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MX3-2280-M-4-C

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See Product Specifications

Mouser No:

89-MX3-2280-M-4-C

Mfr. No:

MX3-2280-M-4-C

Mfr.:

MemryX

Description:

Accelerator Cards The M.2 Module enables high performance, yet power-efficient AI inference for edgedevices and edge servers.

Datasheet:

MX3-2280-M-4-C Datasheet (PDF)

More Information

Learn more about MemryX MX3-2280-M-4-C

Shipping Alert:

Mouser does not presently sell this product in your region.

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Product Attribute	Attribute Value	Select Attribute
Manufacturer:	MemryX
Product Category:	Accelerator Cards
Delivery Restrictions:	Mouser does not presently sell this product in your region.
Form Factor:	M.2 2280-M
Operating Supply Voltage:	3.3 V
Minimum Operating Temperature:	0 C
Maximum Operating Temperature:	+ 70 C
Dimensions:	80 mm x 22 mm
Brand:	MemryX
Moisture Sensitive:	Yes
Product Type:	Accelerator Cards
Factory Pack Quantity:	1
Subcategory:	Embedded Solutions
Unit Weight:	720 g

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Datasheet

MX3-2280-M-4-C Datasheet (PDF)

Compliance Codes

CAHTS:: 8471809900
USHTS:: 8471809000
JPHTS:: 847180000
TARIC:: 8471800000
BRHTS:: 84718000
ECCN:: EAR99

Origin Classifications

Country of Origin:: Taiwan
Assembly Country of Origin:: Not available
Country of Diffusion:: Not available

The country is subject to change at the time of shipment.

M.2 AI Acceleration Module

MemryX M.2 AI Acceleration Module is a cutting-edge solution that brings advanced Artificial Intelligence (AI) processing to edge devices and systems. Powered by four MX-3™ "digital at-memory compute" AI ASICs, this module delivers unparalleled efficiency and performance by processing AI workloads directly within memory, minimizing data movement and latency. This innovative architecture enables real-time inference for complex deep learning models while maintaining low power consumption, making it ideal for applications in industrial automation, smart surveillance, healthcare, and automotive systems. The module's compact M.2 form factor ensures seamless integration into space-constrained devices, providing scalable AI acceleration for various edge computing needs.