Crawl4AI and Firecrawl are two of the biggest AI buzz products in the data collection industry. In this guide, we’ll walk through basic usage and statistics of both products.
By the time you’ve finished reading, you’ll be able to answer the following questions.
- What is Crawl4AI?
- What is Firecrawl?
- Where does each of them shine?
- Where do they come up short?
- Why is Bright Data a great alternative to both?
Understanding how these new tools compare helps highlight Bright Data’s comprehensive and scalable solutions. Whether you need general scraping capabilities or a full-scale data collection suite, Bright Data delivers proven technology.
Overview and Purpose
Before we dive into the specifics, let’s get a closer look at what each of these products are and who they’re marketed to. Since they’re built for different purposes, this isn’t an apples to apples comparison. It’s more of a “toolbox vs. swiss army knife” comparison.
Crawl4AI
Crawl4AI is an open source Python library that makes AI-powered web scraping easier and more accessible. It’s geared more toward developers focused on expanding their extraction pipelines. It’s entirely open source. The code is freely available on their GitHub Page. Crawl4AI aligns more with Bright Data’s traditional scraping tools.
Firecrawl
Firecrawl is one of the enterprise leaders in AI-powered web scraping. They offer a language agnostic framework and plenty of integration options. Firecrawl draws most of its interest from people who wouldn’t traditionally be in data collection or necessarily even development. With Firecrawl, scraping becomes accessible to people who don’t always have coding skill.
Unique Features
Crawl4AI
Crawl4AI stands out because it’s completely open source and uses permissive licensing. Take a look at the features that make Crawl4AI a very attractive option for developers. This tool offers configurable options and trust through transparency in the code.
- Open Source: Anybody can look at the code. Bugs are often spotted quickly fixed quickly by the community. The transparent codebase means that there are no surprises — if you know how to read code.
- LLM-Powered and LLM-Free Extraction: With Crawl4AI, you get your choice of using a small, local model for extraction or you can plug into an external model such as Deepseek.
- Permissive Licensing: The licensing behind Crawl4AI is very flexible and permissive. This draws interest from both hobbyists and enterprise developers.
- Python Library: Crawl4AI isn’t some subscription service. It’s a Python library. You can plug it into other things and if you wanted, you could build your own proprietary scraper using Crawl4AI as a backend.
Firecrawl
Firecrawl is one of the most popular enterprise tools around for web scraping. They offer a language agnostic framework — you can use Python, JavaScript or their GUI website to perform your extraction. They offer a variety of plans tailored to hobbyists and enterprise customers alike.
- Enterprise: Firecrawl is an enterprise product. They do offer an open source option. However, their main product line is geared toward people who want scalable data collection today.
- Language Agnostic: Firecrawl offers GUI support through their webapp. They also offer SDK support for both Python and JavaScript. There are community driven SDKs in Go and Rust as well. With Firecrawl, you’re not limited to Python. You’re not even limited to a programming environment.
- Natural Language Processing (NLP): Firecrawl is geared toward development and data collection via natural language. You tell the model what to do. Then, the model performs the collection task.
Ease of Use
Crawl4AI
Getting started with Crawl4AI is relatively simple. You can install it via pip and call it from your Python environment. The snippets below show how to install it and verify your installation.
Install Crawl4AI with the command below.
Run the setup to install browsers and tooling.
Use the doctor
command to verify your installation and identify any issues.
The code below is very simple. It comes straight from the Crawl4AI documentation here. Paste this into any Python file and run it with python name-of-file.py
. In practice, Crawl4AI runs better as a shell command. Running directly from VSCode or other IDEs tends to cause asyncio
issues.
Firecrawl
When starting with Firecrawl, simply navigate to their playground and enter your target URL. This interface is very friendly to non-developers.
If you click the “Run” button, you’ll see example output with your choice of either markdown or JSON.
Performance and Scalability
Crawl4AI
The snippet below comes from the example code you saw earlier. All in all, it took just under two seconds to scrape the example domain. Without an LLM, Crawl4AI is exceptionally fast. It rivals manual scraping with Requests and BeautifulSoup in terms of performance.
