Firecrawl vs Bright Data vs Apify: Which Web Scraping API for LLM Data?

Firecrawl vs Bright Data vs Apify: the short answer

Pick Firecrawl if you want clean markdown from a site quickly and might self-host later. Pick Bright Data if your targets are heavily defended or you need enterprise proxy scale and prebuilt datasets. Pick Apify if a scraper for your exact target site already exists in its marketplace and you would rather configure than build. All three are good tools. They are also built for different jobs, and most of the frustration teams report comes from buying one for a job it was never designed to do.

They are not really competitors

These three products get compared constantly because they all "scrape websites", which is a bit like comparing a chainsaw, a scalpel and a Swiss Army knife because they all cut. Their architectures tell you what they are for.

Firecrawl is an LLM-first crawler. Its whole reason for existing is to turn a page into clean markdown that a model can read without wasting tokens on navigation and cookie banners. It has a strong open-source project, a free tier of 1,000 credits, and paid plans from $16 a month.

Bright Data is a web data platform built on the largest proxy network in the category, with over 150 million residential IPs across 195 countries and hundreds of prebuilt domain scrapers and ready-made datasets. It is priced by usage, with the Web Scraper API billing roughly $0.75 to $3 per 1,000 records depending on product and tier.

Apify is an automation cloud with a marketplace of thousands of prebuilt scrapers, called Actors, that other people wrote and maintain. Plans start at $29 a month, with per-Actor compute or per-result fees on top.

The comparison table

Prices are published US list prices checked in July 2026. Trademarks belong to their owners.

Which is best for LLM and RAG data?

Firecrawl, of the three, and it is not close. RAG lives or dies on chunk quality, and chunk quality starts with clean text. If your embeddings contain navigation menus, cookie notices and footer links, retrieval degrades: the model matches on boilerplate that appears on every page instead of the content that distinguishes them. Firecrawl outputs markdown designed to avoid exactly that, and claims its markdown uses roughly 67% fewer tokens than raw HTML, which shows up directly in your embedding and inference bill.

Bright Data and Apify can both get you the data. Neither is shaped for what happens next. With Bright Data you get raw data or a dataset and you write the transformation. With Apify you get whatever the Actor's author decided to emit, which varies Actor by Actor. Either way you are building and maintaining a cleaning stage between the scraper and the model, and that stage is where most RAG pipelines quietly rot.

The same clean-text problem shows up anywhere a model reads your content, which is why teams building a support chatbot trained on their own documentation hit it before they hit any scaling limit. Garbage chunks in, confidently wrong answers out.

Which is best for hard, defended sites?

Bright Data. This is what the proxy network is for. If your targets are marketplaces, travel sites, ticketing platforms or anything behind Cloudflare, DataDome or PerimeterX, the depth of the IP pool is the thing that determines whether you get the page at all, and nothing in this comparison matches 150 million residential IPs across 195 countries.

Firecrawl offers a stealth mode, but it bills 5 credits per page instead of 1, so a Standard-plan page goes from about $0.00083 to roughly $0.0042. That is fine for a subset of your crawl and painful if it is most of it. Apify's answer depends entirely on which Actor you run and how well its author handled blocking.

Which is best if a scraper already exists for my target?

Apify, comfortably. If you need LinkedIn profiles, Amazon listings, Google Maps results or Instagram posts, someone has already written and battle-tested an Actor for it, and you can be pulling data this afternoon instead of writing a parser this week. That is a real, unglamorous advantage and it is why Apify keeps winning deals.

The bill is the tradeoff. You pay the platform plan plus the Actor's own compute, result or gigabyte pricing, and the total is harder to forecast than a flat plan. You are also depending on someone else to keep that Actor working when the target site changes.

What none of them do

All three make you assemble the pipeline. Firecrawl gives you separate crawl, scrape and extract endpoints. Bright Data gives you a suite of products to combine. Apify gives you Actors to chain. In each case, getting from "a URL" to "typed fields my application can use" is several steps that you orchestrate, plus the retry and error handling around them.

That is the gap ClawEngine was built for. One call crawls the site, renders the JavaScript and extracts typed fields against a schema you define, then returns clean markdown or typed JSON that is ready to chunk and embed. There is no separate extract step, no parsing layer, and no Actor to maintain. Compliance is a default rather than a setting: ClawEngine works on public and permitted data only and respects robots.txt, site Terms of Service and crawl-delay, which matters the first time a customer, an investor or a regulator asks where your training data came from. Plans are $39, $99 and $399 a month, usage-based, with no free tier.

To be straight about the tradeoff: Firecrawl is cheaper to start and has an open-source path we do not offer. Bright Data will get pages we will not touch. Apify has a marketplace we cannot match. If those are what you need, buy those.

How to choose in one paragraph

Write down your target list and what the data feeds. If the targets are public documentation, catalogs, knowledge bases or marketing content, and the data feeds an LLM, choose on output quality, and Firecrawl or ClawEngine are your shortlist. If the targets are defended commercial platforms, choose on proxy strength, and Bright Data is the answer. If a prebuilt Actor already covers your exact site, choose speed and take Apify. The mistake to avoid is buying anti-bot capacity for undefended pages, or buying a proxy platform when what you actually needed was clean text.

For the full field, including ScraperAPI, ScrapingBee, ZenRows and Crawl4AI, read the best web scraping API buyer's guide. For head-to-head detail, see Firecrawl alternatives, Bright Data alternatives and Apify alternatives. If cost is the deciding factor, the web scraping API pricing breakdown shows where the hidden money goes. And if RAG quality is the real goal, start with web scraping for RAG.