What a Raspberry Pi Can (and Can’t) Do With AI
AI (artificial intelligence) is a buzzword that has been thrown around a lot these days, and the Raspberry Pi ecosystem is no exception. New use cases have been tested on it, and new products have even been released to accompany this phenomenon. So, what can your Raspberry Pi actually do with AI?
A Raspberry Pi can run many AI applications, including large language models (LLMs), AI agents, and computer vision projects. It can also serve as the brain of many AI projects. But even the best Raspberry Pi setup has its limits when it comes to computing power, so it’s not the perfect fit for every use case.
The AI category is really broad, so I can’t give a simple yes or no answer to the question I’m discussing here. It really depends on what you’re trying to build.
For example, object detection can be considered AI. It’s been running on Raspberry Pis for a while now, even on older models that don’t have an accelerator or special hardware. The Raspberry Pi is perfect for that kind of project.
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Check the book hereA bit more demanding: AI agents like OpenClaw or Hermes are surprisingly lightweight. The agent itself doesn’t require much computing power, so a Raspberry Pi 5 is generally more than enough to run it. I’ve got Hermes running on a Raspberry Pi at home, and it’s totally usable.
The main limitation you’ll run into is with LLMs. While some small models can run on a Raspberry Pi, most useful modern LLMs need more RAM and processing power than a Pi can comfortably provide.
If you want fast responses from an LLM, you generally need a powerful CPU, a dedicated GPU, or both. If you’re used to ChatGPT, your local AI running on Raspberry Pi might feel a bit slow and limited.
The Raspberry Pi team recently released several products aimed at improving AI performance (the AI HAT, AI Camera, and others). They’re really interesting for computer vision projects, but they don’t make much difference when it comes to running LLMs.
To sum it up, a Raspberry Pi can absolutely run AI projects, but it’s usually better at using AI than hosting large AI models locally.
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