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Item #:
104079047
G950-01456-01/ G950-06809-01Coral USB Edge TPU ML Accelerator coprocessor for Raspberry Pi and Other Embedded Single Board Computers
64% of respondents would recommend this to a friend
Item #:
104079047
XPF 18017
Price Details
Excluding Shipping & Custom charges ( Shipping and custom charges will be calculated on checkout )
*All items will import from US
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Imported from USA store
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Order now and get it around Saturday, October 31
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The USB Accelerator brings real-time inference to your Raspberry Pi 4 and many other computers, enabling fast and energy-efficient inference for TensorFlow Lite models.
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What Stands Out
Edge AI Processing
The Coral USB Edge TPU accelerates machine learning applications, offering fast processing speeds ideal for AI tasks on Raspberry Pi and other embedded systems, enhancing performance significantly over standard CPU operations.
Versatile Compatibility
Designed to work seamlessly with Raspberry Pi and various embedded single board computers, this coprocessor provides flexibility, enabling developers to integrate advanced AI features into a wide range of projects effortlessly.
Energy Efficient
With a low power consumption profile, the Coral USB Edge TPU delivers impressive AI capabilities without draining resources, making it perfect for battery-operated devices and energy-conscious applications.
Product Details
| Memory Storage Capacity | 32 GB |
| CPU Model | Google Tensor |
| Connectivity Technology | USB 3.0 |
| Operating System | Linux |
| Processor Brand | YwPulseU |
| Compatible Devices | Raspberry Pi 4, PCs, laptops, tablets |
| RAM Memory Technology | LPDDR4 |
| Processor Count | 4 |
| Total Usb Ports | 1 |
| Brand | YwPulseU |
| Model Name | Coral-USB-Accelerator |
| Built-In Media | 1*USB Accelerator uff1b1*USB 3 cable |
| Number of Packs | 1 |
| Number of Items | 1 |
| Manufacturer | Google Coral |
| Model Number | Coral-USB-Accelerator |
| Mfr Part Number | Coral-USB-Accelerator |
| Item Weight | 0.2 lbs (90 grams) |
Who Should Buy?
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AI Developers
Ideal for developers creating machine learning models needing efficient processing on Raspberry Pi and embedded systems.
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IoT Enthusiasts
Perfect for Internet of Things projects that require real-time data processing and lightweight AI applications on devices.
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Education Projects
Great for educational use, enabling students to explore artificial intelligence and machine learning concepts with hands-on experience.
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General Usage
Not suitable for users needing general computing power; it's specifically designed for machine learning tasks.
Product Description
G950-01456-01/ G950-06809-01Coral USB Edge TPU ML Accelerator coprocessor for Raspberry Pi and Other Embedded Single Board Computers
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Is G950-01456-01/ G950-06809-01Coral USB Edge TPU ML Available to Shop Online in Wallis and Futuna Islands?
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Answer: The delivery time of your ordered product varies as per what you've ordered and the shipping method that you've chosen. The estimated delivery time is mentioned during the checkout process, so be carefree while shopping.
YwPulseU Single Board Computers Coral-USB-Accelerator Editorial Review
The G950-01456-01/ G950-06809-01 Coral USB Edge TPU ML Accelerator is a robust coprocessor designed for Raspberry Pi and other embedded single-board computers. It features a substantial 32 GB memory storage capacity and uses the efficient Google Tensor CPU, ensuring impressive performance for machine learning tasks. This device is compatible with various systems, including Raspberry Pi 4, PCs, and tablets, making it versatile for numerous applications. Users appreciate its USB 3.0 connectivity technology for high-speed data transfer, while the lightweight design at just 0.2 lbs enhances its portability for developers and hobbyists alike.
Customer Reviews & Ratings
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Pros
- High performance with Google Tensor CPU
- Compatible with Raspberry Pi 4 and PCs
- Provides USB 3.0 connectivity
- Lightweight for easy portability
- Ideal for machine learning projects
Cons
- Limited number of USB ports for expansion
Platform Trust & Buyer Confidence
BS
Beat
Verified buyer
“Simple process, tax and import duties announced by email. Paid online. Delivery was quick. Can recommend.”
22 October 2026 · via Trustpilot
S
Songpon
Verified buyer
“The product met my expectations perfectly. The ordering process was convenient and easy, and I was kept updated on the delivery status throughout the shipping process. The delivery was also very fast. I can confidently confirm that Ubuy provides an excellent shopping and delivery experience. Highly recommended! From Thailand”
22 October 2026 · via Trustpilot
D
Dimitra
Verified buyer
“Quick and efficient delivery and the possibility to get the package delivered from a pick-up point. I'm very happy with my experience and would recommend it again!”
22 October 2026 · via Trustpilot
HJ
Heer
Verified buyer
“My product came in good condition from the USA. I was happy that I could buy via this Chanel and that DHL brought it to my house. The communication is fine. The charger works very well. Fast and my Samsung watch and Samsung airbuds and Samsung Fold 8 Ultra all charge fast.”
22 October 2026 · via Trustpilot
SF
Sergey
Verified buyer
“Hello Ubuy team, thank you so much for the excellent service! I received the package today; it arrived in great condition and was packed very neatly. The delivery was fast, and the courier was very friendly as well. Wishing continued success to Ubuy and the entire team!”
23 October 2026 · via Trustpilot
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XPF 18017
Order now and get it around Saturday, October 31
This item is not restrict in my country.(Please click on above link if this item is not restrict in your country, So our team will review and allow.)
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Fastest cross-border delivery
Features & Benefits
- Includes a USB Accelerator and Raspberry Pi 4 (8 GB) for enhanced AI capabilities.
- Achieves real-time inference with low latency and data protection.
- Utilizes a powerful Tensor Processing Unit (TPU) for fast operations.
- Compatible with various host systems including Linux, Mac, and Windows.
- Enables up to 20 times faster performance in AI applications.
- Easy setup with Python and extensive online resources for learning.
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