Best Web Scraping APIs: 7 Services Benchmarked on Speed & Cost (2026)

Last year a developer went hunting for the best web scraping API and moved his price-monitoring job off his own scraper onto a “cheap” one. The headline rate looked great: a dollar per thousand. Then the first invoice landed at $4,800 for a month of work his old setup did for the cost of a few proxies.

Nobody had told him the API billed per record, not per request. Each search returned 50 products, so every search he made counted as 50 charges.

That gap, between what an API says it costs and what it actually costs, is the whole game. Speed matters. Success rate matters. But the billing model is what decides whether the scraping API you picked is a bargain or a slow-motion budget leak.

FlyByAPIs is a structured data API that bills per request, so one call returning 50 results is one charge. Against per-record and per-result vendors, that single difference makes it 16 to 33 times cheaper on any workload that returns lists.

We run scraping infrastructure for a living. Over 5 million API requests a month flow through our systems, for more than a thousand active developers and teams. So this isn’t a tour of marketing pages. It’s the stuff that shows up on the invoice and in the data you actually get back.

By the end you’ll know which of these seven services fits your workload, why two of them can quietly cost 30 times more than the others, and the one factor that breaks data quality before pricing ever enters the picture.

How I benchmarked these web scraping APIs

Five things decide whether a scraping API is good, and they don’t all pull in the same direction.

No single tool wins all five. The right pick depends on whether you need raw pages from anywhere or clean data from specific sources.

The 7 best web scraping APIs at a glance

Here’s the full benchmark. FlyByAPIs leads because it wins the two axes this comparison is built on, speed and real cost, while returning data you don’t have to parse. The anti-bot success rates for the unblockers come from publicly published 2026 benchmark studies run by scraping vendors and review sites (Scrape.do, Proxyway, and similar), so they shift over time. Verify current numbers before you commit.

*The 99%+ figure is for the FlyByAPIs vertical APIs on their own sources, so it isn't directly comparable to general-purpose unblockers tested against arbitrary protected sites. The FlyByAPIs AI Web Scraper does take any URL, and when a target does block it, the request costs zero credits and the response tells you the real HTTP status and which protection fired. We still cede the raw anti-bot crown to Bright Data and compete on cost, speed, honesty, and data accuracy.

Two kinds of scraping API, and most people pick the wrong one

Before the rankings, one distinction that saves you months of grief. The term web scraping covers two products that solve very different problems.

Here’s the part people miss. Most folks searching for a scraping API don’t actually want HTML. They want the data inside it. If you’re scraping Amazon, Google, Maps, or company profiles, a structured API hands you the answer and skips the part where you babysit CSS selectors. If you’re scraping known URLs on any other site, a general-purpose web scraping API can hand you the page as HTML, LLM-ready Markdown, or structured JSON.

Crawling is a third job. If you need to discover pages across a whole site or thousands of random domains, follow links, map structures, that’s what crawl-first tools like Firecrawl are built for. Know which job you have before you pick.

1. FlyByAPIs: structured data at per-request prices

I’ll be straight: I’m biased, this is what we build. But the reason it tops a benchmark about speed and cost is simple math, not loyalty.

FlyByAPIs is a growing suite of structured data APIs. Instead of raw HTML, you get clean JSON for the data you came for. Need Amazon product data through a single API call ? One request, structured response, prices and reviews and stock included. Same story for Google search results via API and local business data from Google Maps .

Since this post first ran, the “specific sources only” caveat has retired. The AI Web Scraper API takes any URL and returns the page as raw HTML, LLM-ready Markdown with the boilerplate stripped, or structured JSON. It carries the same honest meter as the rest of the suite: it tries the cheap HTTP path first and escalates to a real browser only when the site fights back, and it bills only the attempt that won. A blocked request costs zero credits, and the response always tells you the real HTTP status, the block reason, and which protection system fired instead of masking the failure as a success.

