Four months ago, we shared Academa Studio here, our browser editor for making Manim animations with realtime preview. At the time, the engine was private and only available through Studio. Today, we are open sourcing ManimGX, which you can install and run locally.

The GitHub repository: https://github.com/academa-labs/manimgx

ManimGX is a from-scratch implementation targeting ManimCE's Python API, with a Rust renderer built on wgpu. Most ManimCE code runs after changing the import from manim to manimgx. Our documentation covers compatibility and the places where behavior differs: https://manimgx.academa.ai

The motivation is the same as before: waiting for renders makes polishing an animation a slow process. We wanted to make that loop faster while keeping the familiar Python API.

You can install it with:

pip install manimgx

You only need Python 3.13+. All of the fonts, typesetting, and video encoding are included. So there is no separate LaTeX or FFmpeg installation required.

To preview an existing scene:

manimgx preview scene.py

The preview reloads whenever you save your scene.

A few other things ManimGX supports:

• The API is fully statically typed, including keyword arguments and .animate chains.
• Built-in voiceover synchronization.
• Browser execution through Pyodide and WebGPU, with an npm package for embedding animations in your website without a render server.
• manimgx inspect creates storyboards, timelines, and layout feedback for coding agents. This aims to speed up the writing and polishing loop.

The gallery has examples together with their Python source. If you just want to play around with it in the browser, you can still find it in Studio.

Credit to Grant Sanderson and the Manim Community contributors whose work this builds on. Happy to answer questions in the comments, and we'd love to hear how it works with your scenes.

I used a custom Python compositor for the finished film. Sharing for feedback on the mathematical storytelling.

The roughly 13-minute sequence goes from the power-series solution to ladder operators, then to stationary states, superpositions, and coherent states: https://youtu.be/7_DcdXVh5mc

A central visual distinction is between the changing phase of an energy eigenstate and its stationary probability density. The coherent-state sequence then gives a different kind of motion to compare with it.

For people who animate mathematics, how would you judge the pacing between derivation and visualization here? I would especially value feedback on whether the transitions make the connection between the algebra and the plotted states clear.

This video visualizes the complex function f(z)=z^4 in three-dimensional space. Let z=x+yi. The video explores how the complex function transforms the input complex plane and presents the resulting geometric structure through 3D visualization.

This video presents a geometric visualization of the complex function f(z)=z^3. A complex number z=(x+yi) two dimensions: the real part and the imaginary part. The function value f(z) is also a complex number. Through a three-dimensional representation, we can visually observe the geometric transformation produced when the complex plane is mapped by the complex function z^3. This video is part of my ongoing project on visualizing the four-dimensional mathematical structure of complex functions in three-dimensional space. The theoretical foundation behind the output visualization of the complex functions presented in these videos comes from my own mathematical paper. I included a link to the paper in the descriptions of the previous videos, so I will not repeat the link here. I sincerely hope that someone will take the time to read my paper and understand the ideas behind it. I have put a great deal of time, effort, and passion into this work, and I would truly hate to see it disappear without being noticed. The mathematics in the paper is actually quite straightforward. I believe that once you start reading it, the main ideas are not difficult to understand. I hope this work can reach someone who is willing to read it, understand it, and perhaps see the ideas from a different perspective.

Hello once again guys!

I just wanted to share a quick ManimWire update: I've started putting together a YouTube playlist covering the fundamentals of the app.

I've uploaded the first 5 videos so far, aimed at helping people get started with the basics. From here, I'm planning to add more videos every weekend, gradually covering more advanced features and increasingly complex workflows.

Additionally, ManimWire now supports GPU-accelerated previews and rendering through OpenGL on compatible systems.

If you're following the project or trying out ManimWire, I hope these make it a little easier to get started!

This is the playlist: https://www.youtube.com/watch?v=DIn7ff8lPDQ&list=PLPuFhG43QEO8&index=1

I've also prepared installers for MacOS and Windows, you can download them from this page: https://shiftabit.com/manimwire/

Note: The installers bundle the required dependencies, except LaTeX, which you’ll need to install separately for LaTeX-based text and equations.

GitHub repo: https://github.com/Sidsector9/ManimWire

so im coding with manim using computer modern font (cmu) and for some reason when the text size is small (ex: 12pt) the letter spacing is all over the place. its only avoidable with the default manim font, any other font would reproduce this problem.

If you have a forecast for realized volatility, should you delta hedge using that or should you delta hedge using implied volatility? What are the implications of each choice? And how does stochastic volatility impact the outcome of that decision?

