image model · stable-diffusion · macOS
Can I run Stable Diffusion XL 1.0 on Apple M1 (8GB)?
Needs ~7.5 GB at fp16, but only ~5.5 GB is usable on Apple M1 (8GB). With aggressive CPU offload it can run on as little as ~4 GB, much slower.
Needs ~7.5 GB at fp16, but only ~5.5 GB is usable on Apple M1 (8GB). With aggressive CPU offload it can run on as little as ~4 GB, much slower.
The gap is about 2 GB: Stable Diffusion XL 1.0 needs roughly 7.5 GB and Apple M1 (8GB) leaves only about 5.5 GB usable for a model. The lightest tracked hardware that runs Stable Diffusion XL 1.0 is the Nvidia GeForce RTX 3060 (12GB) at 12 GB. See Stable Diffusion XL 1.0 on Nvidia GeForce RTX 3060 (12GB).
- Peak VRAM
- ~7.5 GB
- Usable on device
- ~5.5 GB
- Device memory
- 8 GB
- Quant
- fp16
- Type
- image (UNET)
- Parameters
- 2.6B
- Peak VRAM
- ~7.5 GB at fp16
- Resolution
- 1024×1024
- License
- CreativeML OpenRAIL++-M
- Memory
- 8 GB unified
- Usable for weights
- ~5.5 GB
- Power draw
- ~39 W
- Best runtime
- Ollama (llama.cpp Metal backend)
What you can run instead
Run Stable Diffusion XL 1.0 on other hardware
FAQ
Can Apple M1 (8GB) run Stable Diffusion XL 1.0?
Needs ~7.5 GB at fp16, but only ~5.5 GB is usable on Apple M1 (8GB). With aggressive CPU offload it can run on as little as ~4 GB, much slower.
How much VRAM does Stable Diffusion XL 1.0 need?
Apple M1 (8GB) does not have enough memory. 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 2026-08-03. See methodology.