Everything You Need to Know About MLX + oMLX for Local AI on Mac

MLX + oMLX Explained: Run Local AI on Apple Silicon with Pi and OpenCode In this video, I walk through the Apple Silicon path for running local AI using MLX and oMLX. We look at what MLX does on Mac, how oMLX turns local MLX models into an OpenAI-compatible server, and how tools like Pi and OpenCode connect to that local endpoint for coding workflows. Covered in this video: What MLX is on Apple Silicon How oMLX works as a local server Local model setup with Qwen2.5-Coder 1.5B MLX 4-bit Direct oMLX speed evidence Pi connected to oMLX OpenCode connected to oMLX Why client overhead changes response time When to use direct oMLX, Pi, or OpenCode Tools and references: MLX: https://github.com/ml-explore/mlx MLX docs: https://ml-explore.github.io/mlx/buil... oMLX: https://github.com/omlx-ai/omlx Qwen2.5-Coder 1.5B MLX 4-bit: https://huggingface.co/mlx-community/... OpenCode: https://opencode.ai/docs/ This is a practical local AI walkthrough for Mac users who want to understand the runtime layer, server layer, and coding client layer before building a local workflow. #MLX #oMLX #AppleSilicon #LocalAI #AIOnMac #MacAI #OpenSourceAI #Qwen #QwenCoder #OpenCode #PiAI #LLM #LocalLLM #AICoding #MacBookAI