whisper.cpp

Fast C/C++ port of OpenAI's Whisper speech-to-text model, runs locally on CPU or GPU.

Stars: 54.9k
Forks: 6.3k
Licence: MIT
Language: C++
Last update: 7 days ago
Type: Library

What it is

whisper.cpp is a C/C++ implementation of OpenAI's Whisper automatic speech recognition model, which turns spoken audio into text. It is written to run with no external dependencies and can work offline on the device. People use it to add transcription to their own apps or to transcribe audio on their own machine without sending it to a cloud service.

Transcribe a WAV file from the command line with whisper-cli
Convert an MP3 to 16-bit 16 kHz WAV with ffmpeg and transcribe it offline
Quantize a model to a smaller format such as q5_0 to reduce memory and disk use
Build an offline voice assistant using the command example described in the README

Great for

Developers who want to embed offline speech-to-text in a C, C++, or other native app
People on Apple Silicon who want GPU or Neural Engine accelerated transcription
Users who need to transcribe audio privately on their own computer
Projects targeting constrained or embedded hardware such as Raspberry Pi

Not ideal for

Non-technical users who want a ready-made app with a graphical interface, since the README centers on command-line usage and building from source
Anyone who needs audio in formats other than 16-bit WAV without first converting it, because the CLI example only accepts 16-bit WAV
Teams needing a hosted transcription API, since this is a local inference library rather than a service

Step-by-step guide: how to use whisper.cppInstall, first run, examples, tips and FAQs

whisper.cpp alternatives Whisper vs whisper.cpp Handy vs whisper.cpp Meetily vs whisper.cpp faster-whisper vs whisper.cpp Buzz vs whisper.cpp Nano-vLLM vs whisper.cpp OpenWhispr vs whisper.cpp RealtimeSTT vs whisper.cpp

How to get it

1
Clone and build from source
You'll need: git · CMake · A C/C++ compiler · ffmpeg (optional, for converting audio to WAV)
Clone the repository
git clone https://github.com/ggml-org/whisper.cpp.git
Download the base.en model
sh ./models/download-ggml-model.sh base.en
Configure the build with CMake
cmake -B build
Build the project
cmake --build build -j --config Release
2
Run it
- Clone the repository and move into the whisper.cpp folder
- Download the base.en model with the provided script
- Build with CMake as shown in the README
- Run ./build/bin/whisper-cli -f samples/jfk.wav to transcribe the sample file
3
Get the most out of it
- Use ./build/bin/whisper-cli -h to see detailed usage options
- Quantize models with the quantize tool to save memory and disk space
- Enable Core ML on Apple Silicon for faster encoder inference, as described in the Core ML section
- Use the -DGGML_BLAS=1 build option on POWER systems with a BLAS package installed
- Convert input audio to 16 kHz mono 16-bit WAV with ffmpeg before transcribing

Downloads

Source code (.zip)master branch · straight from GitHub Release v1.9.5Release notes and source

Strengths

No external dependencies in the core implementation, which eases integration into many platforms
Supports a wide range of hardware including CPU, Metal, CUDA-based NVIDIA GPUs, Vulkan, and Core ML
Includes quantization options that reduce model size and memory use

Trade-offs

Command-line example only accepts 16-bit WAV, so audio often needs conversion first
Building and choosing models requires comfort with CMake and the terminal
Core ML and some accelerator paths require extra setup and platform-specific steps

How it compares

Project	Stars	Type	Level	Updated	Best for
whisper.cpp (this)	54.9k	Library	intermediate	7 days ago	Developers who want to embed offline speech-to-text in a C, C++, or other native app
faster-whisper	26.4k	Library	intermediate	5 days ago	Python developers who need to add speech-to-text to an application
whisper	112k	AI model / agent	intermediate	2 months ago	Developers who want to add transcription of audio files to a Python project
openwhispr	10.5k	App	beginner	4 days ago	People who want dictation in any app without sending audio to a cloud service
nano-vllm	16.3k	Library	intermediate	6 months ago	Developers who want to understand how LLM inference engines work internally
FunASR	20.9k	Library	intermediate	4 days ago	Developers who want to transcribe audio in Python with a pretrained model

Stats synced from GitHub. The assessment above was drafted with AI from the project's README on 2026-10-29 and may miss recent changes — check the README before relying on a command. MIT licence: free to use, modify and distribute, including commercially, as long as you keep the copyright notice.