Math-To-Manim

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Math-To-Manim is an open-source AI tool that creates math and physics animations and study notes from text and images. It leverages AI pipelines to generate pedagogically sound Manim animations.

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At a glance

Pricing

Open Source

Free tier

Yes

API

Skill level

Technical

About

What is Math-To-Manim?

Math-To-Manim is an open-source AI tool designed to generate epic math and physics animations and study notes from text and images. It utilizes advanced AI pipelines, including Google Gemini 3, Claude Sonnet 4.5, and Kimi K2.5 Swarm, to analyze concepts, discover prerequisites, enrich content with LaTeX equations, and design visual specifications. The tool then composes verbose prompts to generate working Manim Python code, enabling the creation of complex animations without manual coding. It focuses on building pedagogically sound animations that flow from foundational to advanced topics, making it ideal for educational content creation.

Best used for

Ideal for professors and students who need to create engaging visual explanations for complex math and physics topics, generate detailed study notes, and animate scientific concepts. Especially valuable for educators and learners seeking to understand and present advanced subjects through dynamic visualizations.

Common actions

generate animations

create educational content

visualize math concepts

explain physics principles

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Capabilities

Key features

Generate math/physics animations
Create study notes
AI-powered Manim code generation
LaTeX equation enrichment
Recursive prerequisite discovery
Multi-agent AI pipelines

Target Audience

professorstudentteachertutor

Integrations

Not yet documented

Pricing & Plans

Open Source

Free

FAQs

What AI models does Math-To-Manim support?

Math-To-Manim supports three distinct AI pipelines: Google Gemini 3 (ADK), Claude Sonnet 4.5 (Anthropic SDK), and Kimi K2.5 Swarm (OpenAI-compatible API). Users can choose the pipeline based on their API access and specific preferences for architecture and reasoning capabilities.

What are the technical requirements to run Math-To-Manim?

To run Math-To-Manim, you need Python 3.10+, an API key for Anthropic, Google, or Moonshot, FFmpeg for video rendering, and Manim Community v0.19.0. A minimum of 8GB RAM is required, with 16GB recommended for optimal performance.

How does Math-To-Manim ensure pedagogical accuracy in its animations?

The tool uses a six-agent reverse knowledge tree pipeline that analyzes concepts, recursively discovers prerequisites, and enriches each concept with LaTeX equations and definitions. This process ensures that animations flow logically from foundational to advanced topics, building pedagogically sound explanations.

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Subcategories trending in Research & Education

Academic Research Study Assistants Knowledge Management Scientific Computing Summarization Language Learning

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Also listed in

This tool also appears in

Content & Design › 3D & Animation Content & Design › Video Generation

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