How to Run OpenClaw Fully Local with Ollama
A user on r/clawdbot has shared a method for running the OpenClaw agent framework entirely on a local machine, eliminating the need for paid cloud APIs.
Setup Process
The described process involves several specific steps:
- Use LLMFit to benchmark and find the best-performing language model your local hardware can handle. The source links to the tool's GitHub repository: https://github.com/AlexsJones/llmfit.
- Install Ollama.
- Pull your selected model locally using Ollama.
- Link Ollama to OpenClaw.
- Restart the OpenClaw Gateway.
Reported Benefits
According to the source, this setup provides several advantages:
- No API keys required.
- No token limits.
- No per-request billing.
- Fully self-hosted.
- Useful for experimentation and automation.
The post suggests this method is particularly applicable for building internal agents, automation workflows, or for aggressive testing scenarios. The original author also solicits community feedback, asking what models others are running locally with Ollama and agent frameworks, what hardware they use, and how the performance is.
📖 Read the full source: r/clawdbot
👀 See Also
Short Leash AI Coding Method: Beat Fable by Keeping Control
Greg Slepak's short leash method for AI coding agents: plan, review every diff, deny bad changes, commit after subtasks. Beats Fable quality by keeping the developer in the loop.
Use Task Runners for Common Coding Tasks
Ham Vocke explains how to use simple bash scripts or Makefiles as task runners to standardize common commands like build, test, and format across repositories.
Claude for Motion Graphics: Prompt Patterns That Produce Animated HTML Visuals You Can Capture as Video
A r/ClaudeAI user shares a reliable prompt structure for generating animated motion graphics and interactive charts as HTML widgets from Claude, then capturing them as MP4 with Playwright + ffmpeg.
How to safely run llama.cpp native tools (exec_shell_command) with multi-sandboxing on Linux
A practical guide to enabling llama.cpp native tools, especially exec_shell_command, and running them inside multiple sandboxes (Firejail + tiny Alpine VM) for safe web fetching and command execution via the llama-server web UI.