Raspberry Pi announced today the highly anticipated 16GB model of the Raspberry Pi 5 single-board computer, designed for those who need more memory for a faster and smoother computing experience. Previously, the Raspberry Pi 5, which launched at the end of October 2023, was available in only three variants: 2GB, 4GB, and 8GB RAM. Now, this new 16GB model sits at the top of the Pi 5 lineup.
When it was first released, the Raspberry Pi 5 delivered a significant upgrade over its predecessors, thanks to the considerably more powerful Broadcom BCM2712 system-on-chip and a user-accessible PCI Express lane for high-speed storage or artificial intelligence accelerators. However, one feature many users were asking for was more memory. And thanks to the optimized D0 stepping of the Broadcom BCM2712 application processor in the Raspberry Pi 5, that is now possible.
The Raspberry Pi 5 16GB model will cost you $120
Raspberry Pi has decided to make the leap to 16GB to position the Raspberry Pi 5 as a viable option for those working with more memory-demanding tasks, such as running large language models, computational fluid dynamics, and other memory-intensive applications. CEO of Raspberry Pi Holdings, Eben Upton, sheds light on this development, stating:
We’re continually surprised by the uses that people find for our hardware. Many of these fit into 8GB (or even 2GB) of SDRAM, but the threefold step up in performance between Raspberry Pi 4 and Raspberry Pi 5 opens up use cases like large language models and computational fluid dynamics, which benefit from having more storage per core
CEO of Raspberry Pi Holdings, Eben Upton
As for pricing, the Raspberry Pi 5 with 16GB will be available at a slightly higher cost than the 8GB variant, priced at $120. While its value proposition might be confusing for some—since apart from the 16GB RAM, the board itself is largely unchanged from the previous Raspberry Pi 5 revision, featuring the same hardware and peripherals as its smaller siblings—power users and professionals dealing with tasks like desktop computing, AI processing, and containerized workloads will likely appreciate the extra memory.
