Apify and Firecrawl both turn websites into data, and there the similarity ends. Firecrawl bills per page. Apify bills per compute-hour plus bandwidth. That single difference makes a straight price comparison meaningless โ the same 10,000-page crawl can cost roughly $1 or $58 on Apify depending on the target, while Firecrawl charges a predictable $9.90. Here is how to work out which one your workload actually wants.
The comparison, by the numbers
Public pricing data, September 2026
$0.99
Firecrawl per 1,000 pages
Standard plan, basic scrape
30,000+
Apify ready-made scrapers
Firecrawl has none
5x
Firecrawl JSON extraction cost
Advanced formats add 4 credits/page
$7-8
Apify residential proxy per GB
Billed on top of compute
The short answer
Choose Firecrawl if you are feeding a language model. It returns clean, LLM-ready markdown or schema-guided JSON from a single API call, and its per-page pricing is predictable enough to quote a client. Choose Apify if you are scraping many different sites, fighting serious anti-bot defences, or need a scraper for a specific platform that someone has already built.
- Firecrawl โ RAG pipelines, AI agents, documentation ingestion, content extraction. One endpoint, clean output, forecastable bills.
- Apify โ Google Maps, Amazon, Instagram, LinkedIn, or any site with real defences. 30,000+ pre-built Actors and managed residential proxies.
- Both โ genuinely common. Firecrawl for the long tail of ordinary pages, Apify for the handful of hard targets that break everything else.
They are not really competitors
Firecrawl is an API for turning the web into model input. You call /scrape with a URL and get markdown, HTML, schema-guided JSON, a screenshot or a brand profile back. There is nothing to build and nothing to maintain.
Apify is a platform for running scrapers. Its unit is the Actor โ a containerised program that takes input, runs on Apify's cloud and writes to a dataset. You run someone else's, fork it, or write your own with Crawlee. It is general-purpose automation infrastructure that happens to be excellent at scraping.
So the honest framing is not "which is better" but "which shape is your problem". Extracting readable content from ten thousand ordinary URLs is a Firecrawl job. Pulling structured listings out of a site that actively fights you is an Apify job.
Firecrawl pricing
Firecrawl sells credits where one credit equals one page on a basic scrape, crawl or map. Plans run Free at 1,000 credits, Hobby $19 for 5,000, Standard $99 for 100,000, Growth $399 for 500,000, and Scale $749 for 1,000,000, plus custom Enterprise.
Firecrawl plans
Priced per page, with a sharp value cliff at Standard
| Benchmark | Free Trial | Hobby Solo | Standard Production | Growth Scale |
|---|---|---|---|---|
Monthly price | $0 | $19 | $99 | $399 |
Credits per month | 1,000 | 5,000 | 100,000 | 500,000 |
Cost per 1,000 pages Hobby is 3.8x Standard's unit rate | โ | $3.80 | $0.99 | $0.80 |
Concurrent browsers | 2 | 5 | 25 | 50 |
Rate limit | 10/min | 100/min | 500/min | 5,000/min |
Note the cliff. Hobby to Standard is 20 times the credits for 5.2 times the price, which drops the unit rate from $3.80 to $0.99 per thousand pages. If you are on Hobby and regularly running out, you are paying nearly four times the going rate โ Standard is almost always the right move rather than topping up.
Not every call costs one credit, either. Search costs 2 credits per 10 results, browser interaction 2 credits per minute, monitoring 1 credit per page when a check errors, and the advanced formats โ JSON, Question, Highlight โ add 4 credits per page. That last one matters most: schema-guided JSON extraction takes a page from 1 credit to 5, so Standard's 100,000 credits becomes 20,000 extracted pages, and your effective rate goes from $0.99 to $4.95 per thousand.
Structured extraction quintuples your per-page cost
If your pipeline uses Firecrawl's JSON mode on every page, budget 5 credits per page, not 1. Where the schema is simple, it is often cheaper to scrape to markdown at 1 credit and run your own extraction pass โ measure both before committing a large crawl.
Apify pricing
Apify sells prepaid platform usage, and on every paid tier your subscription buys exactly its own value in credits: Free gives $5, Starter $19, Scale $199, Business $999. What the higher tiers actually buy is concurrency, memory ceiling, support โ and a better compute rate.
