PDFjet vs LlamaParse
Two RAG-native parsers. LlamaParse is deeply tied to LlamaIndex; PDFjet is a standalone API that also converts, merges and never keeps your files.
LlamaParse is a genuinely strong RAG parser: layout-aware OCR turns complex PDFs into clean Markdown or JSON, tables become structured output, and it drops straight into LlamaIndex pipelines. Its FAQ states your data is never used for training and files are deleted after a 48-hour cache.
PDFjet targets the same RAG job as a standalone API and differs on scope and retention: it also returns CSV, editable Word and a searchable PDF, converts and merges files, gives you per-element bounding boxes, and never stores your files at all — no cache window.
LlamaParse vs PDFjet, feature by feature
| Capability | PDFjet | LlamaParse |
|---|---|---|
| PDF → CSV (tables) | ||
| PDF → Markdown (RAG-ready) | ||
| PDF → structured JSON | ||
| PDF → editable Word (.docx) | ||
| OCR of scans / searchable PDF | Partial | |
| AI / vision-model extraction | ||
| RAG chunking (heading-aware) | ||
| Per-element bbox provenance | Partial | |
| Schema-guided field extraction | Partial | |
| Convert files → PDF | ||
| Merge / split / encrypt | ||
| Files never stored | Partial |
Comparison reflects each vendor's public documentation as of July 2026. Capabilities change — check the source links below before relying on a specific detail.
When LlamaParse may fit better
- •You're building on LlamaIndex and want a parser that plugs straight into that framework and its agent tooling.
- •You need best-in-class AI parsing accuracy on very messy, layout-heavy documents and charts.
- •You want a documented no-training guarantee (LlamaParse caches files 48h, then deletes, and states data isn't used for training).
When PDFjet is the better call
- •You want zero retention with no cache window — PDFjet stores nothing, versus LlamaParse's 48-hour cache.
- •You need CSV, editable Word or a searchable PDF directly, plus convert/merge/split/encrypt — all outside LlamaParse's scope.
- •You want a framework-agnostic API (works from any language, plus an MCP server for Claude/Cursor), not a LlamaIndex-centric one.
- •You want a deterministic, on-server option and per-element bounding boxes for exact citations.
Try PDFjet in one call
Point your PDF at one endpoint and pick the output — CSV, Markdown, JSON, editable Word, or a searchable PDF. No SDK required.
curl -X POST https://pdfjet.dev/extract/md \
-H "Authorization: Bearer pj_live_..." \
-F [email protected]FAQ
Is PDFjet a good alternative to LlamaParse?
Yes, particularly if you want zero data retention with no cache window, need CSV/Word/searchable-PDF and convert/merge/split alongside Markdown, or prefer a framework-agnostic API over one centered on LlamaIndex. LlamaParse remains excellent for LlamaIndex-native, high-accuracy AI parsing.
What's the difference between PDFjet and LlamaParse?
Both produce RAG-ready Markdown and JSON. LlamaParse is tightly integrated with LlamaIndex and caches files for 48 hours; PDFjet is a standalone API that also does CSV, Word, searchable PDF, convert, merge, split and encrypt, and never stores files.
Does LlamaParse store or train on my documents?
Per LlamaParse's FAQ, files are cached for 48 hours then permanently deleted and are not used for model training. PDFjet goes further and never stores your files at all.
Switching from LlamaParse? Start free.
100 pages/month, every feature, zero data retention. No credit card.
Get your free API key →More comparisons
Sources: developers.llamaindex.ai/llamaparse/·www.llamaindex.ai/pricing·developers.llamaindex.ai/llamaparse/general/faq/