DeepSeek (671B) running on a cluster of 8 Mac Mini Pros with 64GB RAM each

[AstonJ]

This is cool!

DEEPSEEK-V3 ON M4 MAC: BLAZING FAST INFERENCE ON APPLE SILICON

We just witnessed something incredible: the largest open-source language model flexing its muscles on Apple Silicon. We’re talking about the massive DeepSeek-V3 on M4 Mac, specifically the 671 billion parameter model running on a cluster of 8 M4 Pro Mac Minis with 64GB of RAM each – that’s a whopping 512GB of combined memory!

This isn’t just about bragging rights. It opens up new possibilities for researchers, developers, and anyone interested in pushing the boundaries of AI. Let’s dive into the details and see why DeepSeek-V3 on M4 Mac is such a big deal.

TABLE OF CONTENTS

• The Results Are In: DeepSeek V3 671B Performance on the M4 Mac Mini Cluster
• Why So Fast? Understanding the DeepSeek-V3 on M4 Mac Performance Advantage
  • LLM Inference Explained: A Systems Perspective on Running Large Models
  • Mixture-of-Experts (MoE) Models: The Key to DeepSeek V3’s Efficiency
  • DeepSeek-V3 on M4 Mac: Why This Setup Works So Well for MoE Models
• Exploring Key Considerations: Power, Cost, and Alternative Setups for Running DeepSeek-V3
  • Power Consumption:
  • Efficiency:
  • Older But Beefier Hardware:
• Conclusion: The Future of LLM Inference on Apple Silicon with DeepSeek-V3 on M4 Mac

DeepSeek-V3 on M4 Mac: Blazing Fast Inference on Apple Silicon