Arm’s edge AI platform features the Cortex-A320 CPU and Ethos-U85 NPU, enabling on-device execution of models exceeding 1 billion parameters. The Armv9 platform enhances efficiency, performance, and security for IoT, while unlocking new edge AI applications through support for both large and small language models.
Built on the Armv9 architecture, the Cortex-A320 delivers 10× higher ML performance and 30% better scalar performance than its predecessor, the Cortex-A35. It also achieves an 8× ML performance gain over the Cortex-M85-based platform launched last year. Additionally, Armv9.2 offers advanced security features like pointer authentication, branch target identification, and memory tagging extension.
The Cortex-A320 pairs with the Ethos-U85 AI accelerator, which supports transformer-based models at the edge and scales from 128 to 2048 MAC units. To streamline edge AI development, Arm’s Kleidi for IoT compute libraries enhance AI an ML performance on Arm-based CPUs with seamless ML framework integration. For example, Kleidi boosts Cortex-A320 performance by up to 70% when running Microsoft’s Tiny Stories dataset on Llama.cpp.
To learn more about the Armv9 edge AI platform, click on the product page links below.
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