FaceFusion Installation Problems? You're Not Alone.

Pinokio "No Such File or Directory" (ENOENT)

This happens when the installation path is too deep, a previous install was interrupted, or your system doesn't have enough virtual memory to extract large model files.

1. Delete leftover files

   Navigate to your Pinokio folder and delete the facefusion-pinokio.git directory and the facefusion conda environment folder.

2. Move Pinokio to a shorter path

   Reinstall Pinokio to a root-level directory like C:\Pinokio instead of deeply nested folders. Avoid spaces and special characters in the path.

3. Increase virtual memory

   Open System Properties → Advanced → Performance Settings → Virtual Memory. Set custom size: Initial 32768 MB, Maximum 65536 MB. Restart your computer.

Mac M1/M2/M4 — Installation Stalls or CoreML Crash

Pinokio needs Apple's Command Line Tools to compile native dependencies. Without them, the installation silently hangs.

After macOS Tahoe updates, the CoreML framework version changes and breaks cached ONNX models.

1. Install Command Line Tools

   Open Terminal and run: xcode-select --install — wait for it to complete (~10 minutes), then restart Pinokio.

2. Fix permissions

   Run: sudo xattr -r -d com.apple.quarantine /Applications/Pinokio.app

3. Delete model cache & upgrade runtime

   Delete cached .onnx files from your FaceFusion environment. Then run: pip install --upgrade onnxruntime-silicon. If the error persists, switch Execution Provider to CPU temporarily.

Linux — Pinokio Won't Launch FaceFusion

Pinokio relies on Electron, which has complex system library dependencies that vary across Linux distros. Conflicts with GTK/WebKit versions frequently prevent the app from running.

Skip Pinokio entirely and use the official command-line installation — it's cleaner and more reliable on Linux:

RunPod / Vast.ai — Port 7860 "Not Ready"

Three reasons: the port isn't exposed in your pod settings, FaceFusion binds to localhost instead of the public interface, or the models are still downloading (this takes 5-10 minutes on first launch).

1. Expose port 7860

   When creating your pod, add 7860 to the Exposed HTTP Ports field in the pod configuration.

2. Bind to 0.0.0.0

   Launch FaceFusion with: python facefusion.py run --host 0.0.0.0 — this allows external access.

3. Wait 5-10 minutes

   On first launch, FaceFusion downloads hundreds of MB of AI models. Check the terminal logs — if you see download progress, it's working. Just wait.

AMD GPU — No Acceleration on Windows

AMD's ROCm acceleration framework only works on Linux. Windows AMD users default to CPU processing unless they explicitly enable DirectML.

1. Windows: Use DirectML

   Install with: python install.py --onnxruntime directml — DirectML is slower than CUDA (NVIDIA) but significantly faster than CPU-only processing.

2. Linux: Use ROCm

   Install the AMD GPU driver stack, then run: python install.py --onnxruntime rocm — this gives you full GPU acceleration on supported AMD cards.

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