Raspberry Pi Compute Module 3 Takes On SOPINE A64

  • comments
  • print
  • email
Jan 20, 2017 02:06 PM EST

Raspberry Pi Compute Module 3, a smaller variant of the well-known namesake board was unleashed. Digital creators are able to fuse the same processing power of the Raspberry Pi 3 into their individual Internet of Things (IoT) models. This is with the use of Compute Module 3 of the Raspberry Pi Foundation.

According to CNET, Raspberry Pi CM3 costs $30 and is powered by a Broadcom 1.2GHz, 64-bit quad-core ARM Cortex-A53 CPU processor. It also sports 1GB of RAM and 4GB of eMMC flash storage on a normal DDR2 SODIMM module resulting to an accessible interlock into traditional projects.

A Lite variant for $25 sells the onboard eMMC to incorporate an SD-card socket or eMMC flash. They can be bought in the UK for£27 and £22 and approximately AU$40 and AU$35 in Australia. The Raspberry CM3 is considerably retrogressive compatible as compared to the original CM1.

However, the latest modules are 1mm in height and became hotter with a large CPU load. Therefore, creating a new project using a Raspberry Pi CM3 can obtain the Compute Module IO Board V3 (CMIO3). This IO board offers something to input the CM3 for producing power and processor interfaces and HDMI and USB connectors.

The latest Compute Module 3 of Raspberry Pi has a tough opponent arriving on its way as per PCWorld. It is the new SOPINE A64 64-bit computing module, a tinier variant of the well-known Pine64 board computer.

The SOPINE contains 64-bit quad-core ARM-based CPU like the Raspberry Pi Compute Module 3. It has 2GB RAM, which doubles the RAM of Raspberry Pi CM3. It, likewise, holds a quicker DDR3 memory, surpassing the DDR2 memory of Raspberry Pi CM3.

The SOPINE A64 has a price of $29, which is almost near to the rate of Raspberry Pi Compute Module 3. The brand-new SOPINE will arrive in February, according to the website. It cannot function alone like the Pine64 so it should be plugged in as a memory space within a computer.

Join the Conversation
Real Time Analytics