image model · qwen · macOS
Can I run Qwen-Image on Apple M3 Ultra (256GB)?
Yes. Qwen-Image runs on Apple M3 Ultra (256GB) at Q4_K_M GGUF (~14 GB of ~192 GB usable).
Runs at Q4_K_M GGUF using ~14 GB of ~192 GB usable.
- Peak VRAM
- ~14 GB
- Usable on device
- ~192 GB
- Device memory
- 256 GB
- Quant
- Q4_K_M GGUF
How to run it
Use ComfyUI or Nunchaku (SVDQuant 4-bit) at Q4_K_M 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
- 20B
- Peak VRAM
- ~14 GB at Q4_K_M GGUF
- Resolution
- 1328×1328
- License
- Apache-2.0
- Memory
- 256 GB unified
- Usable for weights
- ~192 GB
- Best runtime
- MLX direct / Ollama (MLX backend)
You could also run
Run Qwen-Image on other hardware
FAQ
Can Apple M3 Ultra (256GB) run Qwen-Image?
Yes. Qwen-Image runs on Apple M3 Ultra (256GB) at Q4_K_M GGUF (~14 GB of ~192 GB usable).
How much VRAM does Qwen-Image need?
Apple M3 Ultra (256GB) has room to spare. At Q4_K_M GGUF the realistic peak is ~14 GB of VRAM, versus ~57 GB with every component kept resident (no offload). With aggressive CPU offload it drops to ~3 GB, much slower.
What do I use to run Qwen-Image locally?
Qwen-Image runs in ComfyUI or Nunchaku (SVDQuant 4-bit). 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.