Two features stand out against the category. The AI extraction returns null when a field isn’t on the page rather than guessing something plausible. And the rule generator writes reusable CSS/XPath selectors from a one-time description of the fields you want, so every future page of that layout runs at plain fetch price with no model involved, where Firecrawl and ScrapeGraphAI run an LLM on every single page. There’s also a one-call article summarizer API built on the same engine when you want the page as prose instead of markup. Plans start free at 100 requests a month, then $14.99 for 100K.

The cost advantage comes from one rule: one call is one charge, no matter how many results come back. One request to scrape Amazon product listings returns 50 products for a single charge. The vendors that bill per record or per result charge you 50 times for the same call. On list-heavy work that’s a 16 to 33 times difference, and it’s the entire reason this lands at number one.

There’s also the accuracy piece. Every request is country-pinned, so the response matches what a real local user sees on the page. That solves the “wrong price” and “missing buy box” problem that wrecks cross-border scraping. I’ll come back to why that breaks more pipelines than blocking ever does.

Beyond e-commerce and search, the same per-request model covers company and funding data from Crunchbase and job listings pulled from Google Jobs , with more sources shipping over time. There’s even a format-aware translation API for localizing the data once you have it.

Verdict: the best web scraping API for teams who want the data from specific sources or from any known URL, with a bill that never scales with results and never charges for a block.

2. Bright Data: the enterprise heavyweight

Bright Data is the name that comes up when the target is brutal. Public 2026 benchmarks put its success rate at 98.87%, the highest of any provider tested, on a proxy pool north of 150 million IPs. If you need to get through Cloudflare, DataDome, and Akamai at industrial scale, it delivers.

The catch is billing. Bright Data charges per record, around $1 per thousand at list price (less with volume commitments). One search returning 50 results is 50 records. Run 100,000 searches a month and you’re looking at thousands of dollars where a per-request vendor charges low hundreds.

Verdict: the right call for enterprises that need maximum unblocking on the hardest targets and can absorb per-record pricing.

3. Oxylabs: high throughput, per-result billing

Oxylabs sits in the same enterprise tier as Bright Data, with strong success rates and throughput up to 50 requests per second on entry plans. If raw speed at volume is your constraint, it’s genuinely good.

But it bills per result, the same trap as Bright Data wearing a different label. At $0.50 per thousand results on the Micro plan, one 50-result search costs $0.025 against $0.0015 on a per-request plan. The entry price is also $49 a month, three times higher than a per-request alternative.

Verdict: strong for high-throughput enterprise scraping, expensive once your calls return lists.

4. ScrapingBee: the developer-friendly all-rounder

ScrapingBee is the one developers reach for first, and for good reason. The docs are clean, JavaScript rendering works without fuss, and it has dedicated endpoints for Google, Amazon, and YouTube. Public benchmarks put success on complex targets around 84%, lower than the enterprise tier but fine for most sites.

It’s an HTML unblocker at heart, so you parse the output yourself. If you want a deeper look, we wrote up the best ScrapingBee alternatives including where it wins and where it doesn’t.

Verdict: a solid generalist for developers who want clean docs and don’t mind parsing HTML.

5. Scrape.do: budget unblocking, pay for what works

Scrape.do is the value pick among the unblockers. Public benchmarks report a 98.61% success rate, and it only charges for successful requests, which is a genuinely fair model. Plans start at $29 a month.

Verdict: great budget unblocker for batch scraping where a few extra seconds per request doesn’t hurt.

6. Zyte: built for the hardest anti-bot walls

Zyte (the team behind Scrapy) specializes in tough targets, with a success rate around 93% and a smart layer that escalates only when a site fights back, so you don’t overpay on easy pages. Pricing is usage-based.

It’s a capable, engineering-led product. The flip side is that usage-based pricing on a per-page model still leaves you holding the parsing work, and costs climb on list-heavy jobs the same way the per-record vendors do.

Verdict: a strong choice when anti-bot difficulty, not data volume, is your main problem.

