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Doc2Markdown
Docling
MarkItDownai.org
Markovo
MarkItDown
Markdown.free
Upload a document and turn it into clean, token-efficient Markdown for ChatGPT, Claude, Gemini, Cursor and RAG workflows.

Cursor
GitHub Copilot
warp by spolu
Google Antigravity
opencode
Windsurf Editor
Codex 3.0 by OpenAI
Transform hours of debugging into seconds with a single command. Experience coding at thought-speed with Claude's AI that understands your entire codebase—no more context switching, just breakthrough results.

Which is more popular?
Website, pricing, platforms and company facts side by side.
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| Website | tokenpig.co | anthropic.com |
| Pricing | — | |
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| Listed in |
In their own words, as submitted to SaaSHub.


TokenPig converts documents into clean, structured Markdown built specifically for LLM and RAG workflows — ChatGPT, Claude, Gemini, and retrieval pipelines. The problem Raw PDF, Word, PowerPoint and Excel exports carry a lot of formatting noise — repeated headers, broken tables, inconsistent...
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What each product offers, as listed by its team.


Possible disadvantages
An editorial look at what each product does well and who it suits.


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Overall verdict
Why this product is good
Recommended for
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How often each product is chosen within a category, 0–100% relative to the other.


As answered by people managing TokenPig and Claude Code.
TokenPig's answer
TokenPig started from a recurring frustration: pasting PDF or Word exports into an LLM and watching layout noise — repeated headers, broken tables, stray whitespace — burn through the context window before the actual content even got read. TokenPig was built to solve that specific problem: clean, structured Markdown output plus visibility into the tokens saved.
TokenPig's answer
Two main groups: individuals who regularly feed documents into ChatGPT or Claude and want cleaner, cheaper context (researchers, consultants, students), and developers/teams building RAG pipelines who need reliable document-to-Markdown conversion via API.
TokenPig's answer
TokenPig focuses specifically on token efficiency, not just format conversion. Alongside clean Markdown output, it shows an estimated token savings for every conversion, so users can see exactly how much context window they're recovering before pasting a document into ChatGPT, Claude or Gemini — something general-purpose converters don't surface.
TokenPig's answer
TokenPig runs entirely in the browser — no Python setup, no libraries to install, no code to maintain. That makes it accessible to non-developers (consultants, researchers, students) while still offering batch processing and an API for teams that want to automate document ingestion at scale.
TokenPig's answer
TokenPig's answer
Built as a modern web application using Next.js and TypeScript, with a focus on fast, reliable document processing entirely server-side — no client installation required.
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