CrazyTalk vs LivePortrait
CrazyTalk
reallusion.comLivePortrait
liveportrait.github.ioSide by side
| Figure | CrazyTalk | LivePortrait |
|---|---|---|
| Price from | — | — |
| Free plan | — | — |
| Free trial | Yes | — |
| Open source | — | — |
| Web | — | Yes |
| Windows | Yes | Yes |
| macOS | Yes | Yes |
| Linux | — | Yes |
| Self-hosted | — | Yes |
| Plans published | 3 | 0 |
| Spec score · Photo Animation Software | 8.0 (#6) | 7.7 (#12) |
| Purpose | CrazyTalk uses voice and text to animate facial images into talking characters. | LivePortrait animates a portrait from a still image using facial expressions and head pose from a driving video, audio, text, or generated motion. |
| Support | Reallusion offers online video tutorials and manuals and invites users to contact support for help. | The maintainers invite bug reports and suggestions through repository issues and pull requests and provide a contact email for project inquiries. |
Plans
In their own words
CrazyTalk
CrazyTalk has no write-up on Specifiction yet; its figures are above.
LivePortrait
LivePortrait creates portrait video from a single image, using motion from video, audio, text, or generation. It also supports editing portrait video using a source video and a driving video. Stitching and eye and lip retargeting controls provide ways to adjust animation. The project supplies inference code, pretrained models, and a Gradio interface for local use, as well as a demo hosted on Hugging Face Spaces. Its PyTorch implementation is released under the MIT License, and the project reports generation speed of 12.8 ms on an RTX 4090 GPU with PyTorch. Human-mode instructions cover Linux, Windows, and Apple Silicon macOS; Intel macOS is untested. Animal models can animate cats, dogs, and pandas using human-driven motion, but animal mode is tested only on Linux and Windows with an NVIDIA GPU and is unsupported on macOS. Local setup requires git, conda, FFmpeg, Python 3.10, and downloaded pretrained weights. Commercial users must replace the included InsightFace detection models. Maintainers warn of possible deepfake misuse and visual artifacts.