IceWhale ZimaCube 2 Personal Cloud NAS review: A modern, high-performance network-attached storage device with plenty of room to grow

by · TechRadar

TechRadar Verdict

Support for up to six hard drives and six NVMe drives gives this platform a broad foundation. Throw in TrueNAS compatibility as an alternative to ZimaOS, and the ZimaCube 2 Personal Cloud NAS has a credible claim on some serious attention.

Pros

  • +Intel i3 CPU
  • +Dual PCIe slots
  • +Thunderbolt 4 ports
  • +Four M.2 slots

Cons

  • -No locks on drive trays
  • -Awkward port locations
  • -M.2 slot speed limitations

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ZimaCube 2: 30-second review

The original ZimaCube was a Kickstarter campaign by IceWhale that delivered a workable NAS with a reasonable specification. Having proven the concept, the ZimaCube 2 Personal Cloud NAS is a direct-to-retail launch that addresses several shortcomings of the original.

Replacing the N100 CPU is a Core i3-1215U, an Intel 12th Generation Alder Lake chip with six cores, eight threads, 20 PCIe 4.0 lanes, and DDR5 memory support.

At $799, it ships with 8GB of RAM and a 256GB NVMe SSD pre-installed, along with ZimaOS already loaded, which can be upgraded to ZimaOS+ for a small fee. Six SATA bays are ready for drives, and four M.2 slots sit in the expansion section for NVMe storage.

That puts it in direct competition with the UGREEN NASync DXP6800 Pro, which costs north of $1,000, though that machine does come with an i5-class CPU.

Where the ZimaCube 2 stands out is its pair of free PCIe slots, which make it straightforward to add 10GbE LAN, a discrete GPU, or additional M.2 capacity. It also accepts up to 32GB of DDR5 memory.

That flexibility extends to software as well. The internal 256GB NVMe drive runs ZimaOS, a Linux-derived NAS platform, but IceWhale also supports TrueNAS for those who prefer it.

On the whole, the ZimaCube 2 addresses many of the complaints levelled at the N100-powered original, while keeping the minimalist styling intact. But with memory and storage prices what they are, is it offering enough performance for buyers looking to run local AI workloads?

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