nativ

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Nativ

Local AI, native to your Mac.

Chat, serve, monitor, and connect MLX models from one macOS app.

Nativ is a native macOS workspace for running AI models locally on Apple silicon. It bundles an mlx-vlm server, finds compatible models in your Hugging Face cache, and wraps the whole experience in a polished SwiftUI app.

Use Nativ as a private chat app, a model manager, a performance dashboard, or an OpenAI- and Anthropic-compatible local inference server for the tools you already use.

What Nativ can do

Feature	What you get
Local chat and vision	Streaming conversations, image attachments, reasoning output, response metrics, and persistent chat history.
Model library	Discover installed MLX models, browse compatible models on Hugging Face, download them, inspect capabilities, switch models, or remove old ones.
Performance analytics	Track request volume, token usage, time to first token, decode speed, model performance, and recent activity.
Local APIs	OpenAI-compatible chat, Responses, image, audio, and model endpoints, plus Anthropic Messages endpoints.
Coding-tool integrations	Configure and launch Codex, Claude Code, Pi, Hermes, and OpenCode against models served by Nativ.
Developer workspace	Inspect runtime details, copy endpoint URLs, search and filter live server logs, and monitor server health.
Menu bar controls	Start or stop the server, change the loaded model, check serving statistics, and open the main app without breaking focus.
Advanced inference controls	Tune sampling, thinking budgets, structured output, KV-cache quantization, prefix caching, and speculative decoding.

Inference runs on your Mac after a model has been downloaded. Model downloads and first-time build dependencies still require network access.

Coming soon

Support for dedicated audio-only and image-generation-only models is coming soon.

How it works

flowchart LR
    A["Nativ · SwiftUI app"] --> B["NativServerKit"]
    B --> C["Bundled mlx-vlm server"]
    C --> D["MLX runtime"]
    D --> E["Local models · Apple unified memory"]
    F["Apps and coding agents"] -->|"localhost API"| C

NativServerKit owns the embedded Python distribution and server lifecycle. The app adds model discovery, chat, analytics, configuration, integrations, logs, menu bar controls, and software updates around that runtime.

Requirements

To run the app:

• A Mac with Apple silicon.
• macOS 26 or newer.
• Enough unified memory for the model you choose.

To build from source, you will also need:

• Xcode with the macOS 26 SDK.
• xcodegen.
• Python 3.
• Network access to GitHub Releases and PyPI while the embedded Python bundle is first assembled or refreshed.

Get started

Download a release

Download the latest DMG from GitHub Releases, drag Nativ to Applications, and launch it. Nativ uses Sparkle for subsequent in-app updates.

On first launch:

1. Choose an installed language model, or continue with load-on-demand.
2. Optionally generate an API key to protect the server’s management endpoints.
3. Open Models to download or select a compatible model.
4. Start chatting, inspect analytics, or connect one of the supported coding tools.

Build from source

brew install xcodegen
make xcode-generate
make xcode-build
open build/XcodeDerivedData/Build/Products/Debug/Nativ.app

The first build can take a while because NativServerKit creates a relocatable Python runtime and installs the pinned mlx-vlm server dependencies into the framework resources. Later builds reuse the bundle until an input changes.

Use Nativ as a local API server

By default, the app exposes its server at http://127.0.0.1:8080. The Developer page lists every available endpoint and lets you copy URLs directly.

For example, with a model selected:

curl http://127.0.0.1:8080/v1/chat/completions \
  -H 'Content-Type: application/json' \
  -d '{
    "model": "your-model-id",
    "messages": [{"role": "user", "content": "Why is the sky blue?"}],
    "stream": false
  }'

If you enabled a server API key, also send it as a Bearer token:

-H 'Authorization: Bearer your-api-key'

The server includes:

• OpenAI-compatible /v1/chat/completions, /v1/responses, /v1/models, image, and audio routes.
• Anthropic-compatible /v1/messages and token-counting routes.
• /health, /metrics, cache statistics, cache reset, and model unload endpoints.

Project layout

Sources/
├── Nativ/                       # SwiftUI application
│   ├── Features/
│   │   ├── Chat/
│   │   ├── Dashboard/
│   │   ├── Developer/
│   │   ├── ImageGeneration/
│   │   ├── Integrations/
│   │   └── Models/
│   ├── Assets.xcassets/
│   ├── ModelProviderIcons/
│   └── Utilities/
└── NativServerKit/              # Embedded server and Swift clients
PythonDistribution/
├── Launcher/                    # Relocatable server launcher
├── Requirements/                # Pinned Python dependencies
└── Scripts/                     # Bundle assembly and verification
Configuration/                   # App metadata and signing settings
Design/                          # Brand source files and README artwork
scripts/                         # Archive, signing, notarization, and release tools
project.yml                      # XcodeGen project definition

Development

Build and smoke tests

Generate and build the Xcode project:

make xcode-generate
make xcode-build

Verify that the bundled executable can launch and print mlx_vlm.server help:

make xcode-smoke

Exercise the long-running process lifecycle and /metrics readiness:

make xcode-lifecycle-smoke

To generate a few real requests and compare metrics before and after:

scripts/run_metrics_queries.py

The first request may take longer while its model downloads and loads.

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Built for fast, local inference on Apple silicon.