53.5k stars · MIT · v1.9.3 (2026-08-20)
Whisper in C++ — fast on plain hardware and excellent on Apple Silicon, with no Python and no CUDA.
▶Repo detailsthe review · specs · pros & cons · install
What it is
OpenAI's Whisper model rewritten in C++ so it runs fast on ordinary hardware. It is unusually fast on Apple computers. It is one program and one model file. No Python setup and no CUDA (special graphics-card software).
Why it matters
In Edition 2 I recommended whisperX and said clearly that it wants a GPU. Two weeks later it is probably still not installed. This is the version that runs on your Mac tonight. The transcript is the most reusable thing your channel produces. It is the caption file, which raises watch time and is the minimum for accessibility. It is the source text for the Russian subtitles that Edition 4 argued for. And published on your Astro website as an article, it is the only way a YouTube video ever earns you Google traffic. Record once, publish in three places.
- No Python, no CUDA, no tangle of dependencies. Build it once and forget it.
- Fast enough on a Mac that transcribing becomes normal, not an event.
- MIT licence, and released steadily. Version 1.9.3 came out on 20 August.
- It overlaps with whisperX (Ed. 2 #4). whisperX is still better at word-level timing and at telling speakers apart. Pick one. Do not keep both.
- Russian accuracy is clearly lower than English. A human has to check it before you publish anything in Russian.
- The repository moved from
ggerganov/whisper.cpptoggml-org/whisper.cpp. Older guides point at the old address.
The same text also feeds textstat (Ed.
git clone https://github.com/ggml-org/whisper.cpp cd whisper.cpp cmake -B build && cmake --build build -j --config Release sh ./models/download-ggml-model.sh large-v3-turbo ./build/bin/whisper-cli -m models/ggml-large-v3-turbo.bin -f lesson.wav -osrt -l ru
