# NVIDIA DGX Spark vs Strix Halo mini PCs

Explainer · AI PC hardware · 2 min read. By [David Wilson](https://testbenchlab.com/authors/david-wilson/). Updated 2026-10-02.

Choose DGX Spark for a supported CUDA-focused development workflow. For a general x86 Windows or Linux Strix Halo workstation, our preference is Geekom A9 Mega. This is a platform comparison rather than a claimed head-to-head benchmark.

| Requirement | Preferred starting point |
|---|---|
| General x86 Windows/Linux workstation | Geekom A9 Mega |
| Defined CUDA-focused development | NVIDIA DGX Spark |
| Model-fit comparison | Match allocation and context |

## CUDA vs ROCm

DGX Spark targets NVIDIA’s ecosystem, while Strix Halo uses AMD and cross-vendor backends. Dependencies can settle the purchase before specifications do. DGX Spark’s CPU architecture also differs from an x86 desktop; check the whole software stack.

## Memory and bandwidth

NVIDIA lists 128GB unified memory and 273GB/s bandwidth. Compare the exact Strix Halo capacity and allocation. Equal capacity does not imply equal speed, and advertised compute at a particular precision is not a dense-model generation result.

## Price

Compare delivered configurations, storage, tax and support in your country. Launch prices and regional promotions make unqualified dollar comparisons misleading. Keep the intended workload fixed when deciding whether a premium is useful.

## Which should you buy?

Our default is A9 Mega for the general workstation role. Choose DGX Spark for a defined NVIDIA dependency. A personal preference should not override software compatibility that your project genuinely needs.

## Related reading

- [The best Strix Halo mini PCs (Ryzen AI Max+ 395)](https://testbenchlab.com/best/best-strix-halo-mini-pcs/)
- [What is unified memory, and why does it matter for local AI?](https://testbenchlab.com/guides/what-is-unified-memory/)

## Sources

1. [NVIDIA DGX Spark hardware guide](https://docs.nvidia.com/dgx/dgx-spark/hardware.html)
2. [Geekom A9 Mega specifications](https://www.geekompc.com/geekom-a9-mega-ai-mini-pc/)
3. [Ollama hardware support](https://docs.ollama.com/gpu)