image model · qwen · Windows
Can I run Qwen-Image on Nvidia GeForce RTX 3060 (12GB)?
Needs ~14 GB at Q4_K_M GGUF, but only ~11 GB is usable on Nvidia GeForce RTX 3060 (12GB). With aggressive CPU offload it can run on as little as ~3 GB, much slower.
Needs ~14 GB at Q4_K_M GGUF, but only ~11 GB is usable on Nvidia GeForce RTX 3060 (12GB). With aggressive CPU offload it can run on as little as ~3 GB, much slower.
- Peak VRAM
- ~14 GB
- Usable on device
- ~11 GB
- Device memory
- 12 GB
- Quant
- Q4_K_M GGUF
- Type
- image (MMDIT)
- Parameters
- 20B
- Peak VRAM
- ~14 GB at Q4_K_M GGUF
- Resolution
- 1328×1328
- License
- Apache-2.0
- Memory
- 12 GB vram
- Usable for weights
- ~11 GB
- Best runtime
- Ollama (CUDA) / llama.cpp CUDA
What you can run instead
Run Qwen-Image on other hardware
FAQ
Can Nvidia GeForce RTX 3060 (12GB) run Qwen-Image?
Needs ~14 GB at Q4_K_M GGUF, but only ~11 GB is usable on Nvidia GeForce RTX 3060 (12GB). With aggressive CPU offload it can run on as little as ~3 GB, much slower.
How much VRAM does Qwen-Image need?
Nvidia GeForce RTX 3060 (12GB) does not have enough memory. 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.