Source URL: https://simonwillison.net/2025/Jan/22/mlx-distributed/
Source: Simon Willison’s Weblog
Title: Run DeepSeek R1 or V3 with MLX Distributed
Feedly Summary: Run DeepSeek R1 or V3 with MLX Distributed
Handy detailed instructions from Awni Hannun on running the enormous DeepSeek R1 or v3 models on a cluster of Macs using the distributed communication feature of Apple’s MLX library.
DeepSeek R1 quantized to 4-bit requires 450GB in aggregate RAM, which can be achieved by a cluster of three 192 GB M2 Ultras ($16,797 will buy you three 192GB Apple M2 Ultra Mac Studios at $5,599 each).
Via @awnihannun
Tags: apple, generative-ai, mlx, deepseek, ai, llms
AI Summary and Description: Yes
Summary: The text provides practical instructions on deploying the DeepSeek R1 or V3 models using Apple’s MLX library in a distributed manner on a cluster of Macs. This showcases significant insights into optimizing AI workloads on cloud-based infrastructure, particularly beneficial for professionals engaged in AI and cloud computing security.
Detailed Description: The content focuses on the implementation of advanced generative AI models, specifically the DeepSeek R1 and V3 versions, utilizing Apple’s MLX library for distributed computing. This is particularly relevant for professionals in AI, cloud, and infrastructure security as it emphasizes the necessity of robust infrastructure for managing large AI models, which can have implications for privacy, security, and compliance.
– **Running DeepSeek Models:**
– Instructions are provided for setting up the DeepSeek R1 or V3 models on a cluster of Apple Macs.
– The distributed communication feature of Apple’s MLX library is highlighted as a critical component for efficient execution.
– **Hardware Requirements:**
– DeepSeek R1 model, when quantized to 4-bit, requires a substantial 450GB of RAM.
– This can be addressed by leveraging a cluster comprising three Apple M2 Ultra machines, each equipped with 192GB of RAM.
– The financial investment involved in acquiring three Mac Studios is noted, totaling approximately $16,797.
– **Application of Generative AI:**
– The deployment of such models can significantly influence AI security practices, particularly how data is handled in distributed environments.
– Additionally, understanding the infrastructure requirements helps in compliance and planning for secure AI operations.
Overall, this discourse serves as a guide for effectively utilizing hardware resources for advanced AI processes and emphasizes the importance of security considerations in deploying large models within cloud infrastructures.