Is Firecrawl or Zenrows cheaper?

Firecrawl starts at Free (1,000 credits per month); paid plans from about $16 per month billed annually (about $19 billed monthly) (free plan available). Zenrows starts at Free (5,000 credits per month); paid plans from $19 per month, or about $16 per month billed annually (free plan available).

Firecrawl vs Zenrows

An independent, review-free comparison compiled by the SaaSTracker editorial team. Both products are profiled in full, and neither can pay for placement here.

The short answer

Editorial assessment

Zenrows compared with Firecrawl

The closest direct comparison for AI use cases, since both return clean Markdown built for LLM consumption. Firecrawl leans toward crawling and site-wide ingestion for retrieval pipelines, with strong crawl and map primitives. Zenrows leans toward reaching pages that actively resist being read, with a deeper proxy and anti-bot layer and a real cloud browser. Choose Firecrawl for documentation and content ingestion at breadth; choose Zenrows when the targets fight back.

Choose Firecrawl if

Technical go-to-market operators, founders, and small engineering teams who need reliable web content as an input to AI workflows: lead research, competitor and pricing monitoring, account enrichment, RAG ingestion, and agent tooling, where writing a few dozen lines of code is acceptable and reliability at scale matters more than a visual builder.

Choose Zenrows if

Technical go-to-market operators, data teams, and AI agent builders who need live content from sites that block ordinary requests, and who would rather pay per successful page than run and maintain their own proxy and headless browser infrastructure.

Side by side

13 attributes

Attribute	Firecrawl	Zenrows
Category	GTM Engineering	GTM Engineering
Starting price	Free (1,000 credits per month); paid plans from about $16 per month billed annually (about $19 billed monthly) (free plan available)	Free (5,000 credits per month); paid plans from $19 per month, or about $16 per month billed annually (free plan available)
Pricing model	Credit-based monthly subscription. Every plan carries a credit allowance; a standard scrape costs one credit, crawled pages and heavier modes cost more, and enhanced or stealth proxy requests cost a multiple of a standard request. Extract additionally consumes tokens. Plans also differ on requests per minute and on concurrent browsers, which is often the binding constraint before credits are. Annual billing is materially cheaper than monthly.	Credit-based subscription with one shared balance across Fetch, Extract, Browser Sessions, and Batch. Credit cost varies by difficulty: one credit for a plain request, five with JavaScript rendering, ten with premium proxies, twenty-five for a protected page needing both, and 25,000 credits per gigabyte of residential proxy traffic. Plans also step up concurrency, which is often the binding constraint before credits are.
Free plan	1,000 credits per month, 2 concurrent browsers, low rate limits (10 scrape requests per minute)	5,000 credits per month, 5 concurrent requests, every feature unlocked, community support only, no rollover
Free trial	Free plan with 1,000 credits, no credit card required	No time-limited trial; the free plan is permanent and requires no card
Best for	Technical go-to-market operators, founders, and small engineering teams who need reliable web content as an input to AI workflows: lead research, competitor and pricing monitoring, account enrichment, RAG ingestion, and agent tooling, where writing a few dozen lines of code is acceptable and reliability at scale matters more than a visual builder.	Technical go-to-market operators, data teams, and AI agent builders who need live content from sites that block ordinary requests, and who would rather pay per successful page than run and maintain their own proxy and headless browser infrastructure.
Setup time	Minutes for the first call: sign up, copy the API key, install an SDK, and scrape a page. A production pipeline with error handling, credit budgeting, and scheduling is a day or two of engineering. Installing the MCP server into an agent client takes a single command.	Minutes for a first successful request: sign up, copy the API key, paste the sample call. Getting a specific hard target working reliably takes longer, usually a session of testing which combination of JavaScript rendering, premium proxies, country, and wait conditions that particular site requires.
Learning curve	Low for the endpoints themselves, which are deliberately few and well documented. The real learning is economic: understanding which calls cost multiples, when to use map before crawl, when a cached snapshot via maxAge is acceptable, and how to cap jobs so a discovery blowout does not consume the month's allowance.	Low for anyone comfortable with an HTTP client, meaningful for anyone who is not. The concepts that take longest are not the API but the domain: why a request needs residential IPs, what a fingerprint check is doing, and how to write backoff logic that does not trip the abuse protection.
Platforms	REST API, Python, Node.js, Go, Rust, Java, Elixir, Ruby, PHP, and .NET SDKs, CLI, MCP server for Claude, Cursor, Windsurf, and other agent clients, Self-hosted via Docker Compose or Kubernetes	REST API, Python, Node.js, and Go SDKs, Command line client, Proxy endpoint (username and password), Chrome DevTools Protocol for Browser Sessions, MCP server for Claude Code, Cursor, VS Code, Windsurf, Zed, and JetBrains
Compliance	SOC 2 Type II, GDPR, DPA available	GDPR, SOC 2, ISO 27001
Founded	2022	2021
Headquarters	San Francisco, California	Getxo, Spain
Ownership	Independent, venture-backed	Independent, venture-backed

Strengths and limitations

Firecrawl

Strengths

Output is genuinely LLM-ready: clean markdown with the navigation and boilerplate stripped, not raw HTML you have to post-process.
One coherent API covers scrape, crawl, map, search, extract, parse, interact, and monitor, so a pipeline does not need four vendors.
The hard infrastructure problems (JavaScript rendering, proxy rotation, anti-bot escalation, PDF and spreadsheet parsing) are handled without configuration.
Open source under AGPL-3.0 and self-hostable, which is a real answer for teams with data residency or compliance constraints.

