Extract plain text from a PDF in your browser - perfect for searching, quoting, or feeding into AI tools. No upload.
Drop one or many - all convert to TXT. Per-row progress, batch convert, ZIP download.
Going PDF to TXT is what you want when you need the words, not the layout. Researchers grabbing quotes from a paper, students prepping notes from a textbook, anyone feeding a long PDF into ChatGPT or a search index - all of them just need the text. Stripping it out manually means copy-pasting page by page; this does it in one click.
Extraction runs locally via Mozilla's PDF.js engine: we read each page's text layer (the same one your PDF viewer uses for select-and-copy) and concatenate it with page breaks. PDFs that store their content as scanned images won't yield text - those need OCR, which is a separate workflow. Everything happens in your browser; no PDF is uploaded.
The big use case in 2025 is AI input prep. LLMs are excellent at summarising text but choke on raw PDFs (they have to decode the file format first, which often hallucinates or skips content). Pre-extracting to plain text gives the model exactly the words on the page in the order they appear, which produces dramatically better summaries, Q&A answers, and analyses. If you're regularly feeding research papers, legal documents, or financial filings to ChatGPT or Claude, this is the cleanest pipeline.
Academic and legal workflows are the other major bucket. Researchers cite papers by quoting passages; the easiest path is "extract to text, grep for the keyword, copy the surrounding paragraph". Paralegals and lawyers do something similar for contracts and case files. The text-extraction step removes formatting and layout noise so plain-text tools (grep, ripgrep, an editor's find feature) work the way they're supposed to.
A note on what won't extract well: scanned documents (just images of text - need OCR), copy-protected PDFs (rare but exist - some publishers ship "no copy" PDFs), PDFs with embedded fonts that use custom glyph mappings (some Asian-language PDFs, some math-heavy academic PDFs - the visible text doesn't map back to standard Unicode). The success rate on consumer and business PDFs is near 100%; on academic and government PDFs it's roughly 95%. Try it - the worst case is empty output, no harm done.
LLMs handle plain text far better than raw PDF uploads. Extract first, then paste the text into a chat or send via API for summarisation, Q&A, or analysis.
Researchers grep extracted text for keywords, then copy the surrounding paragraph as a quote. Faster than scrolling through a PDF reader page by page.
Paralegals search for specific clauses or numbers across long agreements. Plain text is greppable; PDF rarely is.
Elasticsearch, Algolia, and Postgres full-text search all consume plain text. Extract once, index forever.
ML pipelines that fine-tune on documents need raw text. Strip the visual styling so the model sees only the words.
Some screen readers struggle with PDFs but handle plain text or HTML smoothly. Extract first, restyle for reading.
PDF is the universal document format - looks the same on every device, prints reliably, and is the canonical way to share images that should stay fixed in layout.
A plain UTF-8 text file with no formatting. Opens in every editor on every device. Perfect for piping into other tools, grep-able search, and feeding into LLMs.
Drag a PDF onto the converter above, or click the box to pick one from your device.
We've preselected TXT as the output format. Change it from the dropdown if you want a different target.
Click Convert and wait for the progress bar to finish. Download the TXT when it's ready.
Convert a PDF to JPG images - one image per page, packaged as a ZIP for multi-page PDFs.
Render PDF pages to lossless PNG images - perfect for sharing diagrams, slides, or screenshots-style pages.
Turn a plain text file into a printable PDF in seconds - free, browser-only, no signup.