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Radxa Dragon Q6A Qualcomm QCS6490 SBC 12 TOPS AI LPDDR5 Octa-Core
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Radxa Dragon Q6A Qualcomm QCS6490 SBC 12 TOPS AI LPDDR5 Octa-Core
Price: CN $389.51
Radxa Dragon Q6A Single Board Computer

Qualcomm QCS6490 Edge AI SBC, 12 TOPS 🚀

Overview

The Radxa Dragon Q6A is a powerful edge AI development board built around the Qualcomm QCS6490 platform. With an octa-core tri-cluster CPU, a flagship-class GPU, and up to 12 TOPS of AI performance, it is designed for demanding edge computing, robotics, computer vision and machine learning projects.

Key Featuresâš¡ Qualcomm QCS6490

Octa-core tri-cluster processor paired with a flagship GPU for demanding compute and graphics workloads.

🧠 12 TOPS AI Performance

Dedicated AI acceleration for on-device machine learning, vision, and edge inference tasks.

💾 LPDDR5 Memory

Available in multiple memory configurations from 4GB up to 16GB LPDDR5 for fast, efficient data handling.

🔌 Rich I/O

Onboard connectivity including USB, Ethernet, and expansion headers as shown in the product photos, suited for embedded and IoT integration.

Choosing Your Option

This listing includes multiple memory configurations of the same Dragon Q6A board. Select the variation matching your required RAM capacity:

Q6A 4GBDragon Q6A board with 4GB LPDDR5 memoryQ6A 6GBDragon Q6A board with 6GB LPDDR5 memoryQ6A 8GBDragon Q6A board with 8GB LPDDR5 memoryQ6A 12GBDragon Q6A board with 12GB LPDDR5 memoryQ6A 16GBDragon Q6A board with 16GB LPDDR5 memory

All variations are the single board only; memory capacity is the only difference between Q6AProcessorQualcomm QCS6490, Octa-Core Tri-Cluster CPUAI PerformanceUp to 12 TOPSMemory TypeLPDDR5Memory Options4GB / 6GB / 8GB / 12GB / 16GBTypical ApplicationEducation, Edge AI, Embedded DevelopmentBattery IncludedNoOriginMainland ChinaProduct ImagesFAQQ: Does this board include a battery?

A: No, the board does not include a battery.

Q: What memory options are available?

A: This board is available in 4GB, 6GB, 8GB, 12GB, and 16GB LPDDR5 configurations, selectable from the variation options.

Q: What is this board best suited for?

A: It is well suited for edge AI applications, embedded development, robotics, and educational projects requiring on-device AI acceleration.



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