Meet Your Seller
M.2 AI Accelerator Module 26TOPS Edge AI Inference Processor 2.5W Low Latency Multi-Stream Multi-Model Processing Supports TensorFlow Lite ONNX Keras PyTorch Linux/Windows
- M.2 AI accelerator module form factor for compatible hardware integration.
- Module only configuration; no additional components are specified.
- Based on a 26 TOPS AI processor for AI inferencing workloads.
- Typical power consumption is 2.5W.
- Scalable design supports simultaneous processing of multiple streams and multiple models.
- Enables real-time, low-latency, high-efficiency AI inferencing on edge devices.
- Supports TensorFlow, TensorFlow Lite, ONNX, Keras, and PyTorch frameworks.
- Compatible with Linux and Windows systems.
- Supports operation across a -40°C to 85°C temperature range.
Any questions? Ask CelesteSM will help you find out quickly.
Product Description:
M.2 AI accelerator module for edge AI inferencing, built on a 26 TOPS AI processor. Designed for real-time, low-latency, and high-efficiency inference workloads.
Core Selling Points:
Supports scalable simultaneous processing of multiple streams and multiple models. Supports TensorFlow, TensorFlow Lite, ONNX, Keras, and Pytorch frameworks.
Technical Specifications:
Form factor: M.2 module. AI processor performance: 26 TOPS. Typical power consumption: 2.5W. Operating temperature range: -40°C to 85°C.
Package Contents:
Module only.
Before Purchase:
Compatible with Linux and Windows systems. Confirm M.2 interface compatibility and supported framework requirements before purchase.
Warranty & Returns
Warranty, Returns, And Additional Information
Warranty
- Please contact the Seller directly for warranty information. Warranty information may also be found on the Manufacturer's website.
- CONTACT
Return Policies
- Return for refund within: 30 days
- Return for replacement within: non-replaceable
- This item is covered by GeekSpace Return Policy
Manufacturer Contact Info
- For a directory of all our manufacturers, please click below.
- Manufacturers Directory















