- Memory-mapped file I/O (no read syscalls)
- Zero-copy parsing where possible
- SIMD-accelerated string search for finding PDF structures
- Parallel extraction across pages using Zig's thread pool
- Streaming output (no intermediate allocations for extracted text)
What it handles:
- XRef tables and streams (PDF 1.5+)
- Incremental PDF updates (/Prev chain)
- FlateDecode, ASCII85, LZW, RunLength decompression
- Font encodings: WinAnsi, MacRoman, ToUnicode CMap
- CID fonts (Type0, Identity-H/V, UTF-16BE with surrogate pairs)
FWIW - mupdf is simply not fast. I've done lots of pdf indexing apps, and mupdf is by far the slowest and least able to open valid pdfs when it came to text extraction. It also takes tons of memory.
a better speed comparison would either be multi-process pdfium (since pdfium was forked from foxit before multi-thread support, you can't thread it), multi-threaded foxit, or something like syncfusion (which is quite fast and supports multiple threads). Or even single thread pdfium vs single thread your-code.
These were always the fastest/best options. I can (and do) achieve 41k pages/sec or better on these options.
The other thing it doesn't appear you mention is whether you handle putting the words in reading order (IE how they appear on the page), or only stream order (which varies in its relation to apperance order) .
If it's only stream order, sure, that's really fast to do. But also not anywhere near as helpful as reading order, which is what other text-extraction engines do.
Looking at the code, it looks like the code to do reading order exists, but is not what is being benchmarked or used by default?
If so, this is really comparing apples and oranges.
very nice, it'd be good to see a feature comparison as when I use mupdf it's not really just about speed, but about the level of support of all kinds of obscure pdf features, and good level of accuracy of the built-in algorithms for things like handling two-column pages, identifying paragraphs, etc.
the licensing is a huge blocker for using mupdf in non-OSS tools, so it's very nice to see this is MIT
Impressive performance gains! 5x faster than MuPDF is significant, especially for applications processing large volumes of PDFs. Zig's memory safety without garbage collection overhead makes it ideal for this kind of performance-critical work.
I'm curious about the trade-offs mentioned in the comments regarding Unicode handling. For document analysis pipelines (like extracting text from technical documentation or research papers), robust Unicode support is often critical.
Would be interesting to see benchmarks on different PDF types - academic papers with equations, scanned documents with OCR layers, and complex layouts with tables. Performance can vary wildly depending on the document structure.
Is there the possibility to hook in OCR for text blocks flattened into an image, maybe with some callback? That’s my biggest gripe with dealing with PDFs.
15 comments
[ 3.1 ms ] story [ 37.5 ms ] thread~41K pages/sec peak throughput.
Key choices: memory-mapped I/O, SIMD string search, parallel page extraction, streaming output. Handles CID fonts, incremental updates, all common compression filters.
~5,000 lines, no dependencies, compiles in <2s.
Why it's fast:
What it handles:a better speed comparison would either be multi-process pdfium (since pdfium was forked from foxit before multi-thread support, you can't thread it), multi-threaded foxit, or something like syncfusion (which is quite fast and supports multiple threads). Or even single thread pdfium vs single thread your-code.
These were always the fastest/best options. I can (and do) achieve 41k pages/sec or better on these options.
The other thing it doesn't appear you mention is whether you handle putting the words in reading order (IE how they appear on the page), or only stream order (which varies in its relation to apperance order) .
If it's only stream order, sure, that's really fast to do. But also not anywhere near as helpful as reading order, which is what other text-extraction engines do.
Looking at the code, it looks like the code to do reading order exists, but is not what is being benchmarked or used by default?
If so, this is really comparing apples and oranges.
You didn't. Claude did. Like it did write this comment.
And you didn't even bother testing it before submitting, which is insulting to everyone.
the licensing is a huge blocker for using mupdf in non-OSS tools, so it's very nice to see this is MIT
python bindings would be good too
- commit message: LLM-generated.
- README: LLM-generated.
I'm not convinced that projects vibe coded over the evening deserve the HN front page…
Edit: and of course the author's blog is also full of AI slop…
2026 hasn't even started I already hate it.
I'm curious about the trade-offs mentioned in the comments regarding Unicode handling. For document analysis pipelines (like extracting text from technical documentation or research papers), robust Unicode support is often critical.
Would be interesting to see benchmarks on different PDF types - academic papers with equations, scanned documents with OCR layers, and complex layouts with tables. Performance can vary wildly depending on the document structure.
fpdf
jpdf
cpdf
cpppdf
bfpdf
ppdf
...
opdf
https://github.com/Lulzx/zpdf/blob/main/python/tests/test_zp...
[1] https://github.com/pdf-association/pdf-corpora