One photo → talking head video with natural head movement, blinks, and mouth articulation. MIT license. No video sample required — just a single still image and an audio clip. The most accessible local avatar creation tool.
This model requires a specialized High-VRAM environment. Ensure you have the latest CUDA Drivers or Metal Framework installed.
Minimum VRAM: 8GB VRAM Recommended
Origins & History
The SadTalker model by OpenTalker is a 300M parameter architecture optimized for audio tasks. It requires approximately 6GB of VRAM to comfortably run locally using a FP16 quantization. Extending the context window up to 0 tokens will dynamically allocate further VRAM, meaning high-bandwidth memory hardware is strictly advised.
Pros
Full privacy and offline inference capabilities
Highly capable 300M parameter structure
Supports impressive 0 token context window
Cons
Requires 6GB+ VRAM minimum
Local inference speed depends entirely on memory bandwidth (GB/s)
Architect's Runtime Strategy
For running SadTalker at maximum tokens-per-second, we recommend using LM Studio or Ollama with a GGUF quantization (Q4_K_M or Q6_K). If you are multi-GPU, use vLLM to distribute the layers across your VRAM pool for optimal throughput.
Common Questions
What hardware do I need to run SadTalker?
You will need a GPU with at least 8GB of VRAM to run the FP16 quantized version smoothly with a moderate context window.
How do I install SadTalker locally?
The simplest method is utilizing Ollama by executing 'ollama run sadtalker' directly in your command line. Alternatively, you can search for the model via LM Studio's interface.