Term
whisper.cpp
whisper.cpp is an open-source C++ port of OpenAI's Whisper speech recognition — a compact native binary for local transcription on CPU, CUDA, Metal or Vulkan, with no Python dependency.
whisper.cpp — explained in more detail
whisper.cpp is the modern C++ inference implementation of OpenAI’s Whisper model, started in 2022 by Georgi Gerganov — the same developer who launched the parallel local-LLM movement with llama.cpp. Both projects share the ggml tensor library as their backend. Licensed under MIT, repository: ggerganov/whisper.cpp. The library has no Python dependency and compiles to a lean binary that runs on almost any system.
Example / In practice
whisper.cpp ships with several executables: main for file transcription, server as an HTTP endpoint for inference requests, stream for live streaming from a microphone. Models come in the ggml-<size>.bin format (with quantised variants such as q5_0, q5_1, q8_0) and are fetched via the included download-ggml-model.sh script. Supported backends include CPU with AVX/AVX2/AVX-512, CUDA, Metal on Apple Silicon, Vulkan, OpenCL and CoreML through a separate conversion step. Typical use cases are dictation tools, voice input in CLIs, offline subtitling and inference on edge devices without cloud access.
How it differs from related terms
Whisper refers to the OpenAI model itself; whisper.cpp is only one of several runtimes for it — alongside the official Python reference implementation and faster wrappers like faster-whisper (CTranslate2). Trade-offs: the first install compiles locally and needs a compiler toolchain; models have to be picked and pulled explicitly, with no automatic updates.
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