Hailo-8 M.2 AI Accelerator Module Compatible with Raspberry Pi 5 Support Linux/Windows Systems Based On The 26TOPS Hailo-8 AI Processor
TTD 1872
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Unlock unprecedented AI performance for your edge devices with the Hailo-8 M.2 module, delivering 26 TOPS and 2.5W power consumption.
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Product Details
| Item Weight | 0.2 lbs (90 grams) |
Who Should Buy?
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AI Enthusiasts
Users interested in developing AI applications can leverage the Hailo-8's powerful processing capabilities for innovative projects.
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Developers
Software developers can utilize this module for prototyping and testing machine learning models using Raspberry Pi 5 environments.
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Educational Institutions
Schools and universities can use this accelerator for teaching AI and machine learning concepts in hands-on projects.
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Casual Users
Individuals who are not tech-savvy may find it challenging to set up and utilize this advanced AI module effectively.
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Basic Computing Needs
Users seeking simple computing tasks will not benefit from the high-performance capabilities that the Hailo-8 module offers.
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Budget-Conscious Buyers
This product may not be suitable for users on a tight budget, as advanced AI hardware often comes with a premium price.
Product Description
Hailo-8 M.2 AI Accelerator Module Compatible with Raspberry Pi 5 Support Linux/Windows Systems Based On The 26TOPS Hailo-8 AI Processor
Customer Questions & Answers
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Question:
What is the power consumption of the Hailo-8 M.2 module?
Answer: The typical power consumption is 2.5W, with a maximum of 8.65W. -
Question:
Which AI frameworks are supported by this module?
Answer: It supports TensorFlow, TensorFlow Lite, ONNX, Keras, and Pytorch frameworks. -
Question:
What temperature range can the Hailo-8 module operate in?
Answer: It can operate in a temperature range of -40°C to 85°C.
Unistorm Internal Components Editorial Review
The Hailo-8 M.2 AI Accelerator Module has garnered a positive reception from users, particularly those who are integrating it into their existing systems like Raspberry Pi 5. The performance aspects stand out, especially its capacity for image analysis and inference tasks, which the device handles impressively. Users have noted how it significantly alleviates CPU load, particularly in applications such as video detection via Frigate, highlighting its efficiency and speed during inference. Setting up the Hailo-8 with platforms such as Proxmox and Debian seems to be manageable, though it may require some technical know-how to navigate driver installation and configuration. Users mentioned the need for manual updates to device IDs within Proxmox, which could pose a challenge for less experienced users. Furthermore, while the base software is open-source, the proprietary nature of some necessary code and file formats may limit accessibility for developers who rely on fully open-source solutions. Overall, the customer experience indicates a robust tool for specific AI applications, especially in image processing, provided that users are prepared to engage with some of its technical complexities. **
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Pros
- Excellent performance for image analysis and inference tasks.
- Reduces CPU load significantly when integrated with applications like Frigate.
- Fast processing speed with provided code and libraries.
Cons
- Technical setup may require effort and knowledge, particularly with driver installation.
Product Price History
Important information
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TTD 1872
Order now and get it around Monday, June 29
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Ubuy works hard to protect your security and privacy. Our advanced payment security system ensures confidentiality by encrypting your information during transmission using AES (Advanced Encryption Standards) and SSL (Secure Socket Layer) protocols. Your payment details are 100% secure as we do not share your payment details with third party sellers.
Features & Benefits
- Delivers 26 Tera-Operations Per Second (TOPS) for unmatched AI performance.
- Consumes just 2.5W of typical power, ensuring high efficiency.
- Supports multi-stream and multi-model processing for real-time AI inferencing.
- Compatible with major AI frameworks like TensorFlow, Pytorch, and Keras.
- Designed for extreme conditions, operating in -40°C to 85°C temperature range.
- Easy integration with existing devices through PCIe Gen3 interface.