Apify plans
You are buying capacity, not a bigger credit multiplier
| Benchmark | Free | Starter | Scale | Business |
|---|---|---|---|---|
Monthly price | $0 | $19 | $199 | $999 |
Platform credits Equal to the price on paid tiers | $5 | $19 | $199 | $999 |
Concurrent runs | 5 | 32 | 128 | 256 |
Max memory | 16 GB | 64 GB | 256 GB | 512 GB |
Compute rate per unit 1 unit = 1 GB RAM for 1 hour | $0.20 | $0.20 | ~$0.15 | $0.13 |
Compute is only one of four meters. Storage, data transfer and proxies are billed separately, and residential proxy traffic at $7โ8 per GB is frequently the largest line on the invoice. Datacenter proxies are far cheaper at $0.60โ$1 per IP, but many defended sites reject them outright. Credits also expire monthly with no rollover.
What 10,000 pages actually costs
This is where the units problem becomes concrete. Firecrawl's answer is one number. Apify's answer is a range, because you are paying for how long pages take rather than how many there are.
- Firecrawl, Standard plan โ 10,000 credits at $0.99 per thousand = about $9.90. With JSON extraction on every page, roughly $49.50.
- Apify, simple HTTP scraper โ a 1 GB Actor clearing ~2,000 pages an hour needs about 5 compute units. At $0.20 that is roughly $1 in compute, plus modest datacenter proxy cost.
- Apify, headless browser on a defended site โ a 4 GB Actor managing ~400 pages an hour needs about 100 compute units, or $20. Add residential proxy at half a megabyte per page โ 5 GB at $7.50 โ and you are at roughly $58.
So Apify is ten times cheaper than Firecrawl on easy targets and six times more expensive on hard ones, for identical output. Firecrawl's flat rate is not the cheapest option; it is the predictable one, and on quoted client work that is often worth more than the saving.
Apify is cheapest exactly where scraping is easy, and priciest exactly where you need it most. Firecrawl charges the same either way.
How these numbers were derived
Plan prices, credit allowances, rate limits, compute rates and proxy pricing come from Apify's and Firecrawl's public pricing pages as of September 2026. The 10,000-page cost figures are our own modelling, built on stated assumptions about render time, memory and page weight โ real Apify costs vary enormously by target and are not vendor-published. Treat them as illustrative arithmetic, not quotes. Disclosure: links to both Apify and Firecrawl are affiliate links, and neither vendor reviewed this article.
Capabilities head to head
Pricing aside, the two differ most in what they hand you. Firecrawl gives you finished output; Apify gives you a platform and the raw materials.
Capabilities
Finished output versus a platform
| Benchmark | Firecrawl Per-page API | Apify Scraping platform |
|---|---|---|
Pre-built site scrapers | None | 30,000+ Actors |
LLM-ready markdown | Native output | Build it yourself |
Structured JSON extraction | Schema or prompt | Write your own parser |
Managed proxies | Bundled in credit | Metered separately |
Hard anti-bot targets | Limited control | Residential IPs, fingerprinting |
Cost predictability | High โ per page | Low โ four meters |
Custom crawler tooling | SDKs only | Crawlee, open source |
MCP server for agents Both are agent-ready | Yes | Yes |
Where Firecrawl wins
Anything ending in a language model. Firecrawl was built for the RAG era, and it shows: /scrape returns clean markdown with boilerplate stripped, and JSON mode takes a schema or a plain prompt and returns structured objects without you writing a parser. That is the entire job for documentation ingestion, knowledge bases and agent context.
It also wins on time to first result and budget certainty. One API call, no Actors to evaluate, no compute units to reason about, and an invoice you can predict from a page count. The /interact endpoint handles clicking and form-filling in natural language, and it is open source with SDKs for Python, Node, Rust and Go.
Feeding a model? Start with Firecrawl
If the output goes into a RAG pipeline or an agent, Firecrawl's markdown is production-ready on the first call and the free tier gives you 1,000 pages to prove it. Try Firecrawl free.
