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# Why PDFs break LLMs — and what clean Markdown fixes Jun 12, 2026 · The markitdown.ai team · 3 min read A PDF renders perfectly for a human and falls apart the moment a model reads it. The page you see — columns, tables, headers, footnotes — is a *visual* arrangement, not a logical one. When you pull raw text out of it, that visual order rarely survives, and whatever you feed a language model is only as good as the text it actually receives. ## What actually goes wrong When teams pipe documents straight into an LLM or a retrieval index, a few failure modes show up again and again: - **Reading order breaks.** Multi-column layouts interleave. A two-column page becomes "line 1 left, line 1 right, line 2 left, line 2 right…", so a sentence a human reads top-to-bottom arrives at the model scrambled.- **Tables collapse.** Copy-paste turns a table into a loose run of numbers. The relationship between a header and its cell — the entire point of a table — is gone.- **Headings disappear.** The visual hierarchy (this is a section, this is a subsection) is encoded as font size and weight, not structure. Strip the styling and you get one undifferentiated wall of text.- **Noise creeps in.** Page numbers, running headers, hyphenated line breaks, and stray ligatures end up inline, polluting prompts and embeddings alike.