Rendering Reference

Prerequisites

`bash

manim --version # Manim CE

pdflatex --version # LaTeX

ffmpeg -version # ffmpeg

`

CLI Reference

`bash

manim -ql script.py Scene1 Scene2 # draft (480p 15fps)

manim -qm script.py Scene1 # medium (720p 30fps)

manim -qh script.py Scene1 # production (1080p 60fps)

manim -ql --format=png -s script.py Scene1 # preview still (last frame)

manim -ql --format=gif script.py Scene1 # GIF output

`

Quality Presets

Text rendering quality: -ql (480p15) produces noticeably poor text kerning and readability. For scenes with significant text, preview stills at -qm to catch issues invisible at 480p. Use -ql only for testing layout and animation timing.

Output Structure

`

media/videos/script/480p15/Scene1_Intro.mp4

media/images/script/Scene1_Intro.png (from -s flag)

`

Stitching with ffmpeg

`bash

cat > concat.txt << 'EOF'

file 'media/videos/script/480p15/Scene1_Intro.mp4'

file 'media/videos/script/480p15/Scene2_Core.mp4'

EOF

ffmpeg -y -f concat -safe 0 -i concat.txt -c copy final.mp4

`

Add Voiceover

`bash

Mux narration

ffmpeg -y -i final.mp4 -i narration.mp3 -c:v copy -c:a aac -b:a 192k -shortest final_narrated.mp4

Concat per-scene audio first

cat > audio_concat.txt << 'EOF'

file 'audio/scene1.mp3'

file 'audio/scene2.mp3'

EOF

ffmpeg -y -f concat -safe 0 -i audio_concat.txt -c copy full_narration.mp3

`

Add Background Music

`bash

ffmpeg -y -i final.mp4 -i music.mp3 \

-filter_complex "[1:a]volume=0.15[bg];[0:a][bg]amix=inputs=2:duration=shortest" \

-c:v copy final_with_music.mp4

`

GIF Export

`bash

ffmpeg -y -i scene.mp4 \

-vf "fps=15,scale=640:-1:flags=lanczos,split[s0][s1];[s0]palettegen[p];[s1][p]paletteuse" \

output.gif

`

Aspect Ratios

`bash

manim -ql --resolution 1080,1920 script.py Scene # 9:16 vertical

manim -ql --resolution 1080,1080 script.py Scene # 1:1 square

`

Render Workflow

1. Draft render all scenes at -ql

2. Preview stills at key moments (-s)

3. Fix and re-render only broken scenes

4. Stitch with ffmpeg

5. Review stitched output

6. Production render at -qh

7. Re-stitch + add audio

manim.cfg — Project Configuration

Create manim.cfg in the project directory for per-project defaults:

`ini

[CLI]

quality = low_quality

preview = True

media_dir = ./media

[renderer]

background_color = #0D1117

[tex]

tex_template_file = custom_template.tex

`

This eliminates repetitive CLI flags and self.camera.background_color in every scene.

Sections — Chapter Markers

Mark sections within a scene for organized output:

`python

class LongVideo(Scene):

def construct(self):

self.next_section("Introduction")

# ... intro content ...

self.next_section("Main Concept")

# ... main content ...

self.next_section("Conclusion")

# ... closing ...

`

Render individual sections: manim --save_sections script.py LongVideo

This outputs separate video files per section — useful for long videos where you want to re-render only one part.

manim-voiceover Plugin (Recommended for Narrated Videos)

The official manim-voiceover plugin integrates TTS directly into scene code, auto-syncing animation duration to voiceover length. This is significantly cleaner than the manual ffmpeg muxing approach above.

Installation

`bash

pip install "manim-voiceover[elevenlabs]"

Or for free/local TTS:

pip install "manim-voiceover[gtts]" # Google TTS (free, lower quality)

pip install "manim-voiceover[azure]" # Azure Cognitive Services

`

Usage

`python

from manim import *

from manim_voiceover import VoiceoverScene

from manim_voiceover.services.elevenlabs import ElevenLabsService

class NarratedScene(VoiceoverScene):

def construct(self):

self.set_speech_service(ElevenLabsService(

voice_name="Alice",

model_id="eleven_multilingual_v2"

))

# Voiceover auto-controls scene duration

with self.voiceover(text="Here is a circle being drawn.") as tracker:

self.play(Create(Circle()), run_time=tracker.duration)

with self.voiceover(text="Now let's transform it into a square.") as tracker:

self.play(Transform(circle, Square()), run_time=tracker.duration)

`

Key Features

• - tracker.duration — total voiceover duration in seconds
• - tracker.time_until_bookmark("mark1") — sync specific animations to specific words
• - Auto-generates subtitle .srt files
• - Caches audio locally — re-renders don't re-generate TTS
• - Works with: ElevenLabs, Azure, Google TTS, pyttsx3 (offline), and custom services

Bookmarks for Precise Sync

`python

with self.voiceover(text='This is a circle.') as tracker:

self.wait_until_bookmark("circle")

self.play(Create(Circle()), run_time=tracker.time_until_bookmark("circle", limit=1))

`

This is the recommended approach for any video with narration. The manual ffmpeg muxing workflow above is still useful for adding background music or post-production audio mixing.