Using Whisperfile with GPUs

GPU acceleration is most beneficial for the medium and large models. The tiny model is already fast on CPU, so the speedup there is minimal.

Pass --gpu auto to let whisperfile detect and use the best available GPU on your system. If no supported GPU is found, it falls back to CPU silently:

bash

whisperfile -m models/ggml-medium.en.bin -f audio.wav --gpu auto

You can also target a specific backend:

--gpu apple — Apple Metal (macOS, works on Apple Silicon and AMD GPUs)
--gpu nvidia — NVIDIA CUDA (requires CUDA Toolkit to be installed)
--gpu amd — AMD ROCm (requires ROCm to be installed on Linux)

To disable GPU acceleration entirely:

bash

whisperfile -m models/ggml-medium.en.bin -f audio.wav --no-gpu

Troubleshooting

ggml_backend_load_best: search path does not exist warnings

These are benign. They appear when whisperfile searches for GPU backend libraries and doesn't find them — usually because no GPU is present or configured. Transcription will continue on CPU. To suppress them, redirect stderr:

bash

whisperfile -m models/ggml-medium.en.bin -f audio.wav 2>/dev/null