How Much Does LlamaParse Cost Per Page? (2026 Pricing)

Last updated July 2026.

LlamaParse costs between $1.25 and $75 per 1,000 pages depending on the tier you pick. It bills in credits, where 1,000 credits equals $1.25 (so $0.00125 per credit), and each parse tier consumes a different number of credits per page: Fast is 1 credit ($1.25 per 1,000 pages), Agentic is 10 credits ($12.50), and Agentic Plus is 45 credits ($56.25). Structured extraction stacks an extract tier on top of a parse tier, which pushes the ceiling to 60 credits per page, or $75 per 1,000 pages. LlamaParse also gives you 10,000 free credits every month, standing, which is unusually generous for this category.

How much does LlamaParse cost per page?

Here is every published tier converted from credits to dollars per 1,000 pages, so you never have to do the arithmetic in your head. Multiply the credits-per-page figure by $0.00125 to get the per-page price, or by $1.25 to get the per-1,000-pages price.

Notice the spread. The same product runs from $1.25 to $75 per 1,000 pages, a 45x range, and the pricing page quotes credits rather than dollars, so that gap is easy to miss until you multiply it out. The Fast tier is the cheapest, but it returns spatial text only: no markdown, no reasoning. If you want the agentic parsing LlamaParse is known for, you are at 10 credits per page or higher, which is about 10x the Fast price.

How do LlamaParse credits work?

Every action consumes credits, and 1,000 credits cost $1.25, so each credit is $0.00125. A page's price is just its credit cost times that rate. Parsing charges a per-page credit rate that depends on the tier. The layout add-on charges an extra 3 credits per page. And structured extraction is the one that surprises people, because it stacks.

Structured extraction is not a single line item. It is an extract tier plus a parse tier, added together. The extract tier is 5 credits per page on Cost-effective or 15 credits per page on Agentic. That extract cost sits on top of whatever parse tier you chose. So the cheapest possible structured extraction is the Cost-effective extract (5) plus the Fast parse (1), which is 6 credits per page, or $7.50 per 1,000 pages. The most expensive is the Agentic extract (15) plus Agentic Plus parse (45), which is 60 credits per page, or $75 per 1,000 pages.

The practical lesson: when you budget for structured extraction, you are always paying for two tiers, not one. If you size a project on the extract number alone, your real bill is higher by the full parse cost of every page.

Is LlamaParse free?

Partly, and this is where it beats its rivals. LlamaParse gives you 10,000 free credits every single month, standing, not a one-time trial. That resets on a monthly cycle, so it is a genuine ongoing allowance.

What 10,000 monthly credits buys depends on your tier. At the Fast rate of 1 credit per page, that is 10,000 free pages a month. At the Agentic rate of 10 credits per page, it is 1,000 free pages a month. At Agentic Plus (45 credits), it is about 222 pages. For a small team or a proof of concept on simple documents, you may never pay anything.

The standing monthly reset is the differentiator. Landing AI gives 1,000 free credits that expire 90 days after signup, and Reducto gives 15,000 credits that are one-time only. LlamaParse is the only one of the three that keeps handing you free credits month after month.

Is LlamaParse cheaper than Reducto or Landing AI?

At the entry tiers, yes, LlamaParse is clearly the cheapest of the three; at the agentic tiers the three converge. The reason is that LlamaParse's credits are cheaper per unit ($0.00125 each) than Reducto's ($0.015) or Landing AI's ($0.01), so even similar credit-per-page counts land at very different dollar figures.

Two structural differences matter beyond the headline dollars. First, LlamaParse keeps structured extraction on a flat per-page credit tier, while both Reducto's Deep Extract and Landing AI's extract endpoint bill by the character: (input characters / 5,000) + (output characters / 1,000) credits, rounded up. That means on those two, a data-dense page costs a multiple of a sparse one, and any per-1,000-pages figure is an average, not a quote. LlamaParse's per-page pricing is more predictable. Second, watch the Landing AI classify trap: the widely repeated "0.5 credits per page" is the classify endpoint, not parsing. Real parsing on DPT-2 is 3 credits per page, or $30 per 1,000 pages, six times the number people cite. For the side-by-side across all three, see the full agentic extractor pricing comparison.

How does LlamaParse compare to cloud OCR?

It is several times more expensive than Read-class cloud OCR at every tier except Fast, and that premium buys reasoning. Legacy cloud OCR (AWS Textract Detect Document Text, Azure Document Intelligence Read, Google Document AI Enterprise OCR) all sit at about $1.50 per 1,000 pages. LlamaParse Fast at $1.25 actually undercuts them, but Fast is not agentic; it returns spatial text only. The moment you turn on the agentic parsing you came to LlamaParse for, you are at $12.50 per 1,000 pages, roughly 8x the cloud OCR rate.

Whether that premium is worth it comes down to your documents. On dense tables and nested layouts, the agentic markdown saves real downstream work. On clean typed pages, cloud OCR at $1.50 does the same job for a fraction of the money. You can line up every vendor's OCR rates per 1,000 pages before you decide which side of that line your documents fall on.

Is LlamaParse worth it?

It is worth it when you need clean, structured markdown from complex documents and you can live with parsing as the only step. LlamaParse produces genuinely better output than raw OCR on hard layouts, the free monthly allowance lowers the risk of trying it, and the Fast tier gives you a cheap non-agentic option when you do not need reasoning. For developers building a RAG pipeline who want good markdown out of PDFs, it is a strong default.

Where it stops is the workflow. LlamaParse hands you parsed output and nothing else. It does not classify incoming documents, map fields to your schema, validate values, route uncertain fields to a human, keep an audit trail, or write records into your ERP. Once you have clean output, you often want to do something with it: for instance, you might want to turn that parsed report into a shareable slide deck rather than leave it as raw markdown. Those steps are real work, and they usually cost more in year one than the parsing does.

If you want the parsing plus the workflow as one product, DocuOCR ships classification, extraction, validation, human review, audit trail, and export together, priced per page at about $14 to $20 per 1,000 pages with the workflow included. You can try it free on one of your own documents and compare the structured output side by side.

The short version

LlamaParse costs $1.25 to $75 per 1,000 pages, billed in credits at 1,000 credits per $1.25. Fast is the cheapest at $1.25 but returns plain spatial text; the agentic parsing most people want starts at $12.50, and structured extraction stacks an extract tier onto a parse tier for up to $75. The 10,000 free monthly credits are the best free tier in the category. It is cheaper than Reducto and Landing AI at the entry tiers, more predictable on extraction because it stays per-page, and worth it when you need clean markdown from hard documents and can handle the rest of the workflow yourself.