image model · stable-diffusion · iOS
SD Can I run Stable Diffusion 1.5 on iPad Pro M4 (16GB, 1TB/2TB config)?
Yes. Stable Diffusion 1.5 runs on iPad Pro M4 (16GB, 1TB/2TB config) at fp16 (~3.7 GB of ~12 GB usable).
Runs at fp16 using ~3.7 GB of ~12 GB usable.
- Peak VRAM
- ~3.7 GB
- Usable on device
- ~12 GB
- Device memory
- 16 GB
- Quant
- fp16
How to run it
Use AUTOMATIC1111 or ComfyUI 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.
- Type
- image (UNET)
- Parameters
- 860M
- Peak VRAM
- ~3.7 GB at fp16
- Resolution
- 512×512
- License
- CreativeML OpenRAIL-M
- Memory
- 16 GB unified
- Usable for weights
- ~12 GB
- Best runtime
- MLX (via Python or Swift; mlx-lm package)
You could also run
Run Stable Diffusion 1.5 on other hardware
FAQ
Can iPad Pro M4 (16GB, 1TB/2TB config) run Stable Diffusion 1.5?
Yes. Stable Diffusion 1.5 runs on iPad Pro M4 (16GB, 1TB/2TB config) at fp16 (~3.7 GB of ~12 GB usable).
How much VRAM does Stable Diffusion 1.5 need?
iPad Pro M4 (16GB, 1TB/2TB config) has room to spare. At fp16 the realistic peak is ~3.7 GB of VRAM, versus ~4 GB with every component kept resident (no offload). With aggressive CPU offload it drops to ~2 GB, much slower.
What do I use to run Stable Diffusion 1.5 locally?
Stable Diffusion 1.5 runs in AUTOMATIC1111 or ComfyUI (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.