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image model · stable-diffusion · iOS

Can I run Stable Diffusion 1.5 on iPad Pro M4 (16GB, 1TB/2TB config)?

Compatibility verdict VRAM check
Yes, it runs heavy offloading

Yes. Stable Diffusion 1.5 runs on iPad Pro M4 (16GB, 1TB/2TB config) at fp16 (~3.7 GB of ~12 GB usable).

Needs ~3.7 GB Device usable ~12 GB

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
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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.

Model stable-diffusion
Type
image (UNET)
Parameters
860M
Peak VRAM
~3.7 GB at fp16
Resolution
512×512
License
CreativeML OpenRAIL-M
Full Stable Diffusion 1.5 requirements →
Device iOS
Memory
16 GB unified
Usable for weights
~12 GB
Power draw
~14 W
Best runtime
MLX (via Python or Swift; mlx-lm package)
Best models for iPad Pro M4 (16GB, 1TB/2TB config) →

You could also run

Run Stable Diffusion 1.5 on other hardware

Nvidia GeForce RTX 2060 (6GB)Apple M1 (8GB)iPhone 15 ProiPhone 16iPhone 16 ProiPhone 17

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; catalog updated 2026-10-05. See methodology.