Firecrawl vs Jina Reader (2026): which web reader fits your project?

Which one costs less per page?

It depends on page length and volume, because the two bill in different units. Firecrawl charges per page: $0.99 per 1,000 pages on Standard, $0.749 on Scale with monthly billing, rendering included. Jina charges per output token, and publishes no average per page.

As an estimate, assuming 5,000 tokens per page, Jina costs about $0.25 per 1,000 pages on its $50 package and $0.225 on the $500 package. On that assumption Jina costs less per page than Firecrawl at every volume. For pages far longer than 5,000 tokens, such as long documentation pages, the gap closes or reverses; for short pages it widens. Firecrawl's JSON extraction adds 4 credits per page, which changes the comparison for extraction work.

Which one is better for crawling a whole site?

Firecrawl. Its crawl endpoint follows the sitemap by default, takes a page limit (10,000 by default) and a discovery depth, and returns 402 if your credits cannot cover the limit. A separate map endpoint lists a site's URLs for one credit per call.

Jina Reader is a single-URL reader plus a search endpoint; its pages state no crawl feature. To read a whole site with Jina, you collect the URLs yourself, for example from the sitemap, and call the reader once per page.

How do they treat robots.txt and site owners?

Firecrawl respects robots.txt by default and lets only Enterprise customers turn that off; site owners allow or refuse it with the FirecrawlAgent token. Its documentation warns that this token may not be the User-Agent header of the fetch itself.

Jina checks robots.txt when the request carries the X-Robots-Txt header, which names the bot to check as. It also lets the caller override the browser User-Agent. Its pages do not state the default for either. Both approaches leave much of the choice to the customer; ours does not, as the next section explains.

Which one fits AI agents better?

Both serve agents well, in different ways. Firecrawl offers a hosted MCP server, keyless access with a daily cap per IP, and a long list of integrations, including LangChain, LlamaIndex, CrewAI and n8n; OpenClaw bundles Firecrawl as its web_fetch provider.

Jina offers an official remote MCP server whose read_url tool reads up to five URLs per call, an n8n credential, and the URL prefix that any tool able to make a GET request can use. For an agent that reads a few pages per task, Jina's prefix is the simplest start; for an agent that crawls, maps and extracts, Firecrawl covers more.

Where does WebReaderAPI fit between the two?

WebReaderAPI sits closer to Jina in scope, a reader, and closer to Firecrawl in billing, per page, with a crawl endpoint for whole sites. What sets it apart is the payment and the policy rather than the feature list:

• Crypto with no KYC. Top up from $25 in BTC, USDT, USDC, ETH, SOL, LTC.
• Credits that never expire, sold in packs from $3.75.
• A fixed policy for sites. We respect robots.txt: our crawler identifies itself as WebReaderAPI, follows the rules written for it or for all robots, and does not read a page that a site disallows. Refused pages are not charged. If a site refuses our request, we return its answer: we never solve CAPTCHAs, log in to accounts, or try to get around a block or a paywall.

It does less than Firecrawl: no JSON extraction, no browser actions, no map, no free tier. Read the Firecrawl alternative and Jina Reader alternative pages for the details of each switch.

Which should I choose for my use case?

• Prototype or hobby agent: Jina Reader without a key, or Firecrawl's free tier.
• RAG over documentation sites: Firecrawl for crawl and map; WebReaderAPI if you want per-page credits that keep and crypto payment.
• Extraction into fixed fields: Firecrawl's JSON format.
• Many short news or blog pages: Jina's token billing tends to cost less.
• Strict respect of site owners' choices, enforced by the provider: WebReaderAPI.
• No card and no identity documents: WebReaderAPI; neither Firecrawl nor Jina lists a crypto payment option on the pages we read.