---
title: "A Renesas RZ/V2N-based SoM and carrier board for Vision AI applications"
url: https://daily.dev/posts/a-renesas-rz-v2n-based-som-and-carrier-board-for-vision-ai-applications-9ofna9cii
source_url: https://www.cnx-software.com/2026/08/26/banana-pi-bpi-ai2n-a-renesas-rz-v2n-based-som-and-carrier-board-for-vision-ai-applications
type: article
source: "CNX Software"
author: "CNXSoft"
published: 2026-08-26T10:57:53.840Z
updated: 2026-08-27T07:00:31.264Z
tags: ["hardware", "embedded", "local-ai"]
reading_time: 4
upvotes: 0
comments: 0
language: en
---

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# A Renesas RZ/V2N-based SoM and carrier board for Vision AI applications

**[CNX Software](https://daily.dev/sources/cnx-software)** · [@cnxsoft](https://daily.dev/cnxsoft) · 4 min read · 0 upvotes · 0 comments

## Summary

Banana Pi has released the BPI-AI2N, a system-on-module built around the Renesas RZ/V2N quad-core Cortex-A55 processor with a DRP-AI3 accelerator delivering up to 15 sparse TOPS for vision AI workloads. The module packs 8GB LPDDR4x, 32GB eMMC, dual Gigabit Ethernet, and a 260-pin SO-DIMM connector, paired with a Jetson Nano-styled carrier board offering MIPI DSI/CSI connectors, M.2 NVMe storage, USB 3.0 ports, and a 40-pin GPIO header. Despite the visual similarity, it is not pin-compatible with Jetson Nano/NX boards. Documentation includes Yocto and Armbian images based on Linux 6.1, though a third-party review notes the fan and camera don't work properly on Armbian. Pricing starts at $266 for the SoM and $26.70 for the carrier board, sold via AliExpress. The carrier board will also support an upcoming higher-performance RZ/V2H-based module.

## Full article

daily.dev links to this article rather than hosting it. Read it at the original source: <https://www.cnx-software.com/2026/08/26/banana-pi-bpi-ai2n-a-renesas-rz-v2n-based-som-and-carrier-board-for-vision-ai-applications>

## Questions this post answers

### What is the AI performance of the Renesas RZ/V2N used in the Banana Pi BPI-AI2N module?

The Renesas RZ/V2N's DRP-AI3 accelerator delivers up to 4 dense TOPS or 15 sparse TOPS for vision AI workloads. It pairs with a quad-core Arm Cortex-A55 CPU at 1.8 GHz, an Arm Cortex-M33 at 200 MHz, and an Arm Mali-G31 GPU supporting OpenGL ES 3.2 and OpenCL 2.0 FP.

_Developers evaluating edge AI hardware compare accelerator specs like these on daily.dev._

### Is the Banana Pi BPI-AI2N carrier board compatible with NVIDIA Jetson Nano modules?

No, despite visually resembling a Jetson Nano carrier board, the BPI-AI2N module and carrier board are not compatible with the Jetson Nano or Jetson NX pinout. The carrier board is instead designed to also support the upcoming Renesas RZ-V2H-based Banana Pi BPI-AI2H module, which will offer higher AI performance of up to 80 sparse TOPS.

_Anyone weighing Jetson alternatives can track hardware compatibility details like this on daily.dev._

### How much does the Banana Pi BPI-AI2N vision AI module cost?

The BPI-AI2N-Core system-on-module sells for $266, while the matching carrier board costs $26.70, both via AliExpress. Additional accessories include a heatsink and fan combo for $6.70, a camera module for $21.28, and an optional MIPI to HDMI adapter board for $14.36.

_Builders pricing out vision AI hardware follow board launches and costs like these on daily.dev._

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---

Tags: [#hardware](https://daily.dev/tags/hardware), [#embedded](https://daily.dev/tags/embedded), [#local-ai](https://daily.dev/tags/local-ai)

[View this post on daily.dev](https://daily.dev/posts/a-renesas-rz-v2n-based-som-and-carrier-board-for-vision-ai-applications-9ofna9cii)
