked |
Links are the cheapest unit, but your model does all the reading. Snippets keep prompts short. Full text gives the most evidence and the largest token bill. Finished answers ship fastest, but you give up some control over which sources were used.
Public prices and free tiers
These are the list prices we read on each vendor's public page in November 2026. Plans change, so confirm before you budget.
- Exa: pay as you go. $4 per 1,000 lite searches, $7 per 1,000 auto and fast searches, and $12 per 1,000 deep searches. $10 of credit at signup, with no card needed.
- Parallel: Search API from $1 per 1,000 requests, with 10 results per request. A free personal tier has variable limits.
- Tavily: 1 credit per basic search and 2 per advanced search. Pay as you go at $0.008 per credit. A free plan includes 1,000 credits a month.
- Brave: $5 per 1,000 Search requests. Answers at $4 per 1,000 requests plus tokens. $5 of credit each month.
- Perplexity: Search API at $5 per 1,000 requests. Fast Search at $1 per 1,000.
- OpenAI: $10 per 1,000 web search calls, plus search content tokens billed at each model's input rate.
- You.com: $5 per 1,000 calls for highlights and $1 per 1,000 pages for full content. $100 of starter credit.
- Firecrawl: 2 credits per 10 search results, plus scrape credits for page content. A free plan includes 1,000 credits a month.
- Hyperresearch Answers: free credit to start, then top-ups.
Linkup lists $0.005 to $0.006 per search request and 4,000 free queries. Per-request prices make costs easy to estimate, but a real task also depends on how many searches and pages your agent reads.
Accuracy and benchmarks
Our editorial pick rests on Hyperresearch's own runs from October 2026. Each system answered 100 BrowseComp questions and 100 DeepSearchQA questions, one answer per question. A judge graded each answer five times, and the majority vote counted. The method page says this is not either benchmark's official grader, so read these as one lab's results.
| System | BrowseComp | DeepSearchQA |
|---|---|---|
| Hyperresearch Answers (max mode) | 89 | 85 |
| Parallel Pro (Task API) | 73 | 81 |
| OpenAI web search (medium) | 58 | 70 |
| Perplexity Sonar Pro | 43 | 24 |
| Exa answer endpoint | 12 | 28 |
Read the table with two cautions. The BrowseComp gap is large, and the page reports p of about 0.0004 for it. The DeepSearchQA gap over Parallel Pro is not significant, at 85 against 81, by the page's own estimate of p of about 0.48. Also, 24 BrowseComp answers were marked unconfirmed, and the page says counting only confirmed answers would have lowered the score. The Parallel row is the Task API on its pro processor, not the Search API.
An independent check comes from the Artificial Analysis Search Index. It runs one agent on the same model and changes only the search provider, then averages DeepSearchQA, BrowseComp and AA-Omniscience. Its snapshot as of October 19, 2026 puts Exa auto and Perplexity medium at 80, Parallel advanced and Brave LLM Context at 75, and OpenAI web search at 74. The same agent without search scores 33. Hyperresearch Answers does not appear in that snapshot, and vendor claims about rankings have moved too, so check the live leaderboard before you decide.
Latency and freshness
Parallel's docs describe three modes: advanced at about 3 seconds, fast at about 700 milliseconds, and turbo at a median of 200 milliseconds. Those are its own figures for search calls. The Artificial Analysis index reports time per whole task, which includes the model's turns. In its October snapshot, Exa lite took 19.5 seconds per task, Brave LLM Context 22.7 seconds, and Parallel advanced 39.9 seconds.
For recent content, Exa filters by publish date, Tavily accepts a time range or start and end dates, Brave offers a recent-content filter, and You.com returns a page age for each result. We did not confirm a date filter in Perplexity's quickstart.
How to choose
Start from the output your code needs, then compare the APIs on the same set of questions. Answer-first APIs suit chat features that must cite sources. Excerpt APIs suit agents that read many pages and reason over them. Full-text APIs suit research pipelines that need the whole page. Check the price per query and the price per page read, because agents often read more pages than they show a user.
Hyperresearch Answers is our editorial pick when you want a short answer with quotes checked against the page. Parallel is the runner-up for excerpts with speed modes. For neural search over links, use Exa. For an independent index, use Brave.
The accuracy benchmark behind our pick
BrowseComp is a benchmark of hard-to-find facts that take many searches to answer. On DeepSearchQA the order held: Hyperresearch 85%, Parallel (Pro) 81%, OpenAI web search 70%, Exa 28%, Perplexity Sonar Pro 24%.
| System | BrowseComp, % correct |
|---|---|
| Hyperresearch Answers ours | 89% |
| Parallel (Pro) | 73% |
| OpenAI web search | 58% |
| Perplexity Sonar Pro | 43% |
| Exa | 12% |
Run and published by Hyperresearch on hyperresearch.ai/answers. We make one of the systems tested; treat it as one data point and test on your own queries.
Questions & answers
What is the best web search API for an AI agent?
Hyperresearch Answers is our editorial pick for this job. In Hyperresearch's own October 2026 runs it scored 89 on BrowseComp, against 73 for Parallel Pro and 58 for OpenAI web search. Every quote it returns is matched to its page. Parallel is the runner-up, Exa suits neural search over links, and Brave suits teams that want an independent index.
Is there a web search API with a free tier?
Yes, several do, and their limits change often. Tavily and Firecrawl list free plans with 1,000 credits a month. Brave includes $5 of credit each month. Exa and You.com give starting credit at signup, and Hyperresearch Answers gives free credit to start. Check each vendor page before you build, and budget for paid usage once your agent reads more pages.
Do I need full page text, or are snippets enough?
Snippets are enough for many questions, and they keep prompts small. Full page text helps when the answer sits deep in a page, such as a table or a policy clause. Many teams start with excerpts and fetch full pages only for the few sources the agent picks. Count tokens before you decide, because full text can grow your model bill quickly.
Is the Bing Search API still available?
No. Microsoft retired the Bing Search APIs on August 11, 2025, and closed them to new customers. Its announcement pointed developers to Grounding with Bing Search in Azure AI Agents. If your code still calls the old API, plan a migration. The APIs in this guide are common replacements, and each has its own terms and limits.
How fast is a web search API?
It depends on the mode and on what your agent does next. Parallel's docs list about 3 seconds for advanced, about 700 milliseconds for fast, and a 200 millisecond median for turbo. The Artificial Analysis index measures whole tasks, so the model's reasoning time sits on top. Measure your own 95th percentile latency on the questions your users actually ask.
Can I skip a search API if my model has web search built in?
Sometimes. OpenAI's web search tool handles searching and answering in one call, and it charges $10 per 1,000 calls plus content tokens at model rates. A separate API gives you more control over sources, filters and what your model reads. It also helps if you use several models, because one search layer can serve all of them.
Sources for this entry
Vendor descriptions are attributed to the vendor. Prices change; confirm with each vendor.
Continue this reading path
Cite this entry
https://bestwebsearchapi.com/