BeagleY-AI

schematics

open (schematics + 3D/mechanical files, CC-BY/CC-BY-SA-4.0, OSHWA-certified US002616)

toolchain

open (open Linux/U-Boot BSP)

datasheets

public (public TI AM67A datasheet)

blobs

required (TI DSP/WiFi firmware blobs a caveat)

form_factor

board (SBC sold ready to run, OSHWA-certified as a board)

BeagleY-AI's board design files are published under Creative Commons and OSHWA-certified as US002616, with an open Linux/U-Boot toolchain and a public TI AM67A datasheet. The proprietary AM67A silicon and its DSP/WiFi firmware blobs are the caveat that keeps it short of fully open silicon.

• https://certification.oshwa.org/us002616.html recorded 2026-08-13

  OSHWA UID US002616 for BeagleY-AI by the BeagleBoard.org Foundation, certified March 27 2024, licences recorded as Hardware CC-BY-4.0, Software GPL, Documentation CC-BY-SA-4.0

• https://docs.beagleboard.org/boards/beagley/ai/03-design.html recorded 2026-08-13

  "This work is licensed under a Creative Commons Attribution-ShareAlike 4.0 International License" and "Design materials and license can be found in the BeagleY-AI git repository"; the board carries 2x C7x DSPs with MMA and a Beagle BM3301 wireless module based on the TI CC3301, the two firmware-bearing subsystems behind the recorded blob caveat

• https://github.com/beagleboard/beagley-ai recorded 2026-08-13

  repository under a CC-BY-4.0 license with design and 3D directories and a link to https://certification.oshwa.org/us002616.html

• https://www.ti.com/product/AM67A recorded 2026-08-13

  "AM67x Processors datasheet (Rev. B)" published openly on the part page, status ACTIVE

In stock at $70.00 with volume pricing at Seeed and orderable via TI, backed by the established BeagleBoard.org community, though recent (2024) so installed base trails Raspberry Pi. The AM67A it is built on is ACTIVE at TI with evaluation boards in stock.

• https://www.seeedstudio.com/BeagleYr-AI-beagleboard-orgr-4-TOPS-AI-Acceleration-powered-by-TI-AM67A.html recorded 2026-10-08

  $70.00, "In stock"

4 TOPS plus an IMG BXS GPU suits edge vision and quantized CNNs, but fixed 4GB RAM and modest TOPS rule out large LLMs. The board page reads "Dual general-purpose C7x DSP with Matrix Multiply Accelerator (MMA) capable of 4 TOPs" and 4GB LPDDR4, which sits below the 6 TOPS RK3588 boards and well below the Jetson Orin line.

• https://docs.beagleboard.org/boards/beagley/ai/03-design.html recorded 2026-09-29

  Design page states "BeagleY-AI has 4GB of Kingston x32 LPDDR4 Memory." and "2x C7x DSPs with MMA support are intended for use as Deep Learning Accelerators".

• https://www.beagleboard.org/boards/beagley-ai recorded 2026-09-29

  Board page lists "Dual general-purpose C7x DSP with Matrix Multiply Accelerator (MMA) capable of 4 TOPs" and "4GB LPDDR4".