How to run DeepSeek R1 on your Raspberry Pi 5 step by step

How to run DeepSeek R1 on your Raspberry Pi 5? Can it be done? Let's take a look. Since the advent of open source AI models, many enthusiasts have been looking for ways to run them on their own devices. One of the most promising is DeepSeek R1, a model developed in China that has proven to compete with OpenAI's most advanced options. However, the big question is this.

The quick answer is yes, but with certain limitations. In this article we will discuss in detail what it takes to make it work, how to set it y what result can be expected depending on the hardware available. Let's go with the article on how to run DeepSeek R1 on your Raspberry Pi 5. Remember that using the search engine Tecnobits, you will find more information about Raspberry and other hardware or software.

What is DeepSeek R1 and what makes it special?

DeepSeek R1 is an open source AI model that has surprised the community thanks to its efficiency y performance. Unlike many other models, it offers the possibility of running on local hardware, making it an interesting alternative to solutions in the cloud like ChatGPT.

However, the most complete model, the DeepSeek R1 671B, takes up more than 400 GB and requires multiple high-performance graphics cards to run properly. Although the full version is unattainable for most, there are distilled versions that can run on more modest hardware like a Raspberry Pi.

If you like the world of Raspberry in Tecnobits We have a lot of information about this hardwareFor example, we bring you this news in which we talk about Raspberry Pi Pico: the new board that is only worth 4 euros.

Running DeepSeek R1 on a Raspberry Pi 5

The Raspberry Pi 5 is a powerful mini pc compared to its predecessors, but it still has significant limitations when it comes to artificial intelligence. To make DeepSeek R1 work on this device, it is necessary to resort to lighter versions of the model.

Previous requirements

• A Raspberry Pi 5 with at least 8 GB of RAM.
• A microSD card of high capacity and speed to store the necessary files.
• A Linux-based operating system, such as Raspberry PiOS or Ubuntu.
• Internet connection to download model files.
• Access to a terminal to install and run the necessary software.

Now we have everything we need to start learning how to run DeepSeek R1 on your Raspberry Pi 5.

Installing key components

To run DeepSeek R1 on Raspberry Pi, you need to install a key tool set. Below we explain step by step how to do it.

1. Installing Llama.cpp

Llama.cpp is a software that allows you to run AI models efficiently on devices with limited resourcesTo install it, use the following commands:

sudo apt update && sudo apt upgrade -y sudo apt install git cmake build-essential -y git clone https://github.com/ggerganov/llama.cpp.git cd llama.cpp make

This process will download and will compile the tool on your Raspberry Pi.

2. Downloading the distilled DeepSeek R1 model

To ensure manageable performance on Raspberry Pi 5, it is recommended to use the version DeepSeek R1 1.5B, which is about 1 GB in size.

You can download it from Hugging Face with the following command in Python:

from huggingface_hub import snapshot_download snapshot_download(repo_id='DeepSeek-R1-1.5B', local_dir='DeepSeek-R1')

3. Setting up and running the server

Once the model is downloaded, the next step is to run it with Llama.cpp. Use the following command:

./llama-server --model /path_to_your_model/DeepSeek-R1-1.5B.gguf --port 10000 --ctx-size 1024 --n-gpu-layers 40

If all went well, the server will be running in http://127.0.0.1:10000.

4. Integration with Open WebUI

To facilitate the interaction With the model, Open WebUI is a graphical interface that allows you to send questions and receive answers without having to write commands manuallyTo connect to the Llama.cpp server, follow these steps:

1. Open Open WebUI.
2. Go to Settings > Connections > OpenAI.
3. Enter the URL http://127.0.0.1:10000 in the settings.
4. Save the changes and start using DeepSeek R1 from the web interface.

Is it clear how to run DeepSeek R1 on your Raspberry Pi 5? There's more for you.

what results can be expected?

Although DeepSeek R1 can run on Raspberry Pi 5, there are several caveats to consider: major limitations:

• A performance very limited compared to the full version of the model.
• text generation slow, especially with models with more than 7B parameters.
• Replies less precise compared to larger models running on powerful hardware.

In tests carried out with different versions of the model, it was found that the version 1.5B is the most recommended for Raspberry Pi 5, although performance is still modest. Before we finish this article on how to run DeepSeek R1 on your Raspberry Pi 5 we have a few more things to tell you about different use cases for lightweight models.

Use cases for lightweight models

Although a Raspberry Pi cannot handle giant models, scaled-down versions can still be useful in certain Scenarios:

• Basic code generation and math help.
• Automation in home automation projects.
• Support for specific tasks in embedded systems.

Being able to run advanced AI models on affordable hardware is certainly a major step forward in the open source world. Although the Raspberry Pi 5 will not offer an experience comparable to that of a server with multiple GPUs, exploring these options opens new Possibilities for low-cost computing. If you are interested in trying it out, follow the steps in this guide and experiment with the different versions of the model to tune performance to your needs. We hope this article on how to run DeepSeek R1 on your Raspberry Pi 5 has been helpful to you.