
EatsReady
Foody
Capy Eats — Stop scrolling. Get one dish that fits your taste.

Markitdown Online
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.

Which is more popular?
Website, pricing, platforms and company facts side by side.
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| Website | capyeats.dnkistudio.com | tokenpig.co |
| Pricing | ||
| Platforms | — | |
| Company | 2026 | — |
| Listed in |
In their own words, as submitted to SaaSHub.


Capy Eats is a food decision app for the “what should I eat?” moment. Tell Dada your taste, swipe through a calibration, and get one dish instead of an endless list. It learns from your likes, skips, mood, budget, and history; filters allergies and avoided ingredients; and shows nutrition context...
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...
What each product offers, as listed by its team.


How often each product is chosen within a category, 0–100% relative to the other.


As answered by people managing Capy Eats and TokenPig.
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.
Share your experience with using Capy Eats and TokenPig. For example, how are they different and which one is better?
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