Rock Pi 4 vs Google Coral Dev Board
Side-by-side comparison of features, pricing, ratings, and alternatives.
The Rock Pi 4 is a compact single-board computer featuring a hexa‑core Rockchip RK3399 processor, up to 4 GB LPDDR4 RAM, and dual‑channel M.2 NVMe support. It offers a rich I/O set including dual HDMI 4K, USB‑C 3.0, Gigabit Ethernet, and Wi‑Fi/Bluetooth for versatile connectivity. Designed for developers, makers, and edge‑AI projects, the board runs Linux, Android, and various open‑source OSes, providing a flexible platform for everything from media servers to AI inference workloads.
The Google Coral Dev Board is a powerful single-board computer designed for rapid prototyping of low-power edge AI devices. It features Google's proprietary Edge TPU coprocessor, capable of performing 4 trillion operations per second while consuming very little energy. Equipped with a complete system containing NXP i.MX 8M SoC, LPDDR4 RAM, and onboard wireless connectivity, the board runs a specialized Debian-based Linux system called Mendel. It provides developers with a complete, out-of-the-box environment to build and deploy high-performance machine learning models locally at the edge.
- High‑performance RK3399 CPU
- M.2 NVMe slot for fast storage
- Dual 4K HDMI outputs
- Strong community and open‑source support
- High-speed local inferencing via Edge TPU
- Removable SOM simplifies custom board design
- Full Linux development environment
- Low power consumption during heavy AI workloads
- Wi‑Fi limited to 802.11ac (no Wi‑Fi 6)
- Limited official Android builds
- Power consumption higher than low‑end SBCs
- Can run quite warm under sustained heavy loads
- Limited to TensorFlow Lite models
- Discontinued or supply-constrained availability in recent years
More alternatives & similar tools
Alternatives to Rock Pi 4
View all →A small, powerful AI computer for makers, learners, and embedded developers.
A powerful, community-supported open-source development board for makers and engineers.
A single-board computer with a removable system-on-module for edge AI applications.
Alternatives to Google Coral Dev Board
View all →A high-performance single-board computer powered by the Rockchip RK3568 processor.
A small, powerful AI computer for makers, learners, and embedded developers.
The Verdict
AI-generated from listing dataThe Coral Dev Board (A) excels at low‑power, dedicated Edge TPU AI inference, while the Rock Pi 4 (B) offers higher general‑purpose performance, more ports, and open‑source flexibility at a lower price.
Key differences
- •AI acceleration: A includes Google's Edge TPU for TensorFlow Lite; B has no dedicated AI coprocessor.
- •CPU performance: B’s hexa‑core RK3399 (up to 2 GHz) outpaces A’s modest processor for general tasks.
- •Storage & expandability: B provides an M.2 NVMe slot and optional eMMC; A relies on standard USB power only.
- •Open‑source support: B is fully open‑source with mainline Linux/Android drivers; A runs Mendel Linux, not open source.
- •Price: A costs $149.99; B is $99.
Pricing & value
B costs $99 versus A’s $149.99, offering more features for less money.
Performance
B’s RK3399 hexa‑core CPU (up to 2 GHz) provides higher overall compute than A’s unspecified processor.
Build quality
Both have similar compact dimensions; weight differs but no clear quality advantage.
Connectivity
B adds USB‑C 3.0, USB‑A 3.0, dual HDMI, and Bluetooth 5.0 on top of Ethernet and Wi‑Fi.
Power & efficiency
A is noted for low power consumption during heavy AI workloads; B consumes more power.
Compatibility
B runs mainline Linux and Android with open‑source drivers; A runs Mendel Linux and only TensorFlow Lite.
Warranty & support
Both provide a 1‑year warranty.
Choose Rock Pi 4 if…
General‑purpose developers or hobbyists wanting higher CPU performance, NVMe storage, and open‑source support.
Choose Google Coral Dev Board if…
Embedded AI engineers needing dedicated Edge TPU inference and low‑power operation.
Common questions
Is the price difference justified?
B is $50 cheaper and adds NVMe, dual HDMI, and broader OS support, while A’s premium is for the Edge TPU.
Can I run any AI model on both boards?
A only runs TensorFlow Lite models on the Edge TPU; B has no AI accelerator, so models run on CPU only.
Which board has better software openness?
B is fully open‑source with mainline Linux/Android drivers; A runs Mendel Linux, a Debian derivative, but is not open source.
