Apify vs Firecrawl
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
Both sides assessedApify compared with Firecrawl
Firecrawl is narrower and cleaner: point it at a URL or a domain and get back markdown or structured JSON suited to feeding an LLM, with a simple API and simple credit pricing. Apify is a general-purpose platform, and its advantage shows up when the target is a specific application rather than a content site, since a Google Maps or Instagram Actor already handles pagination, authentication quirks, and rate limits that a generic crawler will not. Many teams use both: Firecrawl for turning documentation and marketing sites into agent context, Apify for structured extraction from named platforms.
Firecrawl compared with Apify
Apify is a marketplace and compute platform: thousands of prebuilt actors for specific sites, scheduling, storage, and a per-compute-unit bill. Firecrawl is a narrower API that does general web-to-markdown conversion exceptionally well. If your target is a named site with an existing actor (a specific marketplace, a specific social network), Apify saves days. If your targets are arbitrary company websites and the output feeds a model, Firecrawl is simpler and cheaper to reason about.
Choose Apify if
Growth, RevOps, and data teams that need custom web data at a scale a manual list build cannot reach, and that want ready-made scrapers for the common sources with an escape hatch into custom code when a target is unusual. Also strong for anyone wiring web data into an AI agent through MCP.
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.
Side by side
13 attributes| Attribute | Apify | Firecrawl |
|---|---|---|
| Category | GTM Engineering | GTM Engineering |
| Starting price | Free with $5 of monthly platform credit; paid plans from $29 per month ($26 billed annually) (free plan available) | Free (1,000 credits per month); paid plans from about $16 per month billed annually (about $19 billed monthly) (free plan available) |
| Pricing model | Prepaid platform credit with usage metered against it. Each plan includes a monthly credit allowance equal to its price, consumed by compute units (memory multiplied by run time), proxy bandwidth, storage operations, and data transfer. Rented or paid Store Actors carry their own fees on top, set by the Actor's developer as a monthly rental, a per-event charge, or a per-result charge. Seats are not the pricing axis; usage is. | 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 plan | $5 of platform credit per month, community support, limited trial access to rented Actors, and access blocked rather than billed once credit is spent | 1,000 credits per month, 2 concurrent browsers, low rate limits (10 scrape requests per minute) |
| Free trial | Free plan with no credit card required, plus limited trials on most paid Store Actors | Free plan with 1,000 credits, no credit card required |
| Best for | Growth, RevOps, and data teams that need custom web data at a scale a manual list build cannot reach, and that want ready-made scrapers for the common sources with an escape hatch into custom code when a target is unusual. Also strong for anyone wiring web data into an AI agent through MCP. | 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. |
| Setup time | Minutes for a first Store Actor run: sign up, pick an Actor, fill the form, export a CSV. A scheduled pipeline with proxy configuration, webhooks, and a downstream destination is a half day. A custom Actor is a normal software project, measured in days, and its length depends on how hard the target defends itself rather than on Apify. | 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. |
| Learning curve | Low to run existing Actors, moderate to operate the platform well. The two things that take time are understanding the cost model well enough to predict a bill, and learning which proxy and browser settings a given target requires. Writing Actors requires working JavaScript or Python. | 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. |
| Platforms | Web console, REST API, JavaScript and Python API clients, Apify CLI, Docker-based Actor runtime, Hosted MCP server | 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 |
| Compliance | GDPR, SOC 2 Type II, CCPA | SOC 2 Type II, GDPR, DPA available |
| Founded | 2015 | 2022 |
| Headquarters | Prague, Czech Republic | San Francisco, California |
| Ownership | Independent, venture-backed | Independent, venture-backed |
Strengths and limitations
Apify
Strengths
- The Store is the moat: for most common data sources, someone has already built, debugged, and now maintains the scraper, which collapses a two-week project into an afternoon of configuration.
- Real infrastructure underneath, with proxies, headless browsers, storage, scheduling, and retries handled rather than left as an exercise.
- Genuinely usable free tier with $5 of monthly credit, no credit card, and full API and MCP access, so evaluation costs nothing.
- Crawlee is open source and runs anywhere, which meaningfully limits lock-in for teams writing their own crawlers.
Limitations
- Compute-unit billing is hard to predict before you run a job, because cost is memory multiplied by time and both depend on how the target site behaves that day.
- Included platform credit expires monthly with no rollover, so buying a tier for occasional heavy months means paying for unused capacity in the quiet ones.
- Store Actor quality is uneven; some are abandoned, some break silently when a target site changes markup, and the run-success statistics on the Actor page are the only pre-purchase signal.
- Paid Actors add a second billing layer on top of platform credit, and the total cost of a workflow is not visible from any single number on the pricing page.
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.
Pricing compared
Apify
Prepaid platform credit with usage metered against it. Each plan includes a monthly credit allowance equal to its price, consumed by compute units (memory multiplied by run time), proxy bandwidth, storage operations, and data transfer. Rented or paid Store Actors carry their own fees on top, set by the Actor's developer as a monthly rental, a per-event charge, or a per-result charge. Seats are not the pricing axis; usage is.
- Free$0
- Starter$29
- Scale$199
- Business$999
Judged against building the same thing yourself, Apify is inexpensive: a residential proxy pool, headless browser fleet, retry logic, and storage would cost more than $29 a month in engineering attention alone, before any infrastructure. Judged against a fixed-price scraping tool, it is harder to compare, because you are buying capacity rather than a defined output, and the honest answer for month one is that you cannot forecast the bill precisely. The mitigation is straightforward: run the job once at a small limit, read the usage breakdown, multiply. Teams that do this usually find the real cost of a recurring list build lands in the tens of dollars a month, and teams that skip it are the ones who write reviews about unpredictable pricing.
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.
Editorial verdict on each
Apify
Apify is the most complete web scraping platform a small team can buy without a sales call, and its real asset is the Store: for the sources most go-to-market teams need, someone has already written and is still maintaining the scraper, which is the difference between a two-week engineering project and an afternoon. Underneath it, the proxy pool, browser fleet, storage, and scheduling are the parts people underestimate until they have tried to build them, and Crawlee being open source keeps the lock-in honest. The MCP server has made it one of the more useful data sources to hand an AI agent. The cost of all this is a billing model you have to learn: compute metered by memory times time, credit that expires monthly, and a second layer of fees on paid Actors that no headline price reflects. Budget an hour to measure one representative job before committing, set a spending limit on day one, and check an Actor's success rate before you depend on it. Do those three things and it is very good value; skip them and you will write one of the reviews about unpredictable pricing.
Read the full Apify profileFirecrawl
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 profileApify profile last reviewed 2026-08-23; Firecrawl last reviewed 2026-08-23. Pricing is compiled from public sources and can change without notice. See our methodology.