# What is unified memory, and why does it matter for local AI?

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

Unified memory is a shared physical pool that multiple processors can access. For local AI, its attraction is capacity: an integrated GPU can potentially work with more model data than a small graphics card holds. Allocation and software still set limits.

## What is unified memory?

The CPU and integrated accelerator share a memory system rather than relying on entirely separate physical RAM banks. Details vary by platform. The operating system, applications and model runtime still compete for capacity and bandwidth.

## Unified memory vs VRAM

Dedicated VRAM belongs to a graphics card; unified memory also serves ordinary system work. Equal capacity is not equivalent performance. A large shared pool is valuable for fit, while a smaller fast card can excel on a workload that fits its memory.

## How much of the memory can the GPU use on Strix Halo?

The GPU-visible amount depends on firmware, capacity and drivers. A 128GB listing does not supply 128GB exclusively for model weights. Inspect the runtime’s allocation and leave room for the operating system, context and temporary buffers.

## Unified memory on Mac vs AMD

Mac workflows commonly use Metal or MLX; AMD systems use supported Vulkan, ROCm or other backends. Choose the software environment first. A similar memory number does not make applications and model formats interchangeable.

## Frequently asked questions

### Is unified memory the same as VRAM?

No. It can serve graphics workloads but remains a shared system pool rather than separate card memory.

### What does "96GB VRAM" mean on a mini PC?

It usually describes an allocation from shared memory. Confirm the platform and settings rather than assuming separate physical graphics memory.

## Related reading

- [Geekom A9 Mega (Ryzen AI Max+ 395) review](https://testbenchlab.com/reviews/geekom-a9-mega-review/)
- [Minisforum MS-S1 Max review](https://testbenchlab.com/reviews/minisforum-ms-s1-max-review/)
- [GMKtec EVO-X2 review](https://testbenchlab.com/reviews/gmktec-evo-x2-review/)
- [The best Strix Halo mini PCs (Ryzen AI Max+ 395)](https://testbenchlab.com/best/best-strix-halo-mini-pcs/)
- [How much RAM do you need to run a local LLM?](https://testbenchlab.com/guides/how-much-ram-for-local-llm/)

## Sources

1. [AMD Ryzen AI Max specifications](https://ir.amd.com/news-events/press-releases/detail/1232/amd-announces-expanded-consumer-and-commercial-ai-pc-portfolio-at-ces)
2. [Ollama hardware support](https://docs.ollama.com/gpu)
3. [Apple Mac mini specifications, 2024 models](https://support.apple.com/en-gb/121555)