# 使用 Homebrew, dnf, Nix, pacman, apk, scoop 安装 whisper-cpp

查看 whisper-cpp 的安装路径、可执行文件、元数据以及面向 AI 代理工作流的安全说明。

## 安装

```sh
sudo av install brew:whisper-cpp
```

其他安装命令:

### macOS

- Homebrew (100%):

```sh
brew install whisper-cpp
```

  证据: local Homebrew formula metadata

### Linux

- dnf (92%):

```sh
sudo dnf install whisper-cpp
```

  证据: Fedora Rawhide package metadata: whisper-cpp from https://dl.fedoraproject.org/pub/fedora/linux/development/rawhide/Everything/x86_64/os/repodata/07190dc5ae9f35ae73866675fed6d95fe6e8d9fe22c9d7cdf85862cb2ed24a4c-primary.xml.zst

- Nix (92%):

```sh
nix profile install nixpkgs#whisper-cpp
```

  证据: nixpkgs package indexes: pkgs/by-name/wh/whisper-cpp/package.nix from https://api.github.com/repos/NixOS/nixpkgs/git/trees/master?recursive=1

- pacman (92%):

```sh
sudo pacman -S whisper-cpp
```

  证据: Arch Linux sync databases: whisper-cpp from https://geo.mirror.pkgbuild.com/extra/os/x86_64/extra.db.tar.gz

- apk (92%):

```sh
sudo apk add whisper-server
```

  证据: Alpine Linux edge package indexes: whisper-server from https://dl-cdn.alpinelinux.org/alpine/edge/testing/x86_64/APKINDEX.tar.gz

### Windows

- Scoop (92%):

```sh
scoop install main/whisper-cpp
```

  证据: Scoop official bucket manifest trees: bucket/whisper-cpp.json from https://api.github.com/repos/ScoopInstaller/Main/git/trees/master?recursive=1

## 软件包事实

- **软件包键:** brew:whisper-cpp
- **软件包管理器:** Homebrew
- **版本:** 1.9.1
- **来源摘要:** Port of OpenAI's Whisper model in C/C++
- **主页:** <https://github.com/ggml-org/whisper.cpp>
- **仓库:** <https://github.com/ggml-org/whisper.cpp>
- **最后更新:** 2026-06-19T09:02:25Z
- **已生成:** 2026-08-03T19:37:03+00:00

## 可执行文件

- parakeet-cli (别名)
- parakeet-quantize (别名)
- whisper-bench (别名)
- whisper-cli (别名)
- whisper-command (别名)
- whisper-lsp (别名)
- whisper-quantize (别名)
- whisper-server (别名)
- whisper-stream (别名)
- whisper-talk-llama (别名)
- whisper-vad-speech-segments (别名)

## 安装行为

- Bottle: 不可用

## 版本和新鲜度

- 页面生成时间: 2026-08-03
- 管理器版本: 1.9.1
## 项目历史与用法

whisper.cpp is Georgi Gerganov's C and C++ runtime for OpenAI's Whisper speech-recognition models. It appeared days after OpenAI released Whisper in September 2022 and turned the Python/PyTorch reference implementation into a small, portable, dependency-light local transcription tool.

### 项目历史

OpenAI introduced Whisper on September 21, 2022 as an automatic speech recognition system trained on 680,000 hours of multilingual and multitask supervised data. The original OpenAI repository positioned Whisper as a general-purpose model for multilingual transcription, translation to English, and language identification.

The whisper.cpp repository was created on September 25, 2022. Its README describes the project as a port of OpenAI's Whisper model in C/C++, with the high-level model implementation contained in `whisper.h` and `whisper.cpp` and the lower-level tensor work handled by ggml. That made Whisper usable in environments where Python, PyTorch, or CUDA were undesirable or unavailable.

The project grew with ggml-style model conversion, quantization, platform backends, examples, bindings, and command-line tools. Its model documentation explains that original OpenAI PyTorch models are converted to ggml format for loading from C/C++, while project discussions and release notes document features such as integer quantization, streaming, server usage, and embedded-device experiments.

### 采用历史

whisper.cpp became one of the canonical local-AI command-line packages because it made a large neural speech model feel like a normal Unix tool: download a converted model, run an executable, and transcribe local audio without a cloud service. The upstream GitHub repository reported more than 51,000 stars and more than 5,700 forks via GitHub's API on July 2, 2026.

Its adoption also matters historically because it helped establish the ggml pattern later associated with local inference projects: compact C/C++ runtimes, quantized model files, CPU-first portability, and optional acceleration paths. In package-manager culture, whisper.cpp is the package people reach for when they want OpenAI Whisper behavior in scripts, media pipelines, offline transcription jobs, and low-power devices.

### 使用方式

Typical usage is local speech-to-text: converting or downloading a ggml-format Whisper model, running `whisper-cli` or related tools against audio, and emitting transcripts or timestamps. The repository also ships examples and executables for benchmarking, streaming microphone input, running a local server, quantizing models, and integrating with other applications through a C API or bindings.

The package is especially useful when privacy, offline operation, repeatable batch processing, or hardware portability matter more than managed cloud transcription. Users choose model size and quantization level as the tradeoff knob between accuracy, memory footprint, and speed.

### 为什么软件包爱好者会关心

For package nerds, whisper.cpp is a landmark local-inference package: it compressed a research model into a buildable C/C++ artifact that could live comfortably in Homebrew, Linux distributions, Docker images, mobile apps, WebAssembly experiments, and single-purpose transcription workflows.

It also became a reference point for later local-AI ports. When people compare local speech runtimes, they often distinguish broad cross-platform portability in whisper.cpp from Apple-specific Core ML and Neural Engine approaches such as WhisperKit, or Python/GPU-oriented projects such as faster-whisper.

