Promptotype vs Dim0

A side-by-side comparison built from both listings. Blank cells mean the company has not given that detail; we never guess.

Promptotype compared with Dim0
Detail	Promptotype	Dim0
What it does	Platform for developing, testing, and monitoring structured LLM tasks	The open-source, real-time collaborative AI canvas with notes, mini-apps, and agents on one infinite board
Stage	Not given	MVP
Founded	Not given	Not given
Based in	Not given	FR
Pricing model	Freemium	Not given
Pricing	Free plan at $0/month includes advanced prompt engineering playground and test queries. Basic plan at $6/month adds prompt template library and collection testing. Professional plan at $10/month includes 60-day run history, fine-tuning, and 1 weekly scheduled run. Yearly pricing available with 2 mon	Free: €0 with 50 AI requests/day, 5 boards, up to 5 collaborators per board. Basic: €6.99/month with 150 AI requests/day, unlimited boards, up to 10 collaborators per board. Plus: €11.99/month with unlimited AI requests, unlimited boards, up to 20 collaborators per board. Self-host: Free MIT-license
Key features	Advanced prompt engineering playground Design prompt templates with extended playground Define test queries with expected result JSON schemas or values Test prompts across entire query collections Function calling support Run and test history tracking Schedule periodic automated tests Model fine-tuning from collections Team collaboration Prompt template and model library management	Real-time collaborative infinite canvas with multi-user sync AI mini-apps: interactive React apps generated directly on the canvas Board-aware AI agent that reads context, searches the web, runs code Notion-grade rich notes with toggles, math, tags, sub-pages Support for 8 AI models: Claude, GPT, Gemini, Mistral, DeepSeek, Qwen, Kimi, GLM Nested boards for organizing projects into folders Presentation mode to turn canvas into slides Mapify: turn notes into mind maps, schemas, or diagrams MIT-licensed open source, self-hostable with local Postgres and vector DB
What makes it different	Structured approach to prompt engineering with JSON schema validation Test entire collections of queries simultaneously for production readiness Automatic expected result generation from model outputs Full function calling support in playground and testing	All three tools—Notion, Excalidraw, ChatGPT—unified on one canvas, with the AI reading surrounding context before acting AI outputs placed as editable nodes on the board instead of lost in a chat sidebar Spatial thinking preserved: canvas keeps structure and relationships visible at once, unlike chat Fully open source and self-hostable with no vendor lock-in or proprietary format
Community votes	0	0
DR (Domain Rating by Ahrefs)	17 no change since last check	8 no change since last check
Trust Flow (Majestic)	3	10
Citation Flow (Majestic)	26	28
Referring domains (Majestic)	40	80

4 details filled in for both companies.

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