> For the complete documentation index, see [llms.txt](https://docs.mozilla.ai/llms.txt). Markdown versions of documentation pages are available by appending `.md` to page URLs; this page is available as [Markdown](https://docs.mozilla.ai/llamafile/whisperfile/gpu.md). # Using 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 ``` --- # Agent Instructions This documentation is published with GitBook. GitBook is the documentation platform designed so that both humans and AI agents can read, navigate, and reason over technical content effectively. Learn more at gitbook.com. ## Querying This Documentation If you need additional information that is not directly available in this page, you can query the documentation by asking a question. Perform an HTTP GET request on the following URL with the `ask` and `goal` query parameters: ``` GET https://docs.mozilla.ai/llamafile/whisperfile/gpu.md?ask=&goal= ``` `ask` is the immediate question: it should be specific, self-contained, and written in natural language. `goal` is what the user is ultimately trying to achieve, the reason they need the answer. Sharing it helps GitBook give you a better, more relevant answer. A goal is most helpful when it describes the outcome the user wants rather than restating the question. For example, with `ask=how do I create an API token`, a goal like `automate deployments from our CI pipeline` lets GitBook tailor the answer to that use case. The response will contain a direct answer to the question and relevant excerpts and sources from the documentation. Use this mechanism when the answer is not explicitly present in the current page, you need clarification or additional context, or you want to retrieve related documentation sections.