AI vision hardware for makers: Pi, Arduino or Jetson?
Comparing the Raspberry Pi AI Camera, AI HAT+ 2, Arduino UNO Q and Jetson Orin Nano for maker AI projects. What each can run, and which to start with.
Updated
Running AI on your own hardware means no cloud fees, no network lag, and no images leaving your workshop. The options now span a $70 camera to a GPU computer. The right choice depends on one question: what does the model need to do?
The short version
| If you want to… | Start with |
|---|---|
| Detect objects, people or animals cheaply | Raspberry Pi AI Camera |
| Run small language or speech models offline on a Pi | Raspberry Pi AI HAT+ 2 |
| Combine vision with precise motor or sensor control | Arduino UNO Q |
| Multi-camera vision, robotics, heavier models | Jetson Orin Nano Super |
Raspberry Pi AI Camera: the easy start
The neural network runs on the camera’s Sony IMX500 sensor, so even a Pi Zero can handle detection. It’s ideal for wildlife cameras, people counters, or watching a print bed. It’s limited to compact vision models.
Raspberry Pi AI HAT+ 2: generative AI on a Pi 5
A Hailo-10H accelerator with its own 8 GB of memory. That memory is the point: it lets a Raspberry Pi 5 run small LLMs, speech-to-text and vision-language models locally. For vision alone it performs about the same as the cheaper original AI HAT+, so buy it for the generative side.
Arduino UNO Q: AI that moves things
A Linux processor and an STM32 microcontroller on one UNO-sized board. The Linux side runs the model; the microcontroller handles real-time timing for motors, servos and sensors. It suits robots and machines where a vision result has to become a precise movement.
Jetson Orin Nano Super: when you need a GPU
67 TOPS, CUDA, and NVIDIA’s robotics software. It’s the choice for several camera streams, larger models, or a drone or rover companion computer. The trade-offs are power draw and a steeper learning curve.
How to choose
- Start with the job, not the TOPS number. Most maker vision projects run happily on the AI Camera.
- Check the software path. Look for a ready-made example close to your project. Converting your own models is where beginners get stuck.
- Count the watts on anything battery-powered. A Jetson can halve a drone’s flight time compared with a Pi-class board.