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This tutorial covers a Windows installation of FaceFusion 3.9.0 with CUDA GPU support, then compares its Alpha 256 face swap model with InSwapper. The speaker describes Alpha 256 as producing sharper facial features and more skin detail without an enhancer. Those conclusions come from the examples presented, rather than a general benchmark.
For the local AI setup, the description recommends 4 GB or more of VRAM; the narration calls 4 GB a minimum. Other listed prerequisites are CUDA Toolkit 11.8 to 12.8, Python 3.11.0, FFmpeg, Visual Studio and Git for Windows. The walkthrough clones the repository, creates and activates a Python virtual environment, upgrades setuptools and pip, and installs PyTorch.
The dependency steps include editing SciPy, replacing ONNX Runtime with ONNX Runtime GPU, and reinstalling NumPy. The speaker notes that the ONNX Runtime GPU version depends on the CUDA and PyTorch setup, but the transcript does not state the exact replacement versions. These steps therefore do not provide a complete text-only installation recipe.
On the first launch, FaceFusion downloads models and displays a local URL to open in a browser. The tutorial also shows how to save a run.bat launcher for later use. It ends with another face swap comparison, where the speaker calls the InSwapper result blurry and favors Alpha 256 for detail.
