Run Gemma 4 26B MOE Locally on a Mac with Only ~6GB RAM

1. 1Install llama.cpp and its dependencies
2. 2Configure memory-mapped files using mmap
3. 3Set up Metal for GPU acceleration
4. 4Download and load the Gemma 4 26B MOE model
5. 5Run benchmarks to measure performance

Machine learning engineers and researchers can benefit from this guide to run large language models on local machines with limited RAM, improving development and testing efficiency

💡 The Mixture-of-Experts (MOE) architecture in Gemma 4 26B MOE allows it to run with limited RAM by only activating a subset of experts at a time

🚀 Run Gemma 4 26B MOE locally on a Mac with ~6GB RAM! 🤯 Using llama.cpp, mmap, and Metal, achieve 49 tokens per second 📊