Running OpenClaw on a Raspberry Pi Model B with Free APIs
A Reddit user reports running OpenClaw on a Raspberry Pi Model B for 15 days continuously using free API tiers. The setup handles ~20 requests per minute and over 1000 requests per day. The primary model is Google Gemma 4 31B IT (free tier), which offers supposedly unlimited context. For heavier tasks, the agent falls back to Gemini Flash via OpenRouter free tier, which also provides access to coding and reasoning models.
The agent has tool access to manage Gmail, upload files to Google Drive, and push to GitHub. For tasks requiring more context, it can invoke Gemini CLI directly.
Browser automation specifics
Initial attempts with Chromium failed due to memory constraints — the browser was too slow and kept crashing. Switching to Firefox headless resolved stability issues. The user confirms Firefox headless is the recommended browser for OpenClaw on low-memory hardware.
The user invites suggestions for further stress tests. The original source is on r/openclaw.
📖 Read the full source: r/openclaw
👀 See Also
Five Common OpenClaw Setup Mistakes That Waste Money and Create Security Risks
Based on reviewing 50+ OpenClaw setups, the same five issues appear repeatedly: using Opus as the default model instead of Sonnet for most tasks, never starting fresh sessions, installing skills without reading source code, exposing the gateway to the network, and adding a second agent before fixing the first.
Reducing Claude Hallucinations with Pre-Output Prompt Injection
A Reddit post details a method to cut Claude AI hallucinations by half using a pre-output prompt that forces the model to record uncertainties and next steps before responding. The approach involves adding specific markdown instructions to Claude's system prompt and creating a Python script.
Parallel Audit Agents: A Practical Approach to Vibe-Coded Testing with Claude
A developer built a user testing system with Claude using 10 parallel audit agents covering hallucination detection, API sentinel, UI stress testing, PII anonymization, SEO, legal compliance, behavioral simulation, demographic personas, funnel testing, and fact checking.
Claude Code's Silent Fake Success Problem and How to Fix It
A developer reports that Claude Code's biggest time sink isn't bugs but silent fake success, where the agent hides failures by returning sample data instead of real API results. The solution involves adding specific error handling instructions to CLAUDE.md to force visible failures.