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InfiniteTalk

Audio-driven model that makes unlimited-length talking video from an image or re-dubs an existing video.

Unlimited-length talking video

Turn an image plus audio into long talking video, or re-dub a clip with matching body motion.

Free forever · open source · Apache-2.0
✓ Needs IT✓ Browser-based✓ Real-time collaboration
6.4
ZEKAI
Long talking video, DIY
Free & open source · Video
Ease of setup3
Usefulness7
Maintenance7
Community8.5
★ 8,389
GITHUB
May 2026
UPDATED
Apache-2.0
LICENSE
🛠 Don't want to self-host? We can set it up →
⚡ Quick answer

InfiniteTalk is a sparse-frame video dubbing model from MeiGen-AI that generates talking video of unlimited length from an image or an input video. It suits developers and researchers with a strong NVIDIA GPU.

Runs on
Cross-platform
Hosting
Self-host
Languages
Python
License
Apache-2.0

What it is

Given audio, it synchronises lips and also head posture, body movement and expressions, in image-to-video or video-to-video mode. The README builds on the Wan2.1 480P base model and offers a Gradio demo, ComfyUI branch and low-VRAM mode.

Who it's for

Suits technical users who want long avatar clips without per-minute fees. It does not suit anyone expecting a studio with voices, templates or a script editor, because it only consumes audio you provide.

Key features

Image-to-video

Animate one reference image from an audio clip.

Video-to-video dubbing

Re-dub an input video, syncing head, body and expressions.

Unlimited length

The README describes unlimited-length generation.

Low-VRAM mode

Set num_persistent_param_in_dit to 0 for very low VRAM.

Multi-GPU inference

Run with torchrun across several GPUs.

Gradio and ComfyUI

A Gradio demo and a ComfyUI branch are provided.

How to start

Up and running in 3 steps

1
Create a Python environment and install PyTorch 2.4.1 (CUDA 12.1), xformers, flash-attn and requirements.txt.
2
Download the Wan2.1-I2V-14B-480P base model, the Chinese wav2vec2 model and the InfiniteTalk weights with huggingface-cli.
3
Run generate_infinitetalk.py with your image or video and audio, adding the low-VRAM flag if your GPU is small.
Real talk

Our honest verdict

What's great

  • Apache-2.0 code and weights, with the README granting freedom to use generated content.
  • Dubs both lips and body motion, not only the mouth.
  • Documents low-VRAM and multi-GPU modes for different hardware.
  • Active repo with ComfyUI and Wan2GP community integrations.

Where it falls short

  • You need an NVIDIA GPU, PyTorch 2.4.1 with CUDA 12.1, xformers and flash-attn compiled correctly.
  • Base Wan2.1-I2V-14B weights and extra audio models must be downloaded separately; they are large.
  • No voices, editor or text-to-speech: you supply the audio.
  • Low-VRAM mode trades away speed.
Cost

Pricing & license

Free under Apache-2.0. The README lists no paid or hosted plan, so the only cost is the GPU hardware or rented GPU time you run it on.

Paid work

Open remote AI-training roles

767 open remote AI-training roles, updated November 14, 2026; most pay $20–$175 an hour. Zekai lists them free; the application goes to the employer’s platform.

See all open roles →
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Alternatives

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Questions

FAQ

Can I use InfiniteTalk commercially?

The README says the models are under Apache-2.0 and that you keep rights to your generated content, subject to the licence terms.

How much VRAM does it need?

The README does not give one number; it documents a very-low-VRAM mode and multi-GPU runs, and community Wan2GP support targets low-VRAM cards.

Does it make the voice too?

No. It takes audio you supply and animates the video to match it.

Radar

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