Top 5 PDF to Markdown Tools Compared 2026 — BetaPDF, Marker, Adobe, CloudConvert, Landing AI

If you're building a RAG pipeline, a document chatbot, or just want ChatGPT to answer accurately about a PDF — the PDF → Markdown preprocessing step decides 70% of your output quality.

The problem: most online tools just lift the text layer (PyPDF2, PyMuPDF text-mode) and paste it flat — which breaks on four common file types:

• 📑 Scanned PDFs / photos of documents — no text layer, tools come back empty
• 📊 Tables with merged cells — markdown pipe syntax breaks colspan/rowspan, data clumps
• 🧮 Math formulas — flattened to garbled glyphs (EβᵢXᵢ instead of LaTeX \sum \beta_i X_i)
• 📰 Multi-column layouts — textbooks and journals get read in the wrong order

This article compares the 5 most-used PDF → Markdown tools in 2026, scored across 8 concrete criteria. By the end you'll know which one fits your use case.

1. Speed — wall-clock time on a typical 9-page PDF. Critical for batch jobs.
2. Entry price — cost for ~1000 pages/month. Matters most for indie devs and small teams.
3. Tables preserved — does the tool emit HTML <table> (the only reliable way to keep merged cells) or pipe-markdown that mangles them?
4. LaTeX formulas — are equations kept as native LaTeX or flattened?
5. Native scanned-PDF support (VLM) — does it run a vision model on the pixels, or rely on an OCR layer?
6. Extracted images — are embedded images saved to their own files with relative links in the markdown?
7. JSON bbox for RAG — is there per-block bounding-box metadata for retrieval-quality chunking?
8. Vietnamese diacritic accuracy — how well does the model preserve VN tonal marks on 300-DPI scans? Most Western tools don't optimize for this.

1. BetaPDF (cloud, Vietnam)

MinerU 2.x + Qwen2-VL on vLLM (GB10 GPU). 22-30s for 9 pages. Ships ZIP {.md + .json bbox + images/}. Free 50 pages/file via web UI, API Pro at $9.99/mo (1,000 pages). Specifically tuned for Vietnamese documents.

2. Marker (open source, GitHub)

Popular OSS (~20k stars). LayoutLMv3 + Tesseract vision pipeline. High quality but requires self-hosting on an 8GB+ GPU. Slower in practice (60-180s for 9 pages on consumer GPU). Tables ship as pipe-markdown so merged cells suffer.

3. Adobe PDF Extract API

Enterprise product from Adobe. Strong table extraction on digital PDFs (Word exports). Weak on scans — no native VLM. $14.99/mo entry. No LaTeX for formulas.

4. CloudConvert

All-in-one conversion service. PDF→MD is a side feature using PyMuPDF text-mode. Fast but tables shatter, formulas drop. $8/mo for 100 pages — expensive at volume.

5. Landing AI ADE (Agentic Document Engine)

New AI product from Andrew Ng. Proprietary vision model, quality on par with Marker but faster. $250/mo for 5,000 pages on the Team plan — 25× more expensive than BetaPDF. Developer-friendly SDK + bbox JSON for RAG.

As of May 2026. Marker requires self-hosting on 8GB+ GPU (RTX 3060 or better). CloudConvert's $8 plan caps at 100 pages/month. Landing AI ADE Team plan is $250/mo for 5,000 pages — affordable for enterprise, expensive for indie devs. Vietnamese accuracy: most Western tools don't publish a specific number, but real-world testing on 100-page 300-DPI scans shows 3-7% diacritic loss — BetaPDF benchmarks separately for VN so the advantage is clear.

👉 Indie dev / small startup, need a cheap RAG API

→ BetaPDF. $9.99/mo for 1,000 pages is the cheapest VLM + bbox JSON option. 3-line curl setup, returns Landing-AI-shape JSON ready for LangChain/LlamaIndex.

👉 Working with Vietnamese documents (contracts, scanned IDs, textbooks)

→ BetaPDF. 99.7% diacritic accuracy on scans is unmatched. The pipeline is tuned specifically for Vietnamese.

👉 Researcher with an 8GB+ GPU, wants full control

→ Marker. Free, open source, runs locally — sensitive data never leaves your machine. Slower but you can customize the VLM prompts.

👉 Enterprise with budget, needs SLA + guaranteed uptime

→ Landing AI ADE. $250/mo gets you team support, official SDK, audit log. Right when compliance matters more than cost.

👉 Just need to convert 1-2 simple digital PDFs, no API

→ BetaPDF web UI. Visit betapdf.com, drag-drop, download ZIP. No signup, no ads.

👉 Need integration with no-code (Zapier, n8n, Make.com)

→ Adobe Extract. Officially supported in major no-code platforms. OAuth setup is more involved but integrations are ready.

Free tier — Web UI, 50 pages/file

1. Visit betapdf.com/en/tools/pdf-to-markdown
2. Drag-drop a PDF (or JPG/PNG/WEBP image) into the upload zone
3. Choose "Vietnamese" or "Auto" language
4. Click Convert, wait 22-30 seconds for a 9-page file
5. Download the ZIP, open the .md in VS Code / Obsidian / paste into ChatGPT

Pro tier — API $9.99/mo, 1,000 pages/month

curl -X POST https://betapdf.com/api/v1/parse \
  -H "Authorization: Bearer beta_live_xxx" \
  -F "file=@contract.pdf"

Returns JSON: { markdown, chunks: [{type, markdown, grounding: {box_normalized, page}}], metadata }. Drop-in for RAG pipelines.

After comparing the 5 popular PDF → Markdown tools of 2026, here's the short verdict:

• 🏆 BetaPDF — best value for indie/small teams needing VLM + bbox JSON + Vietnamese support. $9.99/mo is 25× cheaper than Landing AI for equivalent quality on Vietnamese content.
• 🥈 Landing AI ADE — best for enterprises with budget that need SDK + SLA.
• 🥉 Marker — best for researchers with a GPU who want self-hosted + privacy.
• 📃 Adobe Extract — pick when you need ready-made no-code integration (Zapier/n8n).
• ❌ CloudConvert — only for simple digital PDFs, not recommended for production RAG.

If you don't need an API and just want to try quickly — visit betapdf.com, drag-drop your PDF or document photo, download the ZIP. 100% free, no signup, files auto-delete after 6h. If your file is in Vietnamese, BetaPDF gives the best results in this category.

See also: PDF to Markdown guide · Vietnamese OCR PDF · API reference