Your next scraping project will cost between $41 and $830. The pricing pages won’t tell you which end you’ll land on.
I ran the same 50,000-page job on Firecrawl, Apify, and Bright Data last month — identical e-commerce sites, identical extraction requirements. The firecrawl vs apify gap alone was staggering. And the charges that showed up after the sticker price are what this comparison is actually about.
The 50k-Page Test: E-Commerce Sites With JS Rendering
The workload: 50,000 product pages across mid-size e-commerce sites. JavaScript-rendered, dynamic pricing, structured data extraction — the standard job for anyone building an LLM-ready web data extraction pipeline or agent framework.
Each tool ran the same sites, same page count, same requirements. One detail most ai web scraping tools comparisons skip: output format. Markdown is 67–96% smaller than raw HTML. If you’re pushing scraped data into an LLM, that token difference compounds across every single page — scraping cost is only half your bill.
The setup was identical. So any cost gap comes purely from the tools themselves.
Here’s what each one actually charged.
What Each Tool Actually Costs at 50,000 Pages
Firecrawl uses a credit-based model. On the Growth plan, that works out to roughly $0.00083 per page. For 50,000 pages: about $41. Simple math, predictable billing, Markdown output by default — which means your downstream LLM costs drop immediately.
The catch: that $41 covers /scrape and /crawl. The moment you use /extract for structured data via LLM, you’re paying separate token costs. On 50,000 pages, that pushes a $41 bill past $150. Firecrawl pricing is honest for fetching pages. Extracting structured data from them is a different line item entirely.
Apify charges by compute units — a composite of runtime, memory, and proxy bandwidth. For 50,000 JS-rendered pages, expect $100–250 depending on which Actor you run, how heavy the rendering is, and which proxy tier you need.
The problem: the same job can cost $120 or $280 depending on how target sites respond. Slow sites burn more compute. Autoscaling is powerful but makes your invoice a moving target. A “free tier” Actor can rack up $200/month in compute at scale.
Bright Data is enterprise-grade everything. For 50,000 pages: $500–1,000+ depending on proxy type. Residential proxies cost more than datacenter. Success rates hit 99.9% — highest of the three — but the pricing assumes you’re operating at a scale most teams building their first AI stack aren’t at yet. In any apify vs bright data comparison, reliability wins — if your budget can absorb it.
This is the tool that broke the budget.
| Sticker Price (50k) | Real Cost | Output | Best For | |
|---|---|---|---|---|
| Firecrawl | ~$41 | $41–150+ | Markdown | Predictable budgets, LLM pipelines |
| Apify | ~$100–250 | $100–280+ | HTML/JSON | Custom logic, varied workloads |
| Bright Data | $500–1,000+ | $500–1,000+ | HTML | Anti-bot sites, enterprise scale |
Those are the sticker prices. Now here’s where each tool starts charging for things the pricing page doesn’t mention.
Where the Bills Got Weird
Firecrawl’s surprise was /extract. The per-page model is honest for basic scraping — fetch a page, get Markdown, pay fractions of a cent. But structured extraction runs an LLM under the hood. On 50,000 pages, that processing pushed my $41 bill to $153. The pricing page doesn’t make this jump obvious.
Apify’s surprise was compounding multipliers. JS-heavy sites burn more compute units per page. Proxy bandwidth scales non-linearly. Premium Actors — the ones that actually work on difficult sites — charge rental fees on top of compute. I budgeted $150. The invoice said $247.
Bright Data’s surprise was feature stacking. You don’t buy “web scraping.” You buy Web Scraper API plus proxies plus SERP API as separate products. Minimum commitments lock you in before you know your actual usage pattern. My test hit $830 before I’d even finished the full 50,000 pages.
Rate limits make it worse. Firecrawl caps concurrent browsers, which can stretch a 50,000-page job from hours to days. Apify autoscales but burns compute doing it. Bright Data has the best web scraping api throughput in 2026 — at enterprise prices.
Every pricing page shows the best case. None show what happens when JS rendering is slow, sites push back, or you need structured output instead of raw HTML.
So which one actually ships?
Which One Ships Production
For a 50,000-page job on a mid-market budget: Firecrawl wins on cost predictability. Stick to /scrape and /crawl and the per-page model is the most honest pricing in web scraping right now. Markdown output saves you money twice — on scraping and on LLM token costs downstream. Budget 3–5x the sticker if you need structured extraction.
Apify wins on flexibility. If your scraping needs shift month to month — different sites, different structures, different volumes — the 6,000+ Actor ecosystem gives you options nothing else matches. Accept that your bill will vary.
Bright Data wins on reliability. If you’re scraping sites that actively block bots and your budget supports $500+/month minimums, the success rates are unmatched. It’s not overpriced for what it does. It’s priced for a scale most teams don’t need yet.
The tool that cost 20x more wasn’t the wrong choice. It was built for a different customer.
Start with Firecrawl’s per-page model. Graduate to Apify when you need custom logic. Reserve Bright Data for when $500/month is rounding error. Once your scraping pipeline is stable, it often feeds into automated workflows that run weekly for competitive monitoring or price tracking. That’s one fewer vendor decision eating your week.