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FRDM-IMX93

FRDM-IMX93

NXP USA Inc.
- Embedded Evaluation Board
Active

Overview

The FRDM-IMX93 is a compact development platform featuring the i.MX 93 applications processor with a dual-core Arm Cortex-A55 at 1.7 GHz and a Cortex-M33 real-time core. It provides a comprehensive set of interfaces including Gigabit Ethernet, Wi-Fi, Bluetooth, and MIPI display/camera support for high-performance edge processing. The board is designed for rapid prototyping of industrial and consumer applications that require low power consumption and hardware-accelerated machine learning.

Why Choose This Part

The platform offers a versatile heterogeneous architecture that balances high-performance Linux execution on Cortex-A55 with low-latency, real-time tasks on Cortex-M33. It features extensive connectivity options and a robust 2GB RAM capacity in a small 65mm x 105mm form factor.

Applications

Industrial Gateways
Utilizes dual Gigabit Ethernet and multiple CAN interfaces for secure industrial communication and protocol conversion.
Edge AI Vision
Leverages the MIPI CSI interface and A55 cores to process camera data for object detection or presence sensing.
Smart Home Hubs
Integrated Wi-Fi, Bluetooth, and audio interfaces like PDM and I2S enable voice-controlled home automation centers.
Human-Machine Interface (HMI)
Drives high-resolution displays via MIPI DSI or HDMI for interactive control panels in building management.

Getting Started

Start by downloading the NXP MCUXpresso SDK for real-time development and the Yocto Project-based Linux BSP for the application cores. The board supports debugging via the onboard JTAG/SWD interface and connects to power and consoles through USB Type-C and Type-A ports.

FRDM Family

Comparing specs that differ across variants. The current part is highlighted.

Part Number Type Stock
FRDM-IMX93 (this part)
FRDM-IMX91 MPU 36
FRDM-TOUCH Sensor 1
Also available as: FRDM-RW612, FRDM-MCXW71

Also Consider

FRDM-MCXN947 NXP USA Inc. - A more cost-effective choice if application-class Linux processing is not required but high-performance MCU-level edge AI is needed.
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