pdfmux vs LlamaParse: Which PDF extraction tool should you use?
pdfmux wins on cost, privacy, and independence from cloud APIs. LlamaParse is LlamaIndex’s cloud-based document parsing service that uses AI to extract structured content from PDFs. It produces good results — but it requires sending your documents to a third-party server, charges per page, and ties you to the LlamaIndex ecosystem. pdfmux runs entirely locally, is free to use, and produces comparable output quality.
For teams that care about data privacy, predictable costs, and avoiding vendor lock-in, pdfmux is the clear choice.
Feature Comparison
| Feature | pdfmux | LlamaParse |
|---|---|---|
| Deployment | Local, self-hosted | Cloud API only |
| Pricing | Free (MIT license) | Free tier + per-page pricing |
| Data privacy | Documents never leave your machine | Documents uploaded to LlamaIndex cloud |
| Output formats | Markdown, JSON | Markdown, text |
| Table extraction | Built-in, high accuracy | AI-powered, good accuracy |
| Offline support | Full offline capability | Requires internet connection |
| Rate limits | None | API rate limits apply |
| Vendor lock-in | None | LlamaIndex ecosystem |
Benchmark Comparison
| Metric | pdfmux | LlamaParse |
|---|---|---|
| Text accuracy (mixed layouts) | 94.2% | 93.1% |
| Table extraction F1 | 91.8% | 90.5% |
| Speed (pages/sec, local) | 45 | N/A (cloud) |
| Latency per page | ~22ms | 500ms-2s (network) |
| Cost per 1,000 pages | $0 | $3-10 |
| Offline capable | Yes | No |
LlamaParse achieves competitive accuracy using server-side AI models, but the network latency and per-page cost add up quickly at scale.
When to Use LlamaParse
LlamaParse is the right choice when you need:
- Zero setup — no installation, no environment configuration, just an API key
- LlamaIndex integration — you’re already using LlamaIndex and want native parsing
- Complex scanned documents — LlamaParse’s cloud AI can handle heavily degraded scans
- Low volume — the free tier (1,000 pages/day) covers your needs
- Managed infrastructure — you prefer paying per page over managing extraction infrastructure
When to Use pdfmux
pdfmux is the better choice when you need:
- Data privacy — documents stay on your infrastructure, never uploaded to third parties
- Cost control — free at any scale, no per-page charges
- Low latency — local processing at ~22ms/page vs 500ms+ cloud round trips
- Offline capability — works in air-gapped or restricted network environments
- No vendor lock-in — MIT-licensed, works with any framework (LangChain, LlamaIndex, Haystack, etc.)
- High volume processing — batch processing thousands of PDFs without API rate limits or costs
Quick Code Comparison
pdfmux:
import pdfmux
result = pdfmux.convert("report.pdf")
print(result.markdown)
LlamaParse:
from llama_parse import LlamaParse
parser = LlamaParse(api_key="llx-...")
documents = parser.load_data("report.pdf")
print(documents[0].text)
FAQ
Is LlamaParse free?
LlamaParse offers a free tier of 1,000 pages per day. Beyond that, you pay per page. For teams processing thousands of documents, the costs can become significant. pdfmux is completely free under the MIT license.
Is LlamaParse more accurate than pdfmux?
For most text-based PDFs, accuracy is comparable. LlamaParse can perform better on heavily scanned or degraded documents thanks to server-side AI models. For text-based PDFs with tables and complex layouts, pdfmux often produces cleaner output.
Can I use pdfmux with LlamaIndex?
Yes. pdfmux works with LlamaIndex through the standard document loader interface. You get the local processing benefits of pdfmux with the full RAG capabilities of LlamaIndex — the best of both worlds.
Looking for detailed benchmarks? Read our comprehensive PDF extraction benchmark. For a broader comparison of all Python PDF libraries, see Best PDF Extraction Library for Python.