> ## Documentation Index
> Fetch the complete documentation index at: https://mintlify.com/janhq/jan/llms.txt
> Use this file to discover all available pages before exploring further.

# CLI Overview

> Run Jan from the command line to serve models and launch AI agents

## Introduction

Jan's CLI enables you to run local AI models from the command line and wire them to AI coding agents like Claude Code or OpenCode — no cloud required.

The CLI shares all core logic with the Jan desktop app, so models downloaded in the desktop app are automatically available in the CLI.

<CodeGroup>
  ```bash Terminal theme={null}
  jan serve qwen3.5-35b-a3b              # Expose a model at localhost:6767/v1
  jan launch claude --model qwen3.5-35b  # Start model + launch Claude Code
  jan models list                        # Show all installed models
  ```
</CodeGroup>

## Key Features

* **OpenAI-Compatible API**: Serves models via an OpenAI-compatible endpoint
* **Auto-Detection**: Automatically detects LlamaCPP or MLX engines
* **Agent Integration**: Pre-wires environment variables for Claude Code, Codex, and OpenClaw
* **HuggingFace Downloads**: Auto-download models from HuggingFace repos
* **Background Mode**: Run models in detached mode with `--detach`
* **Context Auto-Fit**: Maximize context window based on available VRAM

## Installation

The Jan CLI is included with the Jan desktop application. Build it from source:

```bash theme={null}
cargo build --features cli --bin jan
```

The binary will be located at `target/release/jan-cli` (or `target/debug/jan-cli` for debug builds).

## Quick Start

### Serve a Model

Start a local model server:

```bash theme={null}
jan serve qwen3.5-35b-a3b
```

<ResponseField name="Output">
  ```
  ✓ qwen3.5-35b-a3b ready · http://127.0.0.1:6767

    Endpoint  http://127.0.0.1:6767/v1

    Press Ctrl+C to stop.
  ```
</ResponseField>

### Launch an AI Agent

Start a model and automatically launch Claude Code with pre-configured environment variables:

```bash theme={null}
jan launch claude --model qwen3.5-35b-a3b
```

The CLI will:

1. Load the specified model
2. Set environment variables (OPENAI\_BASE\_URL, ANTHROPIC\_BASE\_URL, etc.)
3. Launch Claude Code with the local model pre-wired

### List Available Models

View all models installed in your Jan data folder:

```bash theme={null}
jan models list
```

<ResponseField name="Output" type="JSON">
  ```json theme={null}
  [
    {
      "id": "qwen3.5-35b-a3b",
      "engine": "llamacpp",
      "name": "Qwen 3.5 35B",
      "model_path": "/path/to/model.gguf",
      "size_bytes": 21474836480,
      "embedding": false,
      "capabilities": ["text"],
      "mmproj_path": null
    }
  ]
  ```
</ResponseField>

## Architecture

### Data Folder

Jan stores models, threads, and configuration in a platform-specific data folder:

* **macOS**: `~/Library/Application Support/Jan`
* **Linux**: `~/.config/Jan`
* **Windows**: `%APPDATA%\Jan`

View your data folder location:

```bash theme={null}
jan app data-folder
```

### Engine Auto-Detection

Jan automatically detects the appropriate inference engine:

* **LlamaCPP**: For GGUF models (most common)
* **MLX**: For MLX models on macOS/Apple Silicon

The engine is determined from the model's `model.yml` file in the data folder.

### Binary Discovery

Jan auto-discovers inference binaries from the Jan app installation:

* **llama-server**: Found in Jan's app bundle or data folder
* **mlx-server**: Found in Jan.app on macOS

You can override with `--bin <path>` if needed.

## Environment Variables

### HuggingFace Authentication

Set a HuggingFace token to download private/gated models:

```bash theme={null}
export HF_TOKEN="your_token_here"
# or
export HUGGING_FACE_HUB_TOKEN="your_token_here"
```

### Logging

Enable verbose logging:

```bash theme={null}
jan serve qwen3.5-35b --verbose
```

Or set the log level via environment variable:

```bash theme={null}
RUST_LOG=info jan serve qwen3.5-35b
```

## Next Steps

<CardGroup cols={2}>
  <Card title="Commands Reference" icon="terminal" href="/cli/commands">
    Complete reference for all CLI commands
  </Card>

  <Card title="Serve Command" icon="server" href="/cli/serve">
    Detailed guide for serving models
  </Card>

  <Card title="Launch Command" icon="rocket" href="/cli/launch">
    Wire AI agents to local models
  </Card>
</CardGroup>