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image model · stable-diffusion · macOS

Can I run Stable Diffusion 3.5 Large on Apple M1 (8GB)?

Compatibility verdict VRAM check
No, not enough memory would not load

Needs ~7 GB at Q4 GGUF, but only ~5.5 GB is usable on Apple M1 (8GB). With aggressive CPU offload it can run on as little as ~5 GB, much slower.

Needs ~7 GB Device usable ~5.5 GB

Needs ~7 GB at Q4 GGUF, but only ~5.5 GB is usable on Apple M1 (8GB). With aggressive CPU offload it can run on as little as ~5 GB, much slower.

The gap is about 1.5 GB: Stable Diffusion 3.5 Large needs roughly 7 GB and Apple M1 (8GB) leaves only about 5.5 GB usable for a model. The lightest tracked hardware that runs Stable Diffusion 3.5 Large is the Nvidia GeForce RTX 3060 (12GB) at 12 GB. See Stable Diffusion 3.5 Large on Nvidia GeForce RTX 3060 (12GB).

Peak VRAM
~7 GB
Usable on device
~5.5 GB
Device memory
8 GB
Quant
Q4 GGUF
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Model stable-diffusion
Type
image (MMDIT)
Parameters
8.1B
Peak VRAM
~7 GB at Q4 GGUF
Resolution
1024×1024
License
Stability Community License
Full Stable Diffusion 3.5 Large requirements →
Device macOS
Memory
8 GB unified
Usable for weights
~5.5 GB
Power draw
~39 W
Best runtime
Ollama (llama.cpp Metal backend)
Best models for Apple M1 (8GB) →

What you can run instead

Run Stable Diffusion 3.5 Large on other hardware

FAQ

Can Apple M1 (8GB) run Stable Diffusion 3.5 Large?

Needs ~7 GB at Q4 GGUF, but only ~5.5 GB is usable on Apple M1 (8GB). With aggressive CPU offload it can run on as little as ~5 GB, much slower.

How much VRAM does Stable Diffusion 3.5 Large need?

Apple M1 (8GB) does not have enough memory. 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 2026-08-03. See methodology.