Transcribe audio files locally with Whisper CLI, a command-line tool that needs no API key. Produce text or translated subtitles, and choose smaller or larger models to balance processing speed and accuracy.
Local speech-to-text with the Whisper CLI (no API key).
openai-whisper transcribes audio files locally and saves the results as text. It uses the whisper command-line tool, where you can specify the output format, destination folder, and model. The supplied examples show how to turn an MP3 into text and translate an M4A into subtitles in SRT format. Smaller models suit tasks where speed matters more, while larger models suit tasks where accuracy matters more.
Use it when you want a written version of a recording to read back later, or when you need translated subtitles from an audio file. It also suits people who want to process audio locally without preparing an API key. You can choose the model and output format to match the task.
medium model and save it as text.”You need to install whisper. No API key is required, but models are downloaded to ~/.cache/whisper on the first run. In the environment described in the material, the default model is turbo.
This overview was written by AI (OpenAI Codex) from the public SKILL.md. Check the original below for the exact behavior.
AI rated this skill on four points using only the contents of its SKILL.md. Stars and popularity are not taken into account.
The total counts each point as A = 25, B = 15, C = 5. Rated by AI (OpenAI Codex) as of Oct 19, 2026. Treat it as a guide and read the original before installing.
Review the instructions the agent will receive before you install.
Use whisper to transcribe audio locally.
Quick start
whisper /path/audio.mp3 --model medium --output_format txt --output_dir .whisper /path/audio.m4a --task translate --output_format srtNotes
~/.cache/whisper on first run.--model defaults to turbo on this install.No reviews yet. Tell others what you thought.
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