Arduino UNO Q Comparison: 2 GB vs 4 GB

Arduino have recently launched the new 4 GB variant (070-8753) of the Arduino UNO Q, expanding the capabilities of their hybrid Linux and microcontroller platform. In this article, we’re going to compare the 2 GB and 4 GB versions side by side, explore what sets them apart, and help you choose the right board for your next project.

If you’re new to the Arduino UNO Q, you can start with my original deep dive, where I explored how this groundbreaking dual processor board marks “a new era for innovators” in embedded AI and hybrid compute design, you can revisit that article here: Meet the Arduino® UNO Q: A New Era for Innovators

I also took a closer look at Arduino App Lab, the powerful new development environment that unifies Linux, real time firmware, AI workflows, and containerised applications into a seamless experience for engineers and makers. You can read that piece here: What is Arduino App Lab and What Does It Mean for Engineers?

Overview of Both Variants of the Arduino UNO Q

Common Architecture

Both versions of the UNO Q share:

• A Qualcomm® Dragonwing™ QRB2210 quad core Cortex A53 MPU @ 2.0 GHz with Adreno GPU and dual ISP
• A real time STM32U585 MCU (Cortex M33 @ up to 160 MHz) with 2 MB flash + 786 KB SRAM
• Linux Debian OS + Arduino Core on Zephyr S for dual OS development
• Support for Arduino App Lab, Python, Arduino IDE, pre loaded AI models, and containerisation via Docker/Docker Compose
• Identical connectivity (Wi Fi 5, Bluetooth 5.1), USB C with video output, UNO form factor, high speed interfaces, and LED matrix

Functionally, both boards are ideal for AI, IoT, robotics, and high level application prototyping it just depends on your workload requirements.

Key Differences between Arduino UNO Q 2GB and 4GB at a Glance

Detailed Technical Comparison

Memory (RAM)

• Arduino UNO Q 2 GB (066-5593) : Suitable for most AI applications, moderate computer vision tasks, and running typical Linux based applications.
• Arduino UNO Q 4 GB (070-8753) : Designed for demanding workloads, multiple simultaneous processes, advanced ML models, and SBC like experiences

Impact: More RAM improves multitasking, prevents memory bottlenecks in Python and containerised apps, and allows larger tensor models to run locally.

Storage

• Arduino UNO Q 2 GB with 16 GB eMMC (066-5593) : Ideal for typical Linux apps, smaller AI models.
• Arduino UNO Q 4 GB with 32 GB eMMC (070-8753) : Recommended for developers storing logs, datasets, and large ML runtimes.

Impact: More eMMC is particularly useful for on device datasets, robotics logs, and model versioning.

Power Input Differences

• Arduino UNO Q 2 GB (066-5593) : VIN 7–24 V DC, more flexible for projects with battery packs or industrial supply ranges.
• Arduino UNO Q 4 GB (070-8753) : VIN fixed at 5 V DC.

Impact: The 2 GB variant integrates better into mixed voltage systems; the 4 GB variant leans toward SBC style use where powered over USB C.

Shared Features (Identical on Both Boards)

All of the following are present on both models:

• USB C with video output & host/device switching
• Qwiic connector
• High speed peripherals (I²C/I3C, SPI, CAN, UART, PWM, GPIO, ADC, JTAG, PSSI)
• 8×13 LED matrix + RGB LEDs
• Wi Fi 5 + Bluetooth 5.1
• Camera/display/audio support via Dragonwing MPU
• Same classic UNO form factor

Recommended Use Cases

Arduino UNO Q 2 GB (066-5593) :

• Learning and prototyping hybrid Linux/MCU workflows
• Moderate AI demos (object recognition, sound detection, keyword spotting)
• Projects using classic UNO shields
• IoT deployments with lighter local processing
• The 2 GB version is a cost effective choice that retains all capabilities of the UNO Q platform.

Arduino UNO Q 4 GB (070-8753) :

• SBC style usage (desktop-like multitasking, browser apps, Python environments)
• Large ML models, including high resolution image classification & complex audio pipelines
• Multiple concurrent Linux processes (e.g., Docker containers + App Lab + CV pipeline)
• Data heavy robotics or monitoring systems with substantial logging requirements
• Arduino explicitly recommends the 4 GB variant for advanced AI and ML workloads.

Which UNO Q Is Right for You?

Arduino UNO Q 2 GB (066-5593) if you want:

• A lower cost entry into hybrid Linux/MCU development
• Uno ecosystem compatibility with moderate AI tasks
• More flexible VIN voltage options
• General experimentation

Arduino UNO Q 4 GB (070-8753) if you need:

• Significant RAM headroom for multitasking
• Running large AI/ML models locally
• A more PC like experience in SBC mode
• More built in storage for datasets and logs

Summary

The two variants are identical in architecture and external functionality, but differ substantially in RAM, storage, and recommended workloads. The 2 GB (066-5593) model is fully capable for most projects, while the 4 GB (070-8753) variant is a powerhouse intended for developers pushing AI, multi process Linux workloads, or SBC applications.

For additional insight into the engineering behind the platform, check out my interview with Andrea Richetta, Principal Tech Evangelist at Arduino:

Play video

And if you’d like even more related content, projects, and technical articles, the DesignSpark Arduino Hub is the best place to explore.

Find Out More About the Arduino UNO Q

Our Team is ready to help you explore why Arduino UNO Q is the smart choice for your next project. Get in touch today to start the conversation.