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.

Terminal

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

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:

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:

jan serve qwen3.5-35b-a3b

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.

Launch an AI Agent

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

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:

jan models list

Output · JSON

[
  {
    "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
  }
]

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:

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:

export HF_TOKEN="your_token_here"
# or
export HUGGING_FACE_HUB_TOKEN="your_token_here"

Logging

Enable verbose logging:

jan serve qwen3.5-35b --verbose

Or set the log level via environment variable:

RUST_LOG=info jan serve qwen3.5-35b

Next Steps

Commands Reference

Complete reference for all CLI commands

Serve Command

Detailed guide for serving models

Launch Command

Wire AI agents to local models