However, markdown scraping and raw HTML are about as clean as it gets. Crawl4AI does list support for JSON extraction without an LLM but the support is limited and buggy. To extract full data structures, you need to add a LLM support to your code. This is the hidden cost of Crawl4AI, you need to host or pay for an external LLM to complete real parsing jobs.
In the code below, we use an OpenAI model to parse the page from Books to Scrape. If you decide to run it yourself, make sure to replace the API key with your own.
Here’s our output. In total, it took just short of 25 seconds. You can also see each book listed along with its price in as a cleanly structured JSON object.
Firecrawl
Firecrawl simply lets you input a URL and it scrapes the page. When using the default version of Firecrawl, it outputs your page as raw markdown dumped into a JSON object.
Firecrawl has a cool feature when you run your code. As your scraper runs, you get to watch the browser as it renders the page.
Data Quality and Accuracy
Crawl4AI
When hooked into GPT-4o, Crawl4AI functioned with 100% accuracy. To check our item count, we added the following line to our code.
As you see in the output below, Crawl4AI and GPT-4o found all 20 items on the page.
When paired with an LLM, Crawl4AI becomes a surprisingly powerful tool with remarkable accuracy.
Firecrawl
Firecrawl actually offers two different products when it comes to scraping. You can use plain old Firecrawl for simple, dirty scraping options. Firecrawl Extract allows you to extract structured JSON objects.
Regular Firecrawl
This is the Books To Scrape output using regular Firecrawl. As you can see, it’s bad — really bad. Firecrawl converted the page to markdown. Then, it sliced up the raw markdown into seemingly random fields of JSON. This data needs to be further cleaned using code manually or passed into an LLM.
Regular Firecrawl will get the page, but it doesn’t do much more than that. You get a sliced up markdown page smashed into a large JSON object. You can fetch the page, but it requires plenty of work to transform your web page into usable data.
Firecrawl Extract
Extract is the next tier up. With Extract, you get full support for scraping via NLP. Tell the model what data to get, and it extracts it from the page. As you can see in the image below, we even get a recommended schema containing the title
, price
and availability
fields. If you’re satisfied with your schema, click the “Run” button.
Please note, your website comes appended with /*
— this tells Extract to automatically crawl the entire site. To save credits, remove the /*
.
If you want a single page crawl, just make sure to change Extract from the default setting. The image below shows our configuration to scrape a single page. The /*
operator is very easy to overlook, save yourself money and only use it when needed.
With Firecrawl Extract, our output comes clean and ready to use out of the box. As you can see, we get structured JSON objects with the following traits.
title
price
rating
availability
Security and Compliance
Crawl4AI
Crawl4AI does not come with compliance guarantees built into the software. They do offer some configurations that can assist you in your compliance with things like the robots.txt
file.
When using Crawl4AI, you are responsible for your own compliance with laws like GDPR and CCPA. Crawl4AI offers almost zero help with legal and security compliance. This means that when running a project at scale, you’ll likely need to hire additional help to ensure you’re following proper practices.
Firecrawl
According to their documentation, Firecrawl gives your information to Google for processing. They explicitly state in their terms that they follow GDPR and the CCPA but that you are required to honor these policies yourself. Any breach of these acts is your responsibility and that they are not responsible for misuse of their tools.
Firecrawl does offer more liability protection than Crawl4AI. However, this still isn’t much. Their products don’t come with guardrails. You are expected to follow the rules and if you don’t, you are liable for any misuse. For more information, take a look at the full Firecrawl Terms of Service.
Pricing and Licensing
Crawl4AI
Crawl4AI is free to use for anyone. We use the term “free” here quite loosely. As you’ve probably noticed while following along, any real extraction work requires LLM integration. You can either host the LLM yourself or plug into a service like the OpenAI API. When using Crawl4AI, you still need to pay for external services or infrastructure costs if self hosting. These costs add up. Crawl4AI will not cut your operating cost to zero.
Crawl4AI is distributed under the Apache License. You are allowed to modify, distribute and even sell Crawl4AI derivatives commercially. If you’ve got compliance help, Crawl4AI’s permissive licensing makes it a very attractive option for developers and data teams.
Firecrawl
Regular Firecrawl
Vanilla Firecrawl comes in a variety of pricing tiers. You can try their Free Plan. Their paid plans range from $16/month for 3,000 pages all the way to $333/month for 500,000 pages.