Where Apify wins
Sites that fight back, and sites someone has already solved. The 30,000-Actor Store means Google Maps, Amazon, Instagram, LinkedIn and TikTok are filled-in forms rather than reverse-engineering projects. No generic scraping API matches that, because the work is site-specific by nature.
It also wins on control and ceiling. Managed residential and SERP proxies, CAPTCHA handling, browser fingerprinting and session rotation are all first-class, and Crawlee gives you a serious open-source crawling library that runs locally as happily as on Apify's cloud โ so your code is portable even though the hosting is not. At 256 concurrent runs and 512 GB of memory, the top of the platform is far above anything a per-page API exposes.
Scraping a defended site? Start with Apify
Check the Actor Store before writing anything โ if a maintained Actor already exists for your target, you are minutes from data instead of days. Browse Apify's free tier on $5 of monthly credits.
Using both is the common answer
Plenty of production stacks run both, and split them on difficulty rather than loyalty. Firecrawl handles the long tail โ blogs, docs, news, marketing pages, the thousands of ordinary URLs where clean markdown is the whole requirement. Apify handles the short list of hard targets where you need residential IPs and a purpose-built scraper.
The economics support the split. Ordinary pages are cheap and predictable on Firecrawl and rarely justify the engineering overhead of an Actor; defended sites are exactly where Firecrawl's uniform per-page model stops being an advantage and Apify's control starts earning its metered bill.
Developer experience: the code
The clearest way to see the difference is to look at what each one actually returns. Firecrawl hands you the document. Apify hands you a run, whose results you then fetch from a dataset.
Firecrawl โ one call, finished output:
Apify โ pick an Actor, run it, read the dataset:
Neither is harder than the other, but they ask different things of you. Firecrawl needs you to know a URL and an output format. Apify needs you to choose an Actor and learn its input schema โ different for every one of the 30,000 โ then handle runs and datasets as separate concepts. That overhead buys durability: a dataset survives a crashed run, and a request queue lets a large crawl resume instead of restarting.
Maintenance and compliance
Scrapers break because websites change, and the two platforms distribute that burden differently. With Firecrawl, breakage is largely the vendor's problem โ its extraction is generic, so a site redesign usually degrades output quality rather than stopping the pipeline. With Apify, breakage is the Actor author's problem, which is excellent when the Actor is actively maintained and a real risk when it is not. Check an Actor's last update date before you depend on it.
Both leave the legal questions to you. Scraping law varies by jurisdiction and by what you collect: public factual data sits on very different ground from personal data, which brings GDPR and similar regimes into play regardless of how you obtained it. Respect robots.txt and site terms, rate-limit politely, and take advice before scraping personal information at scale. Neither platform's terms transfer that responsibility away from you.
Which should you pick?
- Building RAG, agents, or any LLM pipeline โ Firecrawl. Markdown and JSON out of the box, predictable per-page cost.
- Scraping Google Maps, Amazon, social platforms or marketplaces โ Apify. Someone has already built and maintained that Actor.
- Facing CAPTCHAs, residential-IP requirements or aggressive fingerprinting โ Apify, and budget for proxy bandwidth as the dominant cost.
- Quoting fixed-price client work โ Firecrawl. Predictability beats a lower average when you carry the overage risk.
- Running large volumes of simple pages โ Apify, where a lightweight HTTP Actor is dramatically cheaper per page than any per-page API.
- You want one tool and cannot decide โ Firecrawl if your output feeds a model, Apify if it feeds a database.
Verdict
Firecrawl is the better product for the job it chose: turning arbitrary web pages into model-ready text and structured data, with a bill you can forecast. Apify is the more capable platform, full stop โ a deeper toolbox, a vastly larger scraper catalogue and a much higher ceiling, at the price of billing you have to actively manage.
If you want a single decision rule: pay Firecrawl for predictability and finished output; pay Apify for reach and control. The comparison only looks close because both charge $19 at the entry tier โ and as the cost modelling above shows, those two nineteen-dollar plans are not buying remotely the same thing.
Try Firecrawl free โ Try Apify free โ
Firecrawl: 1,000 free pages ยท Apify: $5 free credits monthly ยท Both from $19/month
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Written by
AI Magic Editorial Team
We write about AI image generation, creative workflows, and how creators use AI Magic to ship faster โ built on the latest from Google Gemini.