image model · stable-diffusion · iOS
SD Can I run Stable Diffusion 3.5 Large on iPad Pro M4 (16GB, 1TB/2TB config)?
Yes. Stable Diffusion 3.5 Large runs on iPad Pro M4 (16GB, 1TB/2TB config) at Q4 GGUF (~7 GB of ~12 GB usable).
Runs at Q4 GGUF using ~7 GB of ~12 GB usable.
- Peak VRAM
- ~7 GB
- Usable on device
- ~12 GB
- Device memory
- 16 GB
- Quant
- Q4 GGUF
How to run it
Use ComfyUI or Draw Things at Q4 GGUF. The big text encoder is loaded to encode your prompt, then offloaded before generation, which is why peak VRAM stays near the backbone size rather than the sum of every file.
- Type
- image (MMDIT)
- Parameters
- 8.1B
- Peak VRAM
- ~7 GB at Q4 GGUF
- Resolution
- 1024×1024
- License
- Stability Community License
- 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 3.5 Large on other hardware
FAQ
Can iPad Pro M4 (16GB, 1TB/2TB config) run Stable Diffusion 3.5 Large?
Yes. Stable Diffusion 3.5 Large runs on iPad Pro M4 (16GB, 1TB/2TB config) at Q4 GGUF (~7 GB of ~12 GB usable).
How much VRAM does Stable Diffusion 3.5 Large need?
iPad Pro M4 (16GB, 1TB/2TB config) has room to spare. At Q4 GGUF the realistic peak is ~7 GB of VRAM, versus ~19 GB with every component kept resident (no offload). With aggressive CPU offload it drops to ~5 GB, much slower.
What do I use to run Stable Diffusion 3.5 Large locally?
Stable Diffusion 3.5 Large runs in ComfyUI or Draw Things (among others). It loads as a diffusion checkpoint plus its text 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.