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ComfyUI-Ovi

Integrates Character.AI's Ovi joint video and audio generation engine into node-based ComfyUI workflows.

Joint audio-video generation inside ComfyUI

Generate synchronized video frames and 16 kHz audio tracks using precision-controlled Ovi nodes.

Free forever · source-available · Licence not stated in the repository
✓ Light setup✓ Browser-based✓ Real-time collaboration
4.9
ZEKAI
Essential ComfyUI video node.
Free & open source · Writing
Ease of setup4
Usefulness7
Maintenance3.5
Community5
★ 125
GITHUB
Oct 2025
UPDATED
Licence not stated in the repository
LICENSE
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⚡ Quick answer

ComfyUI-Ovi brings Character.AI's dual video and audio generator directly into ComfyUI pipelines. Multimedia localizers and video content creators can generate synchronized speech and video prompts directly from custom workflow nodes. It suits team members building automated video translation or AI dubbing pipelines within ComfyUI.

Runs on
Cross-platform
Hosting
Desktop
Languages
Python
License
Licence not stated in the repository

What it is

This node package integrates Character.AI's 11B Ovi model into ComfyUI to output synchronized video frames and 16 kHz audio latents. It provides dedicated nodes for engine loading, precision switching, attention backend selection, and latent decoding. The tool automatically fetches core assets while allowing shared use of existing Wan 2.2 VAE and UMT5 text encoders.

Who it's for

It suits multimedia localizers, AI video creators, and technical translators building automated video dubbing or generation workflows in ComfyUI. It is not designed for non-technical users who lack an existing ComfyUI environment or high-end NVIDIA hardware. If you do not have at least 16 GB of VRAM, this tool will not run.

Key features

Self-bootstrapping model loader

Downloads required MMAudio assets and Ovi fusion weights directly into your ComfyUI directories.

FP8 and BF16 precision toggles

Lets you switch between full precision and a 16-24 GB VRAM mode directly from node dropdowns.

Attention backend selector

Allows runtime switching between FlashAttention, SDPA, Sage, and native attention drivers.

Component reuse support

Connects to pre-installed Wan 2.2 VAE and UMT5 text encoders without duplicating model files on disk.

Per-node multi-GPU targeting

Detects available GPUs and lets you assign specific workflow nodes to target graphics cards.

How to start

Up and running in 3 steps

1
Clone the repository into your ComfyUI custom_nodes folder and install requirements.txt.
2
Ensure you have PyTorch 2.4+ and CUDA 12.x installed, then restart ComfyUI.
3
Add the Ovi Engine Loader node to your workflow to fetch weights and begin generation.
Real talk

Our honest verdict

What's great

  • Generates synchronized video latents and 16 kHz audio in a single pass
  • Reuses existing Wan 2.2 VAE and UMT5 text encoder files to save storage space
  • Supports runtime switching between FP8 and BF16 precision modes
  • Includes per-node device selection for multi-GPU hardware setups

Where it falls short

  • Requires a minimum of 16 GB VRAM and a modern CUDA 12.x stack to execute
  • No explicit open-source license provided in the repository metadata
  • High VRAM retention after generation runs requires manual model unloading
  • Requires setting up and maintaining a working ComfyUI environment
Cost

Pricing & license

The custom nodes are free to download and use. The primary financial cost comes from operating high-end GPU infrastructure capable of processing 11B models.

Paid work

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870 open remote AI-training roles, updated November 14, 2026; most pay $20–$170 an hour. Zekai lists them free; the application goes to the employer’s platform.

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Questions

FAQ

What VRAM is required to run ComfyUI-Ovi?

You need 16 to 24 GB of VRAM using FP8 precision with CPU offload, or 32 GB+ VRAM for native BF16 mode.

Does ComfyUI-Ovi generate audio alongside video?

Yes, it produces synchronized video frames together with 16 kHz audio latents.

Can I use existing Wan 2.2 model files?

Yes, the Ovi Wan Component Loader node lets you point to your existing Wan 2.2 VAE and UMT5 text encoders.

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