### 时间线

- 2022-09-21: OpenAI introduced Whisper and released model code and weights for multilingual speech recognition.
- 2022-09-25: The whisper.cpp GitHub repository was created.
- 2023: whisper.cpp discussions and releases documented integer quantization, streaming, and embedded-device experiments.
- 2026-07-02: GitHub API metadata showed the repository above 51,000 stars, reflecting broad adoption in the local-AI ecosystem.

### Related projects

- OpenAI Whisper is the upstream model and Python reference implementation.
- ggml is the low-level machine-learning library and model-format ecosystem used by whisper.cpp.
- WhisperKit targets Apple Silicon with Swift and Core ML rather than whisper.cpp's cross-platform C/C++ approach.

### 来源

- OpenAI Whisper announcement: https://openai.com/index/whisper/
- OpenAI Whisper repository: https://github.com/openai/whisper
- whisper.cpp GitHub API metadata: https://api.github.com/repos/ggml-org/whisper.cpp
- whisper.cpp model documentation: https://github.com/ggml-org/whisper.cpp/blob/master/models/README.md
- whisper.cpp repository and README: https://github.com/ggml-org/whisper.cpp
- whisper.cpp v1.4.0 quantization discussion: https://github.com/ggml-org/whisper.cpp/discussions/838


## 安全说明

broad file, network, media, or database tool signal.

- **Geiger 风险:** blue / 中
- broad file, network, media, or database tool signal

## 其他软件包管理器记录

- Nix - whisper-cpp: normalized package name match | nixpkgs package indexes: pkgs/by-name/wh/whisper-cpp/package.nix from https://api.github.com/repos/NixOS/nixpkgs/git/trees/master?recursive=1
- apk - whisper-server - 1.9.1-r0: normalized package name match | Alpine Linux edge package indexes: whisper-server from https://dl-cdn.alpinelinux.org/alpine/edge/testing/x86_64/APKINDEX.tar.gz | whisper.cpp server | https://github.com/ggerganov/whisper.cpp
- apk - whisper-server-openrc - 1.9.1-r0: normalized package name match | Alpine Linux edge package indexes: whisper-server-openrc from https://dl-cdn.alpinelinux.org/alpine/edge/testing/x86_64/APKINDEX.tar.gz | whisper.cpp server (OpenRC init scripts) | https://github.com/ggerganov/whisper.cpp
- apk - whisper.cpp - 1.9.1-r0: normalized package name match | Alpine Linux edge package indexes: whisper.cpp from https://dl-cdn.alpinelinux.org/alpine/edge/testing/x86_64/APKINDEX.tar.gz | Port of OpenAI's Whisper model in C/C++ | https://github.com/ggerganov/whisper.cpp
- apk - whisper.cpp-dev - 1.9.1-r0: normalized package name match | Alpine Linux edge package indexes: whisper.cpp-dev from https://dl-cdn.alpinelinux.org/alpine/edge/testing/x86_64/APKINDEX.tar.gz | Port of OpenAI's Whisper model in C/C++ (development files) | https://github.com/ggerganov/whisper.cpp
- apk - whisper.cpp-libs - 1.9.1-r0: normalized package name match | Alpine Linux edge package indexes: whisper.cpp-libs from https://dl-cdn.alpinelinux.org/alpine/edge/testing/x86_64/APKINDEX.tar.gz | Port of OpenAI's Whisper model in C/C++ | https://github.com/ggerganov/whisper.cpp
- apk - whisper.cpp-vulkan - 1.9.1-r0: normalized package name match | Alpine Linux edge package indexes: whisper.cpp-vulkan from https://dl-cdn.alpinelinux.org/alpine/edge/testing/x86_64/APKINDEX.tar.gz | Port of OpenAI's Whisper model in C/C++ (Vulkan backend) | https://github.com/ggerganov/whisper.cpp
- dnf - whisper-cpp - 1.8.3-4.fc45: normalized package name match | Fedora Rawhide package metadata: whisper-cpp from https://dl.fedoraproject.org/pub/fedora/linux/development/rawhide/Everything/x86_64/os/repodata/07190dc5ae9f35ae73866675fed6d95fe6e8d9fe22c9d7cdf85862cb2ed24a4c-primary.xml.zst | Port of OpenAI's Whisper model in C/C++ | https://github.com/ggerganov/whisper.cpp
- dnf - whisper-cpp-devel - 1.8.3-4.fc45: normalized package name match | Fedora Rawhide package metadata: whisper-cpp-devel from https://dl.fedoraproject.org/pub/fedora/linux/development/rawhide/Everything/x86_64/os/repodata/07190dc5ae9f35ae73866675fed6d95fe6e8d9fe22c9d7cdf85862cb2ed24a4c-primary.xml.zst | Libraries and headers for whisper-cpp | https://github.com/ggerganov/whisper.cpp
- pacman - whisper-cpp - 1.9.1-1: normalized package name match | Arch Linux sync databases: whisper-cpp from https://geo.mirror.pkgbuild.com/extra/os/x86_64/extra.db.tar.gz | Port of OpenAI's Whisper model in C/C++ | https://github.com/ggerganov/whisper.cpp
- Scoop - main/whisper-cpp: normalized package name match | Scoop official bucket manifest trees: bucket/whisper-cpp.json from https://api.github.com/repos/ScoopInstaller/Main/git/trees/master?recursive=1


## Combined YAML source

View the package source record on GitHub. [combined/whisper-cpp.yml](https://github.com/mxcl/pkgdb/blob/main/combined/whisper-cpp.yml)


## 来源

- pkg.so package database
- Geiger risk classifier
- curated package history
- pkgdb category and tag curation
- external package-manager database matches
- cross-ecosystem install command graph