macOS
Homebrew Cask已验证 · 100%
brew install --cask vmlxlocal Homebrew cask metadata
安装
其他安装命令
概览
软件包摘要
Run local AI models on Apple Silicon
历史
项目历史与用法
vMLX is a local AI inference engine and macOS desktop application for Apple Silicon. It runs and serves language, vision, embedding, reranking, speech, and image models through OpenAI- and Anthropic-compatible APIs.
项目历史
vMLX was created by Jinho Jang/JANGQ AI as an Apple-Silicon inference and model-serving project. It developed into the engine behind a desktop MLX Studio experience, combining chat, model-session management, image generation, conversion tools, and API reference functions.
采用历史
vMLX is distributed both as a macOS desktop application and a Python package. Its compatibility with OpenAI and Anthropic client protocols lets existing SDKs and agent tools use locally hosted Apple-Silicon models by changing the endpoint rather than adopting a project-specific API.
使用方式
Desktop users download the macOS application, load local models, and manage chat or server sessions from the UI and menu bar. Command-line users install the Python package and invoke commands such as `vmlx serve`, `vmlx convert`, `vmlx info`, `vmlx doctor`, and `vmlx bench`. Existing clients can use the local HTTP endpoint with OpenAI- or Anthropic-compatible SDKs.
为什么软件包爱好者会关心
The project packages an unusually broad local-AI stack—desktop UI, Python inference engine, model conversion, quantization, API serving, and developer tools—around Apple's MLX ecosystem. Package enthusiasts care about it as a Mac-native alternative to general-purpose local model servers and as a way to exploit unified memory, Metal acceleration, and aggressively quantized models.
时间线
- 2026: Official project documentation described vMLX as both a Python engine and the backend of a multi-mode MLX Studio desktop application.
Related projects
- Apple MLX and the mlx-lm/mlx-vlm ecosystem provide core Apple-Silicon model primitives.
- JANG supplies the project's adaptive mixed-precision quantization format and runtime integration.
- MLX Studio is the desktop product surface built around vMLX.
来源
安全态势
尚未找到受保护工具覆盖
没有找到 vmlx 的匹配本地密钥处理 manifest。软件包元数据仍在此发布，以便未来覆盖拥有稳定的软件包 URL。
安装行为
- formula 元数据中未记录 Homebrew post-install 钩子。
- 未记录 Homebrew bottle 元数据。
建议审查
在无人值守的代理使用前，请检查该工具是否读取明文凭据、写入远程状态、发布制品或调用插件。
可执行文件
已安装的可执行文件
| 命令 | 类型 | 暴露范围 | 备注 |
|---|---|---|---|
| 没有可执行文件数据。 | |||
新鲜度
版本和新鲜度
这些信号区分页生成时间、软件包管理器活动和上游发布比较。只有存在证据 URL 和可比较版本时，才会提示版本落后。
页面生成时间2026-11-04
管理器版本1.6.83
管理器更新时间
本地数据OK
上游not checked
检测到的最新版本未检测到
https://github.com/jjang-ai/mlxstudio
- 信息No package-manager update timestamp was available.低 置信度
- 信息No cached GitHub release or tag data was available.https://github.com/jjang-ai/mlxstudionone 置信度
安装元数据
软件包元数据
| 软件包键 | cask:vmlx |
|---|---|
| 版本 | 1.6.83 |
| 软件包管理器 | Homebrew Cask |
| 软件包管理器页面 | https://formulae.brew.sh/cask/vmlx |
| 主页 | https://mlx.studio/ |
| 仓库 | https://github.com/jjang-ai/mlxstudio |
| 上游文档 | https://mlx.studio/ |
| 源码归档 | https://github.com/jjang-ai/mlxstudio/releases/download/v1.6.83/vMLX-1.6.83-sequoia-arm64.dmg |
| SHA-256 | 223c23316cd5ae2440f91dd6a9a37e179f624d1e053cfba375ca68f1da3bf96f |
| Bottle | 未记录 |
| Homebrew post-install | 未定义 |
| 服务 | 未声明 |
注册表事实
源数据库详情
| Source Database | Homebrew cask API |
|---|---|
| Tap | homebrew/cask |
| Full Token | vmlx |
| Names |
|
| Depends On | |
| Artifacts | |
| Auto Updates | yes |
| Deprecated | no |
| Disabled | no |
来源线索
由仓库数据生成
此页面由 av-web 从 scripts/generate-pkg-sqlite.py 生成的私有软件包 SQLite 工件提供。
Combined YAML source
View the package source record on GitHub.
使用的来源
- cross-ecosystem install command graph
- curated package history
- package relationship graph
- package version freshness
- package-page enrichment