Limitations

Credits expire monthly with no rollover, so bursty workloads either overpay for headroom or hit the ceiling mid-job.
Credit consumption is hard to predict: stealth or enhanced proxy requests bill at a multiple, crawled pages cost more than simple scrapes, and extract adds token cost on top.
Failed or timed-out requests can still be billed, which inflates spend noticeably on unreliable target sites.
An uncapped crawl bills for every page discovered, and the discovery count on a large site is routinely several times what people expect.

Zenrows

Strengths

Genuinely high success rates on Cloudflare, DataDome, and PerimeterX protected pages, which is the one thing this category is bought for.
One shared credit balance across retrieval, extraction, browser sessions, and batch jobs, so you are not forecasting four separate meters.
A permanent free tier with every feature unlocked, which lets you measure real credit consumption against your actual targets before paying.
Markdown output and an official MCP server make it usable by AI agents without a parsing or integration layer of your own.

Limitations

Credit multipliers make budgeting genuinely difficult: the same 45,000 credit plan is 45,000 plain pages or 1,800 protected ones, and most people discover the difference after their first month.
Extract is still in beta and only covers supported site patterns; on anything else you fall back to parsing HTML yourself, which is the maintenance burden the feature exists to remove.
Premium and JavaScript-rendered calls do not automatically fall back to a cheaper mode when they fail, so your client has to implement the escalation logic itself.
Sending too many failing requests in a short window can get your API key temporarily blocked by the platform's own abuse protection, which surprises teams that ship without backoff.

Pricing compared

Firecrawl

Credit-based monthly subscription. Every plan carries a credit allowance; a standard scrape costs one credit, crawled pages and heavier modes cost more, and enhanced or stealth proxy requests cost a multiple of a standard request. Extract additionally consumes tokens. Plans also differ on requests per minute and on concurrent browsers, which is often the binding constraint before credits are. Annual billing is materially cheaper than monthly.

Free$0
HobbyAbout $16
StandardAbout $83
GrowthAbout $333
ScaleAbout $599
EnterpriseCustom

Measured against building and maintaining your own scraping stack, Firecrawl is cheap. Proxies, headless browsers, anti-bot handling, PDF parsing, and retry logic are a persistent engineering cost, and the Standard plan buys 100,000 pages a month for less than a single seat of most sales tools. Measured against a raw proxy vendor at very high volume it is not the cheapest per request, and measured against a point-and-click scraper it demands code. The honest caution is variance: the headline credit numbers describe simple scrapes, while the workloads go-to-market teams actually run (extract with schemas, blocked sites needing stealth proxies, crawls that discover more pages than expected) consume several times more. Budget on observed spend after a week of real jobs, not on the pricing page arithmetic.

Zenrows

Credit-based subscription with one shared balance across Fetch, Extract, Browser Sessions, and Batch. Credit cost varies by difficulty: one credit for a plain request, five with JavaScript rendering, ten with premium proxies, twenty-five for a protected page needing both, and 25,000 credits per gigabyte of residential proxy traffic. Plans also step up concurrency, which is often the binding constraint before credits are.

Free$0
BuildFrom $19
LaunchFrom $69
GrowthFrom $199
ScaleFrom $549

Priced against the alternative, which is running your own residential proxy contract plus a headless browser fleet plus the engineer who maintains both, Zenrows is straightforwardly cheap at the low end. A team spending nineteen dollars a month to keep an enrichment workflow alive is making an obvious trade. The economics get harder to defend in two places: high-volume crawling of plain HTML, where you are paying an anti-bot premium you do not need, and heavy protected-page work, where the twenty-five credit multiplier compounds fast enough that Scale tier bills arrive sooner than the credit headline suggests. The single shared balance across all four products is a real advantage over vendors that meter each separately, and the permanent free tier makes it possible to measure your own credit burn on your own targets before committing to anything.

Editorial verdict on each

Firecrawl

Firecrawl is the closest thing the current market has to a default web data layer for AI workflows, and for a small go-to-market team it is one of the better value purchases in this category: a free tier that is genuinely useful, a Standard plan that buys 100,000 pages for less than a single seat of most sales software, and output clean enough to hand straight to a model. It is infrastructure rather than an application, so the honest prerequisite is that someone will write code or wire it into a workflow tool; there is no point-and-click builder and there never was meant to be. The things to watch before committing are economic rather than technical: credits expire monthly with no rollover, an uncapped crawl bills for every page it finds, blocked sites escalate to proxy modes costing several times a normal request, and rate limits rather than credit balance are usually what makes a big job slow. Size your plan on a week of observed spend, cap every job, and it earns its place. Skip it if what you actually wanted was a finished dataset with no code anywhere in the chain.

Read the full Firecrawl profile

Zenrows

Zenrows does one thing that is hard and does it well: it gets the page back. For a go-to-market team whose differentiating data lives on sites that reject plain HTTP requests, that is worth far more than the nineteen dollars the first paid tier costs, and the permanent free plan means you can prove it against your own targets before spending anything. The 2026 restructuring into Fetch, Extract, Browser Sessions, and Batch on a single shared credit balance is a real improvement in both clarity and budgeting, and the MCP server makes it one of the more practical ways to give an AI agent honest access to the live web. The reservations are specific rather than generic. Credit multipliers mean the headline allowance tells you almost nothing until you know your target mix, Extract is still beta and falls back to hand parsing on unsupported sites, and there is no scheduling or storage layer, so Zenrows is a component and not a pipeline. Buy it as infrastructure, benchmark it on the free tier against the sites you actually care about, and keep a fallback plan for the targets where nothing reaches one hundred percent.

Read the full Zenrows profile

Firecrawl profile last reviewed 2026-08-23; Zenrows last reviewed 2026-08-23. Pricing is compiled from public sources and can change without notice. See our methodology.