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localmodel.run

image model · stable-diffusion · macOS

SD Can I run Stable Diffusion XL 1.0 on Apple M3 Ultra (256GB)?

Compatibility verdict VRAM check
Yes, it runsmoderate speed

Yes. Stable Diffusion XL 1.0 runs on Apple M3 Ultra (256GB) at fp16 (~7.5 GB of ~192 GB usable).

Needs ~7.5 GB Device usable ~192 GB

Runs at fp16 using ~7.5 GB of ~192 GB usable.

Peak VRAM
~7.5 GB
Usable on device
~192 GB
Device memory
256 GB
Quant
fp16

How to run it

Use ComfyUI or AUTOMATIC1111 / Forge at fp16. It conditions on an image, not a text prompt; the pipeline offloads each stage off the GPU between passes, keeping peak VRAM near the active stage.

Model stable-diffusion
Type
image (UNET)
Parameters
2.6B
Peak VRAM
~7.5 GB at fp16
Resolution
1024×1024
License
CreativeML OpenRAIL++-M
Full Stable Diffusion XL 1.0 requirements →
Device macOS
Memory
256 GB unified
Usable for weights
~192 GB
Best runtime
MLX direct / Ollama (MLX backend)
Best models for Apple M3 Ultra (256GB) →

You could also run

Run Stable Diffusion XL 1.0 on other hardware

FAQ

Can Apple M3 Ultra (256GB) run Stable Diffusion XL 1.0?

Yes. Stable Diffusion XL 1.0 runs on Apple M3 Ultra (256GB) at fp16 (~7.5 GB of ~192 GB usable).

How much VRAM does Stable Diffusion XL 1.0 need?

Apple M3 Ultra (256GB) has room to spare. At fp16 the realistic peak is ~7.5 GB of VRAM, versus ~8.5 GB with every component kept resident (no offload). With aggressive CPU offload it drops to ~4 GB, much slower.

What do I use to run Stable Diffusion XL 1.0 locally?

Stable Diffusion XL 1.0 runs in ComfyUI or AUTOMATIC1111 / Forge (among others). It loads as a diffusion checkpoint plus its image encoder and VAE, not a single chat command.

Sources

VRAM figures are sourced peak-usage anchors at the noted quant, validated 2026-06-15. See methodology.