# Run a local LLM chatbot on a Raspberry Pi 5

## In this learning path

- [Introduction](https://learn.arm.com/learning-paths/embedded-and-microcontrollers/llama-python-cpu/)
- [Run a Large Language Model (LLM) chatbot on a Raspberry Pi 5](https://learn.arm.com/learning-paths/embedded-and-microcontrollers/llama-python-cpu/llama-python-chatbot/)
- [Next Steps](https://learn.arm.com/learning-paths/embedded-and-microcontrollers/llama-python-cpu/_next-steps/)

## About this Learning Path
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| Skill level: | Introductory |
| Reading time: | 30 min |
| Last updated: | 13 Aug 2026 |

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| Author: | Jason Andrews , Arm<br>[GitHub](https://github.com/jasonrandrews)<br>[LinkedIn](https://linkedin.com/in/jason-andrews-7b05a8) |
| Arm IP: | [Cortex-A](https://support.arm.com/?tab=compute-ip&Product%20Type=Application%20Processors) |
| Tags: | [ML](https://learn.arm.com/tag/ml) [Linux](https://learn.arm.com/tag/linux) [LLM](https://learn.arm.com/tag/llm) [Generative AI](https://learn.arm.com/tag/generative-ai) [Raspberry Pi](https://learn.arm.com/tag/raspberry-pi) [Python](https://learn.arm.com/tag/python) [Hugging Face](https://learn.arm.com/tag/hugging-face) |

### Who is this for?
This is an introductory topic for anyone interested in running a local Large Language Model on a Raspberry Pi 5.

### What will you learn?
After completing this Learning Path, you'll be able to perform the following tasks:
- Install the Python version of llama.cpp on your Raspberry Pi 5.
- Download an LLM from Hugging Face.
- Assess LLM memory size and performance.
- Run the LLM on your Raspberry Pi 5 using Python bindings for llama.cpp.

### Prerequisites
Before starting, you'll need the following prerequisites:
- A Raspberry Pi 5 running Raspberry Pi OS.

### Summary
You’ll run a local chatbot on a Raspberry Pi 5 with 64-bit Raspberry Pi OS. First, you’ll install the Python bindings for `llama.cpp`, choose a model that fits available memory, and download it from Hugging Face. Then, you’ll load the model, generate responses, and verify interactive inference directly on the Arm Linux device.

### Frequently asked questions

**Which Raspberry Pi 5 model should I use for this chatbot?**

The 8 GB RAM Raspberry Pi 5 model is preferred for exploring an LLM. Smaller memory configurations might restrict the model that you can run.

**How do I know my Raspberry Pi OS installation is 64-bit?**

Check your system information to confirm the operating system and kernel report a 64-bit build. If not, reinstall Raspberry Pi OS using the 64-bit image.

**Can I follow these steps on another Arm Linux computer?**

Yes. The instructions apply to other Arm Linux systems with minor modifications where Raspberry Pi–specific steps appear.

**How do I choose a Hugging Face model that will run on my Pi?**

Compare the model’s size to your available memory and leave headroom for the operating system and Python runtime. Select a model that fits comfortably within your RAM, then assess performance.

**What result should I expect when I run the chatbot?**

A Python script loads the chosen model and generates text responses in your terminal. If it starts and responds to prompts, your setup is working.