# Get started with the Raspberry Pi 4

## In this learning path

- [Introduction](https://learn.arm.com/learning-paths/embedded-and-microcontrollers/rpi/)
- [Introduction to the Raspberry Pi 4](https://learn.arm.com/learning-paths/embedded-and-microcontrollers/rpi/intro/)
- [Setup a Raspberry Pi 4 and an Arm cloud instance](https://learn.arm.com/learning-paths/embedded-and-microcontrollers/rpi/setup/)
- [Identifying the hardware](https://learn.arm.com/learning-paths/embedded-and-microcontrollers/rpi/id/)
- [Linux Kernel Compile](https://learn.arm.com/learning-paths/embedded-and-microcontrollers/rpi/kernel/)
- [TensorFlow](https://learn.arm.com/learning-paths/embedded-and-microcontrollers/rpi/tf/)
- [Docker](https://learn.arm.com/learning-paths/embedded-and-microcontrollers/rpi/docker/)
- [Linux Perf](https://learn.arm.com/learning-paths/embedded-and-microcontrollers/rpi/perf/)
- [Next Steps](https://learn.arm.com/learning-paths/embedded-and-microcontrollers/rpi/_next-steps/)

## About this Learning Path

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| Skill level: | Introductory |
| Reading time: | 1 hr 30 min |
| Last updated: | 14 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) [Neoverse](https://support.arm.com/?tab=compute-ip&Product%20Type=Infrastructure%20Processors) |
| Tags: | [Embedded Linux](https://learn.arm.com/tag/embedded-linux) [Linux](https://learn.arm.com/tag/linux) [Raspberry Pi](https://learn.arm.com/tag/raspberry-pi) [TensorFlow](https://learn.arm.com/tag/tensorflow) [Docker](https://learn.arm.com/tag/docker) |

### Who is this for?

This is an introductory topic for software developers interested in the Raspberry Pi 4.

### What will you learn?

After completing this Learning Path, you'll be able to perform the following tasks:

- Build and run multiple software examples on the Raspberry Pi 4
- Compare and contrast the Raspberry Pi 4 to an Arm cloud server

### Prerequisites

Before starting, you'll need the following prerequisites:

- A Raspberry Pi 4 board
- An [Arm based instance](https://learn.arm.com/learning-paths/servers-and-cloud-computing/csp/) from a cloud service provider.

### Summary

You’ll compare a Raspberry Pi 4 and an Arm-based cloud instance by running the same workloads on both systems. First, you’ll install 64-bit Raspberry Pi OS and verify each system with `uname`. Then, you’ll build a Linux kernel, install TensorFlow, and run a quickstart example. You’ll use matching commands to compare platform behavior and build times.

### Frequently asked questions

**How do I know both systems are configured for 64-bit Arm before comparing results?**

Run `uname -a` on each machine and confirm the architecture shows `aarch64`. The exact kernel version string might differ, but the architecture should match on both.

**Which Raspberry Pi OS image should I write to the SD card?**

Use the 64-bit version of Raspberry Pi OS.

**Where should I run the TensorFlow example, and which example should I use?**

Run it on both the Raspberry Pi 4 and the Arm-based cloud server to compare behavior. Use the TensorFlow quickstart example or the quickstart code provided in the Learning Path.

**What outcome should I expect from the Linux kernel compile comparison?**

Every recent cloud server is faster than a Raspberry Pi 4. Record the elapsed build time on both systems to understand the relative difference.

**How do I choose a cloud instance for this comparison?**

Use an Arm-based instance from a cloud service provider. For instructions to select and provision an instance, follow the [Get started with Arm-based cloud instances](https://learn.arm.com/learning-paths/servers-and-cloud-computing/csp/) Learning Path.