Run Jemma 4 locally with OpenClaw

This guide demonstrates how to run Google's Gemma 4 open model locally using OpenClaw, with support for remote access from Mac setups. The tutorial covers the setup process, configuration, and execution steps needed to deploy Gemma 4 as a local language model. Users can leverage this approach for private, offline AI inference without relying on cloud services.

Key Points

• •Gemma 4 is Google's open-source language model available for local deployment
• •OpenClaw provides a framework for running large language models locally
• •Local execution enables privacy-preserving AI inference without cloud dependencies
• •Remote access capability allows Mac users to connect to locally-running models
• •Setup process involves configuring OpenClaw with Gemma 4 model weights
• •Local deployment reduces latency and provides full control over model behavior
• •Suitable for development, testing, and production use cases requiring offline AI

Workflow Diagram

Concepts