How to Run DeepSeek-V3 on 8 Mac Minis: A DIY Approach to Local AI

A developer recently stacked 8 Mac Minis into a "mini data center" to run large language models locally. Here's what you need to know:

Setup Details

• Cost: ~$20,000 total

• Performance: 5 tokens/second

• Hardware: 8x M4 Mac Minis in stack configuration

• Implementation: Distributed computing across units

Cost-Performance Analysis

Compared to commercial servers:

• Professional setups: $200,000+

• This DIY approach: $20,000

• Performance trade-off: Significantly slower but locally controlled

Technical Implementation

The system uses distributed computing to coordinate the Mac Minis, enabling local LLM inference without dependence on cloud services.

Practical Considerations

Pros:

• Local control

• Lower initial investment

• Consumer hardware availability

Cons:

• Lower performance vs. commercial servers

• Power consumption concerns

• Heat management needed

While not optimal for production use, this setup demonstrates the possibilities for experimenting with LLMs using consumer hardware. It's particularly relevant for developers and researchers who want to test models locally without significant cloud computing costs.

#AIComputing #MacMini #LocalAI #DIY #TechExperiment