Best SBC for Running LLM

The ability to run large language models (LLMs) is becoming a desirable feature, allowing these compact systems to serve as intelligent assistants. The RAM available on these SBCs is the key factor in determining the complexity of the LLM they can handle. Let’s explore how each SBC stacks up in this regard and what that means for their AI capabilities.

Related: 7 LLM Models for SBC

SBC for Running LLM

Raspberry Pi 4

Raspberry Pi 4

3 out of 5

Good Stuff Can run 7B model Affordable entry-level option.

Bad Stuff Not enough RAM to run 13b model. CPU not fast enough. Model will load slow on sd card

Starting with the Raspberry Pi 4, it represents the entry level for running LLMs with options up to 8GB LPDDR4-3200 SDRAM. It’s capable of handling models with up to 7 billion parameters, which can serve as basic digital assistants for straightforward tasks such as answering questions, performing simple conversational tasks, and automating basic functions.

Lattepanda 3 Delta

Lattepanda 3 Delta

3 out of 5

Good Stuff Similar RAM capabilities as Raspberry Pi 4 (8GB LPDDR4). Slightly more powerful Intel® Celeron processor.

Bad Stuff Not enough RAM to run 13b model.

Moving up, the Lattepanda 3 Delta provides the same 8GB LPDDR4 RAM as the Raspberry Pi 4, but with its slightly more powerful Intel Celeron processor, it may handle similar-sized models with a tad more efficiency. These 7 billion parameter models are where we begin to see a transition from basic task automation to more intelligent, conversational capabilities.

Rock Pi 5 Model B

Rock Pi 5 Model B

3.8 out of 5

Good Stuff RAM options up to 16GB LPDDR4x. Suitable for advanced assistant functions with deeper contextual understanding.

Bad Stuff Potential higher cost compared to entry-level options.

The Rock Pi 5 Model B steps up the game with RAM options that go up to 16GB LPDDR4x. At the 8GB RAM level, it aligns with the Raspberry Pi 4 and Lattepanda 3 Delta in terms of the complexity of models it can run. However, with the 16GB configuration, it can run more sophisticated 13 billion parameter models, making it suitable for more advanced assistant functions that require deeper contextual understanding and more complex reasoning.

Lattepanda Sigma

Lattepanda Sigma

4 out of 5

Good Stuff 16GB RAM enables the operation of LLMs with 13 billion parameters. Suitable for running larger and more complex models.

Bad Stuff Higher cost compared to entry-level options.

The Lattepanda Sigma with 16GB of RAM is a step into higher performance territory, facilitating the operation of LLMs with 13 billion parameters. Its 32GB RAM variant stands out, not just for the sheer size of the models it can run, but also for the potential to handle multiple LLM tasks simultaneously or to run even larger and more complex models that are closer to the cutting edge of current LLM research.

Orange Pi 5B + Plus

Orange Pi 5B + Plus

3.8 out of 5

Good Stuff Highest RAM capacity at 32GB LPDDR4x, suitable for the largest models. Powerful Rockchip RK3588S processor for real-time conversational AI.

Bad Stuff Higher cost compared to other SBCs. Limited community support compared to more established options. Potential power consumption and heat management issues with the powerful processor.

At the top, we have the Orange Pi 5B + Plus, with its staggering option for 32GB LPDDR4x RAM, making it the most capable in this lineup for LLM tasks. It can run the largest models with ease, and its high-performance Rockchip RK3588S processor ensures that it can deal with the demands of processing large amounts of data quickly, which is essential for real-time conversational AI and complex reasoning tasks that require immediate feedback.