Whisper.cpp

whisper.cpp ports OpenAI's Whisper speech recognition model to plain C/C++ with no external dependencies, a project from Georgi Gerganov built on the same ggml tensor library that later powered llama.cpp. It transcribes and translates audio in the 99 languages Whisper supports while running comfortably on hardware the original PyTorch implementation cannot: phones, Raspberry Pis, and browsers via WebAssembly, alongside macOS, Linux, Windows, FreeBSD, iOS, and Android. Performance comes from mixed F16/F32 precision, integer quantization formats such as Q5_0, zero memory allocations at runtime, and a long list of acceleration paths including ARM NEON, Metal, and Core ML on Apple silicon, AVX on x86, and CUDA, ROCm, Vulkan, and OpenVINO elsewhere. The tooling adds word-level timestamps, voice activity detection, and even karaoke-style subtitle video output. MIT licensed and widely embedded, it is the standard route to shipping offline Whisper transcription inside desktop and mobile applications where a Python runtime is impractical.