DevPulse → Use Cases → OpenClaw on Mac Mini

Best Model For

Best local AI model for OpenClaw on a Mac Mini

The Mac Mini is the most popular hardware for running OpenClaw with local models. But memory is tight — especially on the base 24 GB model. The difference between a smooth coding experience and constant swap thrashing comes down to choosing the right model and quantization for your specific Mac Mini config. Here's what actually works, tested across M4, M4 Pro, and M4 Max Mac Minis.

Recommended models

Three tiers based on your available RAM and quality needs.

Tips for openclaw on mac mini

1 On a 24 GB Mac Mini, always unload models when not coding — 'ollama stop' frees the full allocation

2 Close Chrome before loading models. Chrome + OpenClaw + a 9B model on 24 GB leaves zero margin

3 The Mac Mini M4 Pro 48 GB is the sweet spot: runs 32B models with room for a full dev environment

4 Use DevPulse to monitor swap usage — once macOS starts swapping, inference speed drops 10x

5 Q4_K_M is the only practical quantization on 24 GB Mac Minis. Don't bother with Q6_K or Q8_0

6 If you run Docker alongside OpenClaw, lower Docker's memory limit to 2 GB in Settings → Resources

Check with DevPulse

DevPulse tells you which of these models your Mac can run right now — based on your actual available memory, not just your spec sheet.

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Related guides

Quick comparison

Budget Pick
Qwen 3.5 9B (5.5 GB)
Best Overall
Qwen 2.5 Coder 32B (20 GB)
Maximum Quality
Llama 3.3 70B (42 GB)

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