Audio
whisper.cpp
Port of OpenAI's Whisper model in C/C++
★ 54.1k starsMIT
View guide →Fast local speech-to-text across 16+ model families, powered by ggml.
transcribe.cpp is an open-source audio project by handy-computer (handy-computer/transcribe.cpp on GitHub). It has 1,982 GitHub stars and 112 forks, is released under the MIT license, and was last updated on GitHub on 4 October 2026.
Choose one of the 16+ supported speech model families and grab its weights.
Compile the C++ code or use a prebuilt binary for your platform.
Feed it a file or a live stream and get text back in seconds.
Pipe transcripts into notes, subtitles, or your own pipeline.
Runs ggml speech-to-text inference across a wide range of model families.
Audio never leaves your machine; no cloud account or key needed.
Native performance makes transcription fast even on modest CPUs.
Compact model files that are easy to download and swap.
Permissive license that suits open and commercial projects alike.
Designed for both file transcription and low-latency streams.
Download the source and move into the project folder.
git clone https://github.com/handy-computer/transcribe.cpp.git
cd transcribe.cppEvery project documents its own setup; start with install requirements.
cat README.md | head -60Follow the project's launch command — Docker, pip, npm, or a binary release.
# see README for the exact launch commandIt is an open-source project at handy-computer/transcribe.cpp with 112 forks. Check the repo's contributors and recent commits to see how active maintenance is.
MIT licensed — commercial use allowed with attribution.
It supports 16+ speech-to-text model families via ggml/GGUF weights; check the README for the current list.
A GPU helps, but ggml is built for CPU efficiency, so many models run fine on a regular laptop.
The headline difference is breadth: it aims to cover many model families, not just one.
Port of OpenAI's Whisper model in C/C++
Faster Whisper transcription with CTranslate2
Speech-to-text, text-to-speech, speaker diarization, speech enhancement, source separation, and VAD using next-gen Kaldi with onnxruntime without Internet co…
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The most-starred other Audio projects in the LibreAI catalogue — the realistic shortlist if transcribe.cpp is not the right fit.
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Robust Speech Recognition via Large-Scale Weak Supervision
1 min voice data can also be used to train a good TTS model! (few shot voice cloning)
Clone a voice from 5 seconds of audio and generate arbitrary speech in real time
Port of OpenAI's Whisper model in C/C++
Free and open — grab the source, star the repo, and start creating.