Choose the output first
MuseTalk edits a face region, Quark LiveAvatar generates audio-driven video, and Audio2Face-3D produces facial animation for your renderer. Each solves a different part of a live experience.
Compare the projects
| Detail | MuseTalk | Quark LiveAvatar | NVIDIA |
|---|---|---|---|
| Model | MuseTalk 1.5 | LiveAvatar 1.1 | Audio2Face-3D |
| Full avatar usage rate | Your compute | Your compute | Your compute |
| Full billing basis | Your compute + conversation stack | Your compute + conversation stack | Your compute + conversation stack |
| Video-only usage rate | Your compute | Your compute | Your compute |
| Video billing basis | Your GPU costs | Your GPU costs | Your compute costs |
| Full response timing | Your pipeline · Full response depends on your stack | Your pipeline · Full response depends on your stack | Your pipeline · Full response depends on your stack |
| Video timing | 30+ FPS · Throughput on NVIDIA Tesla V100 | 45 FPS · Multi-card H800, 4-step sampling | Not listed · No comparable timing in cited repository |
| Output resolution | 256 × 256 face · Edited face region, not the full output video | Configurable · Depends on inference settings and GPU memory | Your renderer · 3D animation output, resolution set by your application |
| FPS | 30+ FPS · Inference throughput on Tesla V100 after avatar preparation | 45 FPS · Multi-card H800, four-step sampling | Your renderer · 3D facial animation, not a hosted video stream |
| Custom motions | Lip sync only · Edits an existing face region; signature controls not verified | Not verified · Audio-driven diffusion; custom signature controls not established | App / rig controlled · Facial animation output; character actions belong to your renderer |
| Moderation control | App controlled · Your app sets filters; model and license restrictions still apply | App controlled · Your app sets filters; model and license restrictions still apply | App controlled · Your app sets filters; model and license restrictions still apply |
| Deployment | Self-hosted | Self-hosted | Self-hosted |
Account for deployment work
- Pin code and weight versions, and review their licenses.
- Measure avatar preparation separately from warm inference.
- Record the GPU, precision, sampling settings, and output dimensions.
- Include encoding, transport, conversation, and idle compute in cost.
- Test the number of concurrent sessions you need.
Interpret published FPS
GPU throughput establishes a processing result under the published conditions. Delivered frame rate and voice-to-voice latency also depend on your application pipeline.