# Firecrawl credit usage: any tips for large crawls with lots of lightweight pages?

I have had a good experience with Firecrawl for reliably bypassing anti-bot checks and returning clean, well-formatted Markdown. It also helps cut through bloated HTML noise so I can focus on AI pipelines and LLM ingestion instead of maintaining brittle scraper infrastructure. My main challenge is that credit consumption can add up fast on large crawls, especially when many pages do not need full browser rendering or stealth bypass. How are others managing credit usage, and would a lower-credit fast HTTP tier solve this for you?

##### Post Metadata
- Posted at: 18 days ago
- Author title: Technical Lead & Systems Architect | Software Engineering, Infrastructure & Delivery| MEng Computer Engineering (Distinction) | Building scalable, testable, and intelligent systems
- Net upvotes: 2


## Comments
### Comment 1

I’m seeing the same unpredictability when I mix search, scrape, and agent mode, so I try to keep those runs separate when I’m doing competitive benchmarks. On big travel and review platforms with heavier anti-bot protection, I sometimes get partial pages or need a second attempt, which makes credit planning even harder. A clearer credit estimate before launching a larger run would help me budget for scheduled re-runs month to month.

##### Comment Metadata
- Posted at: 1 day ago
- Author title: ceo



### Comment 2

Hey Yusuf, really glad it's been working well for you!

For big crawls, what usually saves the most is running a map first to see every URL, then only scraping the pages you actually care about.

Setting a limit and include/exclude paths on the crawl also keeps it from wandering into tag pages and archives. Sticking to plain markdown helps too, since the extra formats cost more.

If you tell me a bit about what you're crawling, I'm happy to suggest settings!

##### Comment Metadata
- Posted at: 12 days ago



### Comment 3

I’ve had the same issue where the draw limit runs out fast, even though the crawler itself is easy to use and does exactly what I expect. Since I’m using it to crawl data and feed my app, I end up watching credits closely and it can be tight for smaller teams. I’d really like to see the credit system refined or a bit more included so it’s easier to run larger crawls without hitting the ceiling so quickly.

##### Comment Metadata
- Posted at: 15 days ago
- Author title: Founder at Tarkle



### Comment 4

One thing that helped us manage credit usage is leaning on the per-response credit reporting and idempotency keys. We pace and back off from day one because of the smaller-plan rate limits, and retries stay safe without double-spending. Also worth noting: if a request times out, the credits can look “held” for a bit before they’re released, so our running total sometimes reads higher than the final bill.

##### Comment Metadata
- Posted at: 15 days ago
- Author title: Founder



### Comment 5

Yes the below is AI-generated. But I also don't normally respond to these things. Just felt neat because I solved a specific issue half a year ago. thought id share, but also take with a grain of salt. I haven't maintained this plugin repository this came from in 4 months, turns out it was more expensive to maintain the complex system than it was to eat the cost on Firecrawl:

Yeah — we ended up treating Firecrawl as the premium layer, not the default path for every page. For large crawls, the credit burn gets ugly fast if you send everything through the same expensive extraction pipeline. The pattern we used was basically:

- discover URLs with sitemap / cheap fetch logic first
- only hit Firecrawl when we actually need reliable extraction or anti-bot handling
- use a lighter HTML-to-markdown pass for static or low-value pages
- reserve browser rendering for the pages that are truly messy, JS-heavy, or blocked
- dedupe and skip unchanged pages so we’re not paying to reprocess the same content over and over

That’s the part where MarkItDown was useful for us — a cheap way to normalize HTML into something cleaner without spending Firecrawl credits on every page. For simple docs or lightweight pages, that’s usually enough. Firecrawl is best saved for the cases where the site is flaky, protected, or you need the higher-quality extraction.

So yes, a lower-credit fast HTTP tier would absolutely help. But the bigger lever is routing strategy: keep the common case cheap, and only spend credits on the hard cases. That’s the easiest way to get scale without the crawl cost exploding.


The old repo. If you want to see, I pointed you at the point in code where this issue is addressed 
https://github.com/TheLobbi/claude/tree/main/plugins/scrapin-aint-easy/src/crawler

##### Comment Metadata
- Posted at: 17 days ago
- Author title: COO at The Lobbi | Custom Software Engineering for Regulated Industries | Operations & Delivery


#### Reply 1

https://macmdviewer.com/blog/html-to-markdown-guide also this but unless it is a long-running constant job, it may not be worth it to make an HTML-to-Markdown serializer. 


##### Reply Metadata
- Posted at: 17 days ago
- Author title: COO at The Lobbi | Custom Software Engineering for Regulated Industries | Operations & Delivery



## Related Product
[Firecrawl](https://www.g2.com/products/firecrawl/reviews)

## Related Category
[Data Extraction](https://www.g2.com/categories/data-extraction-tools)

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