Highlights
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CPU
Up to 1.4GHz Single Cortex-A55 NXP i.MX91
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High Speed Interfaces
2x USB2.0, 2x GbE
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Certified WiFi/BT
Wi-Fi 6 802.11 ax/ac/a/b/g/n with optional 802.15.4 and BT/BLE 5.4
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Temperature range
-40 to 85°C
security
Security
Security subsystem with cryptographic accelerators
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Product Longevity
2039
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Pin2pin Family
VAR-SOM Pin2Pin family
Learn More
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Support
Supporting you every step of the way - from ideation to launch and beyond. Free and prompt support directly from Variscite’s R&D experts.
Specifications
CPU Name
NXP i.MX 91
CPU Type
Cortex™-A55
CPU Cores
1 core
CPU Clock (Max)
Up to 1.4GHz
Integer performance (DMIPS)
Up to 3,710
RAM
512MB – 2GB LPDDR4
eMMC
8 – 128 GB
Multimedia
Camera Interfaces
8bit Parallel
Display
Parallel RGB
1366x768p60 or 1280x800p60
Touch controller
Resistive, Capacitive
Audio
Headphone driver
Yes
Microphone
Digital, Analog (stereo)
Digital audio serial interface
3 x I2S(SAI),S/PDIF,RX TX, PDM 4CH
Line In/Out
Yes
SD / MMC
x2
USB Host / Device
USB2.0: 2x OTG
UART
x8, up to 5 Mbps
I2C
x7
I3C
x2
SPI
x7
CAN Bus
x2
RTC
On carrier
JTAG
x1
ADC
x4
Networking
Ethernet
2x 10/100/1000 Mbps
Wi-Fi
Certified Wi-Fi 6 dual-band 802.11ax/ac/a/b/g/n with optional 802.15.4, matter
Bluetooth
BT/BLE5.4
Linux
Yocto, Debian
Mechanical Specifications
Dimensions (W x L)
67.8 x 33mm
Electronic Specifications
Supply voltage
3.3V or 3.4-5V
Digital I/O voltage
3.3V/1.8V
Environmental Specifications
Commercial operating temperature
0 to 70°C
Extended operating temperature
-25 to 85°C
Industrial operating temperature
-40 to 85°C
Storage temperature
-40 to 85°C
Storage humidity
5% to 95%
VAR-SOM-MX91S_[xxxx]C_[xxxx]R_[xx]G_[AC]_[EC]_[TP]_[WBD/WBE]_[VBT]_[SDEX]_[X]T
MX91S:
Processor type:
i.MX 9131 single core fully featured
[xxxx]C:
CPU clock speed: 1400MHz: 1400C
[xxxx]R:
LP-DDR4: 512 MB: 512R, 1536 MB: 1536R, 2048 MB: 2048R
[xx]G:
eMMC: 8 GB : 8G, 16 GB : 16G, 32 GB : 32G, 64 GB : 64G
[AC]:
Audio Codec
[EC]:
GbE PHY (second port always via RGMII)
[TP]:
Resistive touch panel controller (note: not available with WBE option)
[WBD/WBE]
WBD: Built-in certified single band Wi-Fi 802.11 ax/ac/a/b/g/n + BT/BLE 5.4
WBE: Built-in certified single band Wi-Fi 802.11 ax/ac/a/b/g/n + BT/BLE 5.4 + 802.15.4
[VBT]
Default: Standard supply voltage
VBT: Higher battery supply voltage
[SDEX]
Default: no additional external SDIO
SDEX: additional external SDIO (available only without WBD/WBE)
[x]T:
C : 0 to 70°C, E: -25 to 85°C, I : -40 to 85°C
Note: All options in [brackets] are optional add-ons that can be either removed or selected from a list of options

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    Why Variscite?

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    Quality
    In-house manufacturing with comprehensive quality control - certified to ISO9001 and ISO13485 medical standards.
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    Pin2Pin
    Our Pin2Pin product families maximize scalability and enable seamless migration to future technologies without redesigning the carrier board.
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    Longevity
    15-year guaranteed hardware availability, backed by continuous software updates and support.
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    Customizability
    Configure your system with precision and flexibility - select only the features you need and reduce costs.
    Updates
    Software releases
    February Software Releases
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    23.02.2026
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    The DART-MX91 leverages NXP’s i.MX91 SoC architecture to provide an ideal solution for IoT, smart cities, connected sensors, portable devices, and industrial applications. Key specifications include:
    19.12.2024
    Blog
    DART-MX93
    This article provides step by step instructions on how to start developing your own Machine Learning (ML) applications using Variscite’s System on Modules. It shows how to build an image using the Yocto Linux BSP with a collection of development tools, utilities, and libraries for building ML applications from the NXP eIQ™ ML Software Development Environment, how to run the default examples built with the image, and finally, how to write a simple ML example from scratch.
    1.1. eIQ™ Machine Learning Software Development Environment Overview
    eIQ™ allows users to easily develop a complete system-level application to solve ML problems related to vision, audio, time-series data and so on. Common examples are face recognition, pose estimation, gesture recognition, speech accents interpretation, etc.
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