Google Coral USB Accelerator Edge TPU, 4 TOPS, USB 3.0, TensorFlow Lite
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Raspberry
GOOGLE CORAL USB
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Competitive EU pricing
Delivered to Cyprus from EU stock
Local warranty support
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Google Coral USB Accelerator Edge TPU - 4 TOPS on-device AI
The Google Coral USB Accelerator adds Edge TPU machine-learning inference to Raspberry Pi and other compatible computers through USB. With up to 4 TOPS of TensorFlow Lite inference performance and 2 TOPS per watt, it is designed for developers building or running supported on-device AI applications.
TensorFlow Lite models
SuperSpeed, 5 Gbps
USB 3.0 / USB 3.1 Gen 1
One available USB port
The Google Coral USB Accelerator adds Edge TPU machine-learning inference to Raspberry Pi and other compatible computers through USB. With up to 4 TOPS of TensorFlow Lite inference performance and 2 TOPS per watt, it is designed for developers building or running supported on-device AI applications.
Best For
✓ A good fit for developers
✓ Armv7, or Armv8 host
Key Features
Commercial Fit
The main reason to choose this accelerator is its dedicated Google Edge TPU, providing up to 4 TOPS of supported TensorFlow Lite inference through a compact USB connection without replacing the host computer.
AI Inference Performance
AI Inference Performance: 4 TOPS
Cable Length
300 mm (12 in) | ±20 mm tolerance | 300 mm (12 in), ±20 mm tolerance
EAN / UPC
EAN / UPC: 0842776110077
Technical Specifications
Frequently Asked Questions
Singular Expert Insight
The main reason to choose this accelerator is its dedicated Google Edge TPU, providing up to 4 TOPS of supported TensorFlow Lite inference through a compact USB connection without replacing the host computer.
Buyer’s Guide
Buy it if
A good fit for developers and makers who need on-device TensorFlow Lite inference on a Raspberry Pi or another compatible x86-64, Armv7, or Armv8 host.
Skip it if
This is an accelerator, not a standalone computer, so a compatible host and an available USB port are required. USB 3.0 is recommended for best performance, and the supported model format is TensorFlow Lite. Check that your operating system and Python version match the listed requirements.
Χαρακτηριστικά
Product Code
CF40122
EAN Code
0842776110077
Manufacturer
Raspberry