Web Scraping API Cost Comparison 2026: Firecrawl vs ScrapingBee vs KnowledgeSDK
Cost is always a top-three concern when choosing a scraping API. But comparing prices is surprisingly hard. Different services use different billing models — per-credit, per-page, per-browser-minute, per-GB transferred — and they don't map cleanly onto each other. A "$49/month" plan at one service might yield 5x more usable pages than the same spend at another.
This guide normalizes everything to cost-per-1,000-pages so you can make an actual apples-to-apples comparison. We also break down the hidden costs that rarely appear in the pricing table.
Understanding Billing Models
Before comparing numbers, you need to understand what you're actually buying:
Per-request billing (KnowledgeSDK, Firecrawl) is the simplest model. One URL = one request = one unit of credit. Predictable, easy to budget.
Per-credit billing (ScrapingBee, Scrape.do) adds complexity. A JavaScript-rendered request might cost 5 credits while a simple HTTP request costs 1. You need to know your content mix before estimating spend.
Per-browser-hour billing (Browserbase) is designed for interactive automation, not bulk extraction. Cost scales with session duration, not page count — which makes it expensive for scraping at volume.
Per-GB billing appears in some bandwidth-heavy services and is largely unpredictable. Avoid it if your content size varies significantly.
Full Pricing Breakdown
Firecrawl
| Plan | Price | Pages/mo (est.) | Cost per 1k pages |
|---|---|---|---|
| Free | $0 | 500 | — |
| Starter | $16/mo | ~3,000 | $5.33 |
| Standard | $83/mo | ~20,000 | $4.15 |
| Scale | $333/mo | ~100,000 | $3.33 |
| Growth | $599/mo | ~250,000 | $2.40 |
Firecrawl's strength is output quality — its markdown extraction is among the best available, making it a popular choice for LLM and RAG use cases. The trade-off is price. At $16/month for the starter tier, it's not the cheapest option for moderate volume.
ScrapingBee
| Plan | Price | Credits/mo | JS pages/mo (est.) | Cost per 1k pages |
|---|---|---|---|---|
| Free | $0 | 1,000 | ~200 | — |
| Starter | $49/mo | 250,000 | ~50,000 | $0.98 |
| Business | $99/mo | 1,000,000 | ~200,000 | $0.50 |
| Business+ | $249/mo | 3,000,000 | ~600,000 | $0.42 |
| Enterprise | $599/mo | 8,000,000 | ~1,600,000 | $0.37 |
ScrapingBee's credit model applies a 5x multiplier for JavaScript rendering (the default for modern web pages). The effective page count drops accordingly. Still, at $0.50-0.98/1k pages, it's significantly cheaper than Firecrawl for pure extraction volume.
Scrape.do
| Plan | Price | Pages/mo | Cost per 1k pages |
|---|---|---|---|
| Free | $0 | 1,000 | — |
| Basic | $29/mo | 250,000 | $0.12 |
| Professional | $99/mo | 1,250,000 | $0.08 |
| Business | $249/mo | 3,500,000 | $0.07 |
Scrape.do markets a 99.98% success rate and a network of 110M+ residential proxies. Its pricing is among the lowest in the market, which makes it attractive for high-volume commodity scraping. It doesn't offer native markdown output or semantic search.
Browserbase
| Plan | Price | Notes |
|---|---|---|
| Free | $0 | 10 hours/mo |
| Developer | ~$20/mo | 40 hours/mo |
| Startup | $99/mo | ~200 hours/mo |
| Enterprise | Custom | SLA, dedicated infra |
Browserbase is priced per browser-hour, not per page. A page that takes 5 seconds to load costs you ~$0.0014 in browser time — which sounds cheap, but 1,000 pages at 5 seconds each is 1.4 hours = ~$0.70 at Startup tier rates. This model makes sense for interactive automation; it's inefficient for bulk read-only extraction.
KnowledgeSDK
| Plan | Price | Requests/mo | Cost per 1k requests |
|---|---|---|---|
| Free | $0 | 1,000 | — |
| Starter | $29/mo | Generous allocation | ~$0.58 |
| Pro | $99/mo | High volume | ~$0.20 |
KnowledgeSDK's pricing is competitive with the mid-tier market, with the advantage of bundling capabilities that would otherwise require multiple services: markdown extraction, semantic search via POST /v1/search, webhooks for change detection, and an MCP server for agent integration.
Normalized Cost Comparison (Per 1,000 Pages)
| Service | Low Volume (~1k/mo) | Medium (~50k/mo) | High (~500k/mo) |
|---|---|---|---|
| Firecrawl | $5.33 | $4.15 | $2.40 |
| ScrapingBee | $0.98 | $0.50 | $0.37 |
| Scrape.do | $0.12 | $0.08 | $0.07 |
| Browserbase | ~$0.70 | ~$0.70 | ~$0.70 |
| KnowledgeSDK | ~$0.58 | ~$0.20 | custom |
At low-to-medium volume, KnowledgeSDK sits in the middle of the market. At high volume, Scrape.do wins on raw page cost, but without the structured output, search, or monitoring capabilities that AI-native use cases require.
Hidden Costs
JavaScript rendering multipliers. Some services (ScrapingBee) charge 5x for JS rendering. If 80% of your targets are JS-heavy — which is likely in 2026 — your effective cost is much higher than the headline number suggests.
Overage fees. Check what happens when you exceed your monthly allocation. Some services charge per-request overages at 2-3x the plan rate. Others pause your account. Plan accordingly.
Anti-bot failures. A 95% success rate sounds good until you realize 50 out of 1,000 requests are returning blocked pages. You're paying for those failed requests and then paying again to retry them. Higher-quality services with better anti-bot bypass have lower effective cost even at a higher per-request price.
Post-processing labor. If a service returns raw HTML and you need markdown, you're writing and maintaining a parser. Engineering time is not free. Services that return clean markdown natively (Firecrawl, KnowledgeSDK) reduce this hidden cost.
Search and indexing. If you need to make extracted content searchable, you're either paying for a vector database (Pinecone, Weaviate) or building your own. KnowledgeSDK bundles hybrid search — a capability that typically costs $70-200/month separately at relevant scale.
When Cheap Isn't Actually Cheap
Scrape.do at $0.08/1k pages looks dramatically cheaper than Firecrawl at $4.15/1k pages. But if you're building an AI application:
- Scrape.do returns raw content, not markdown. You write the parser.
- You need to set up and pay for a vector database separately.
- You need to manage change detection polling yourself.
- You have no native agent/MCP integration.
The total cost of ownership for an AI-native stack built on cheap commodity scrapers can easily exceed what a purpose-built solution costs — once you account for engineering time and third-party service fees.
Choose the cheapest option when you need raw HTML at volume and have the engineering resources to build the pipeline on top. Choose a higher-level API when you want to focus on your application logic, not scraping infrastructure.
The Bottom Line
For AI developers in 2026, the right question isn't "what's the cheapest scraping API?" It's "what's the cheapest path to production-quality, LLM-ready content at my scale?"
That calculation often points to a service that costs more per page but ships with the extraction quality, search capabilities, and monitoring infrastructure that AI applications actually need.
KnowledgeSDK offers 1,000 free requests to get started — enough to validate your pipeline before committing to a paid plan.