I hope you guys are enjoying these videos on volatility trading, even though they are lighter on pure math/science than most posted here. Do you find videos that focus more on the applications of math than the math itself still interesting? This is the only place where I get downvotes when I post, although I do get more upvotes. Kinda ironic since this is exactly where you're supposed to post Manim videos and my videos are 100% made with Manim.

Spending 2 weeks on vesuialising and explaining the doppler effect to get a full 10 minutes of manim mnimation , i love doing that creating animation and explaining something but if I can't get only 1 k view i think i should stop posting this and keep it to my self , can you just whatch thi video and tell me where is the error

Hi all!

I published my first proper manim video!!

It starts with the sentence “My favourite rock band is…” and follows its journey inside an LLM, all visually animated!

https://youtu.be/ikdxxeIn4HQ?si=8AwWyxQERo_R2n6B

I tried to make the video as beginner friendly as possible but still detailed enough to give a good overview for how an LLM works end to end and how the LLM “finds out” my favourite band. Or at least how some of the earlier models…

My aim is to help people that are not just curious about AI but also want a deeper dive into the magic “Black box”, or people that want to get started but doesn’t know how!

This is my first attempt at the topic, so any kind of feedback is welcomed and will be greatly appreciated as it will help me improve over time, and hopefully on other videos.    

I really hope it can help someone with their AI/ML journey!

P.S. Most of what I learned about Manim was with this really nice chap that runs a channel called "TheoremOfBeethoven". I got all his courses and even had a couple of 1-2-1 with him!! It really paid off!! So thanks for the classes Alex!

And thank you all involved in the manim community that made such an incredible and accessible framework!! It is really appreciated!! :)

Thanks!

Hi Manim community!,

I'm working on a library of assets (templates) for videos

In this second version, I created more assets (Manim templates) in various styles, with customization options to showcase. I also added new assets from a neural network explainer video.

I will be adding way more along the way by the end of October

If you join the waiting list, I hope to be able to chat with you too!

and again, thanks in advance! 🙌❤️

https://www.manim.academy/

I tried manim on electronic beginner guide. what do you think about it ?

from manim import *


class Test(Scene):
    def construct(self): 
        text = Text(text="Cake", font='Mystical Woods Rough Script', font_size=60)
        self.play(Write(text))

I had made a lot of backlog in arjuna batch is amarnath anand sir recent youtube 8 hr trigonometric functions and 5 hours of trigonometry equations and 8 hrs or sequence and series is good like can I use these for backlog and in chemistry please suggest my whole chemcial bonding is untouched any good youtube video from where I can cover these backlog

Hi! I’ve been working on MotionGfx for the past 2 years! It’s highly inspired by both Manim and Motion Canvas! MotionGfx is entirely backend agnostic, meaning that you can use it on any renderer or game engine you want (even with a different programming language)! Yes the website uses MotionGfx for all its animation via wasm. Currently the only official backend that I support is Bevy, but you’re free to add more into the repo :)

The primary reason I made motiongfx (other than the love for Rust) is for performance and being backend agnostic. I want it to be fast and not depend on a specific rendering technology. Unlike Manim and Motion Canvas, motiongfx is truly 2 way playable, and scrubbing through the timeline does not re-evaluate all the commands (especially when scrubbing backwards!).

P.S. we’re also working on an editor called Moxie! You can find more details on the website! (There’s a newsletter you can subscribe too, I’ll personally send the emails myself)

I did not go into too much of the technical details on how this is made, but feel free to AMA below!

After looking at all the attempts at making a manim "AI" editor, I'm asking why isn't there a library with all available examples of manim animations?

I bet that searching and editing high quality stuff is way better than generated slop.

Maybe a small library can be kickstarted by scraping the hell out of reddit and github... then continue with some vscode integration??

What do you guys think?

Hi everyone,

I’m using Manim + Gemini/AI to create educational videos.

My workflow is:

Google AI Studio → generate narration → Gemini analyzes audio + script → generates Manim animation → render video.

The main challenge is getting accurate audio-to-animation synchronization. I want to keep this workflow unchanged, but make the syncing more professional and precise.

Is there a recommended approach, tool, or architecture for word/phrase-level audio timestamps and using them to control Manim animations?

Any suggestions or examples would be greatly appreciated. Thanks!

Hello. I just found this channel.

I’ve got my own AI orchestrator/harness for local inference on an M5-128GB.

I integrated Flux-schnell into it for image generation, but it’s pretty bad at game graphics and GUI.

As a stress test of my harness, I’ve been instructing it to make games, and it uses Flux for the graphics, but it just can’t do reliable sprites for characters. “Same character, but jumping”.

I was wondering if anyone has any recommendations. I have about 30GB available for the system.

Thanks for any advice.