Firecrawl Extract
When using Extract, paid plans range from $89/month for 18,000,000 tokens per year up to $719/month for 192,000,000 API tokens per year.
Firecrawl Licensing
Firecrawl uses different licenses for a variety of its products. You can view all of its different licenses here. Please note that Firecrawl is an enterprise level product and that you will not be able to repackage their code as your own. Even their open source code is distributed under the AGPL-3.0 license. Just like other GNU software agreements, this is heavily restrictive when it comes to enterprise use.
Community and Support
Crawl4AI
As an open source project, Crawl4AI offers what limited support it can with the resources it has. There is no help desk or SLA. However, you are free to contact their developers via their Discord Channel. Wait times may vary. Don’t expect a dedicated team tracking issues and resolving your needs in a timely fashion.
Firecrawl
From their dashboard, Firecrawl gives you support options such as documentation, FAQ pages and status updates. You can contact their support team via the “Contact Support” button — although your priority varies based on your plan tier. You are always free to join their Discord Channel as well for community support.
Real World Use Cases
Crawl4AI
Crawl4AI has a variety of real world use cases for modern developers. You are only limited by what you can build.
- Backend Support: If you decided to create your own data products, you could integrate Crawl4AI with an LLM of your own and sell your products.
- AI Agents: As we did earlier in this article, you can plug external LLMs directly into Crawl4AI for powerful extraction operations with custom data structure output — CSV, JSON XML — any format your LLM has seen is a viable format.
- Hobby Projects and Startups: Open source tools like Crawl4AI offer quick accessibility for experiements, proof of concepts and pipeline prototypes.
Firecrawl
Firecrawl is built for teams who need high volume scraping with very little in house development. If you want to go from idea to tangible product without much work, Firecrawl can assist with that.
- Production Level Crawling: Firecrawl is built for crawling at scale. Their tools even crawl full websites by default.
- Content Monitoring: Run routine crawls on competitors to monitor their pricing and content.
- Clean and Ready Data: With Extract, you can pass your data straight to the data team with little to no cleanup required.
Pros and Cons
Crawl4AI | Firecrawl | |
---|---|---|
Pros | – Fully open source and transparent. – Permissive Apache license — build, modify, resell. – Flexible: LLM-powered or LLM-free options. – Plug-and-play Python library for custom pipelines. |
– Dead simple for non-developers: GUI, playground, NLP prompt. – Works in multiple languages (Python, JS, Go, Rust). – Fast to deploy for one-off or routine scraping. – Enterprise pricing and support tiers available. |
Cons | – Requires separate LLM for real structured extraction — adds hidden costs. – Limited built-in compliance support — user must manage GDPR/CCPA. – Async quirks — shell runs best, IDEs can break it. |
– Base output often messy without Extract — raw markdown requires more work. – No real guardrails for compliance — user still liable. – Closed source core, AGPL restrictions limit custom builds. – Usage costs can grow fast with scale or wildcard crawling. |
Why You Should Consider Bright Data
Crawl4AI and Firecrawl both have tradeoffs. Crawl4AI comes with developer needs and hidden LLM costs. With Firecrawl, you’re locked into usage tiers and the Firecrawl ecosystem.
Bright Data offers a variety of products that can help fill the same niches of both these aforementioned tools.
Top Bright Data Tools
- Scraper APIs: run pre-built scrapers with clean, ready to use data — whenever you want.
- Web Unlocker API: Bypass site blocks and solve CAPTCHAs, scrape as markdown and even control your geolocation.
- Browser API: Control a remote browser with integrated proxies and CAPTCHA solving from your programming environment.
- Datasets: Access a vast library of historical datasets from over 100 domains dating back years.
Our MCP Server gets you access to all the best Bright Data products in an LLM friendly package. Plug it into your LLM, write your prompts and let your system do its job.
Bright Data Integration Options
We even offer integration with some of the best tools in the AI and development industries today. We’re adding new integrations all the time. Check our docs for the most up to date list.
Conclusion
At Bright Data, we don’t just solve one scraping problem — we offer a whole ecosystem for your AI stack. From harvesting live data to tapping historical archives for training, we make sure you spend your time on insight, not infrastructure.
Start your free trial today and see the difference.