Descriptions:
This hands-on tutorial walks through building a completely free and fully private OpenClaw setup using Google’s newly released Gemma 4 open-weight models, run locally via Ollama, with SearXNG providing on-device web search so no data ever leaves your machine. The video covers all four Gemma 4 model variants — the mobile-optimized E2B (7.2 GB) and E4B (9.6 GB), which handle text, image, video, and audio, and the desktop-class 26B and 31B models (text and image only) with context windows up to 256K tokens.
The creator shares firsthand results running the E4B on OpenClaw and testing its agentic tool-calling — the ability to chain multi-step tasks like web search, summarization, report creation, and sending via email or ClickUp without stalling mid-chain. The 26B model running on a Mac Studio (512 GB RAM) and a 24 GB MacBook Pro is presented as the recommended daily-driver configuration, with the 7 GB E2B as a viable option for 16 GB MacBook Pro users.
Step-by-step instructions cover installing Ollama, pulling Gemma 4 models from the model library, plugging them into an existing or new OpenClaw instance via the configure command, and setting up SearXNG as a free private web-search backend. The video also briefly addresses a cloud-hosted 31B option for users who want larger model capacity without local hardware. A practical option for anyone wanting capable AI agents without subscription costs or data privacy trade-offs.
📺 Source: Bart Slodyczka · Published April 06, 2026
🏷️ Format: Tutorial Demo
