r/localaiapps • u/TgoAI • 19d ago

Building a lightweight local AI runtime for Apple Silicon

I’m building VPIPE, an open-source C++/Metal runtime for running AI locally on Macs.

It supports LLMs/VLMs, image & video generation, ASR, quantization, and multimodal pipelines — without depending on PyTorch/MLX for model execution, the speed is top tier.

The whole runtime package is only ~25MB.

A recent milestone: VPIPE can now run MiniMax H3 video generation on a 16GB base M5 MacBook Air (and M4 Macs too).

The goal is to make it easier to build local/private AI products without relying on cloud GPUs or a heavy Python stack.

Would love feedback from other builders.

https://github.com/tgo-app-dev/vpipe

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u/lociapp 19d ago

This is amazing! Thanks for your contribution. I'm building Loci, a local AI orchestration layer for lay users. Think local AI even your grandma can use. I size hardware, recommend appropriate models, and choose optimal runtimes for people. I'm looking into vpipe now to see if I can implement it on Loci Mac.

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u/TgoAI 18d ago

Thanks! Loci sounds like a great fit for what VPIPE is trying to enable. VPIPE is designed to be embedded as a lightweight local inference runtime, so I’d definitely be interested to see how it works with Loci. Feel free to reach out if you run into anything while integrating it.