7. Firecrawl: best for crawling whole sites into LLM pipelines

Firecrawl earns its spot by serving a specific job better than anyone: crawling. Point it at a domain and it discovers the pages for you, then turns the whole site into clean Markdown or LLM-ready JSON, which is exactly what RAG pipelines ingesting entire docs sites want. Plans start at $16 a month.

Success on heavily protected sites sits around 60%, the lowest here, but it excels on the content-heavy pages AI apps usually care about. Two things to weigh, though. If you already know which URLs you want, you don’t need a crawler: an AI scraper with a Markdown output does the single-page conversion at per-request prices. And Firecrawl’s AI extraction runs a model on every page, so extraction cost scales with page count, where a generate-rules-once approach pays the model cost a single time per layout. If your model needs specific structured fields rather than page text, a JSON-first data API feeds it cleaner inputs.

Verdict: the pick for crawling whole sites into RAG pipelines, not for fighting hard anti-bot systems or scraping URLs you already have.

The part nobody benchmarks: how billing actually works

Every roundup compares speed and success rate. Almost none compare how you get charged, which is bizarre, because it’s the number that hits your bank account.

There are five billing models in this market, and they are not equivalent.

Let’s make it concrete with a job for any Amazon scraping API : a search that returns 50 products.

Same data. Same 100,000 searches. The bill ranges from about $150 to about $5,000 depending purely on the billing unit. That’s the developer from the intro, whose Amazon price-monitoring job blew up on per-record billing, and it’s why I won’t quote a headline rate without telling you what it’s a rate of.

One honest caveat: per-request isn’t always cheapest everywhere. At very high single-item volumes some competitors get close, and a per-credit vendor like Easyparser is genuinely competitive in the 50,000 to 100,000 monthly range. On anything that returns lists, though, per-request wins by a wide margin. You can see the same pattern play out across providers in our SERP API pricing breakdown .

Why your location quietly breaks the data

Here’s the failure mode that costs people more than blocking ever does, and almost no benchmark tests for it.

Amazon and Google serve different content based on where the request comes from. Point an Amazon product data API at Amazon.de from a US data center and you often get the foreign-visitor version of the page: a different buy box winner, a different price, missing Prime offers, sometimes no buy box at all.

This is the root cause behind most “inconsistent data” and “wrong price” complaints you’ll find in scraping API reviews on G2 . It’s not flaky code. It’s cross-border requests returning a local-to-the-server view.

The fix is country-pinning: routing each request so the response matches what a real buyer in that country sees. We pin every request by country, which is why scraping Amazon product data across marketplaces returns the local truth, and why Google search results pulled through the API reflect real per-country rankings. We also monitor every endpoint for source-site changes and ship fixes within hours, so drift doesn’t silently poison your pipeline.

An unblocker can support geo-targeting too, but you have to configure it correctly per request and verify it yourself. With a structured API that pins by default, accuracy is the baseline, not a setting you hope you got right.

How to choose the best web scraping API for your project

Skip the “it depends” non-answer. Here’s the decision in four boxes.

If you’re still weighing tools beyond APIs, our roundup of the best screen scraping tools and the Python scraping tools we tested cover the build-it-yourself end of the spectrum.

The bottom line

Remember the developer with the $4,800 invoice? His scraper worked fine. His tool worked fine. The billing model ate him alive, and no comparison table had warned him.

So that’s the lesson I’d leave you with. The right scraping API for your project isn’t the one with the flashiest success rate. It’s the one whose speed, output format, and billing unit match the work you’re actually doing. Benchmark cost the way it hits your invoice, not the way it reads on a pricing page.

For structured data from the sources most people scrape, returned as clean JSON, priced per request, and pinned to the right country, that’s what we built. You can pull Amazon listings , Google results , Maps business data , Crunchbase profiles , or job postings , and for everything else there’s an API that can scrape any website , turning any URL into HTML, Markdown, or JSON and charging nothing when a site blocks it. All of it starts with 100 free requests a month and no credit card.

P.S. If you’re staring at an invoice right now wondering where the money went, check the billing unit before you blame your code. Nine times out of ten, that’s the culprit.

Oriol.