Quantization / SOURCE CHECKED 12 OCT 2026
Qwen-Image GGUF
Before you download.
Abiray publishes GGUF quantizations for the Qwen image pipeline. They use a compatible ComfyUI-GGUF loader, plus separate text encoder and VAE files.
Local setup checklist
- Review the base model licence and the quantization repository’s current instructions.
- Choose a quantization for your available memory, then install the documented ComfyUI-GGUF node from its official source after reviewing its code.
- Place the GGUF diffusion file in the directory expected by your loader. Download the matching encoder and VAE separately.
- Load the included workflow and run a small test. Keep a higher-quality reference when comparing quantization effects.
Memory and limitations
Publisher lists Q4_K_M as 4.19 GB and recommends 6–8 GB VRAM. These are publisher estimates, not our hardware test; workload and offloading change requirements.
Licence before use
Qwen Research — review full terms. Check the full current licence; labels alone do not establish commercial permission.
Frequently asked questions
Can I load this in a chat app?
GGUF is a format, not a compatibility guarantee. This is an image diffusion checkpoint requiring a compatible image pipeline.
Does a 4.19 GB file need only 4.19 GB VRAM?
No. Other pipeline components and runtime tensors also consume memory.
Primary source
Publisher model card and files ↗
Guidance is based on the source review, not our own inference benchmark. No user files or prompts are sent to a model by this site.
← Explore other workflows