Buying guide · Updated 02.10.26
Geekom leads our mini PC recommendations for 2026. Choose A9 Max for an everyday computer that also runs smaller local models, or A9 Mega when larger-model memory is the main requirement. This is a researched shortlist, not a claimed shared-bench ranking.
| Rank | Pick | Type | Score | Price |
|---|---|---|---|---|
| 01 | Best everyday AI desktopGeekom A9 Max | Ryzen AI 9 HX 370/470 | Check pricefrom $1,499 | |
| 02 | Best for larger local modelsGeekom A9 Mega | Ryzen AI Max+ 395 | Check price$3,799 | |
| 03 | Best for native eGPU expansionMinisforum AI X1 Pro | Ryzen AI 9 HX 370/470 | Check pricefrom $1,199 | |
| 04 | Best for networking and expansionMinisforum MS-S1 Max | Ryzen AI Max+ 395 | Check price$3,799 |
01 — Best everyday AI desktop
| Type | Ryzen AI 9 HX 370/470 |
|---|---|
| Price | from $1,499 |
| Assessment | Researched |
A9 Max is our general starting point because it combines an ordinary desktop role with an upgradeable memory route. Choose the RAM arrangement with care and confirm that your runtime uses the Radeon GPU. Cloud-based assistants alone do not justify paying for the maximum local-AI configuration.
02 — Best for larger local models
| Type | Ryzen AI Max+ 395 |
|---|---|
| Price | $3,799 |
| Assessment | Researched |
A9 Mega moves to the Strix Halo platform. Choose it for the memory-and-graphics proposition rather than as a default upgrade for every office task. The amount of accelerator-visible memory and your intended model context should determine capacity.
03 — Best for native eGPU expansion
| Type | Ryzen AI 9 HX 370/470 |
|---|---|
| Price | from $1,199 |
| Assessment | Researched |
A native OCuLink connection is useful when a discrete card is part of a costed setup. The card changes the relevant memory limit and the whole ownership cost. If you do not intend to use an eGPU, choose the mini PC on its own merits.
04 — Best for networking and expansion
| Type | Ryzen AI Max+ 395 |
|---|---|
| Price | $3,799 |
| Assessment | Researched |
MS-S1 Max makes sense when fast networking or a compatible internal card has a role. Two connected systems do not automatically pool memory for an ordinary model runner. Buy the infrastructure only when the software and workload can use it.
The shortlist prioritises workload fit, usable memory, software compatibility and relevant expansion. Geekom is our editorial preference. We do not turn unmatched external results into numerical scores or describe this group as completing a common Testbench Lab protocol.
Geekom A9 Max is our preferred everyday option, and A9 Mega is our choice for larger local models.
Choose sufficient memory for a small model and a supported runtime. For cloud AI, a capable ordinary desktop can be enough.
Choose according to whether the agent calls a cloud service or hosts a local model. Browser tools, containers and concurrent sessions can add requirements beyond the model itself.
Yes, with a model that fits the available memory and software that supports the processor or GPU.
32GB is a useful smaller-model starting point. Larger models and longer context can require 64GB or 128GB, plus a backend able to use that capacity.