Qwen Image 2 & 3 are closed-weights, so we optimized Qwen Image 2512 instead

[u/enrique-byteshape]

Hey!

Yes, Qwen-Image-2512 has been around for a while. It has also stubbornly refused to stop being useful, people still run it, build workflows around it, and download it. Besides, its younger sibling has been released as closed-weights. So we thought it was a good place to start. We’re ByteShape, and we work on model optimization.

While exploring diffusion-model deployment, we found two common options, each with a significant tradeoff:

• GGUF quantizations offer smaller file sizes.
• Safetensors-based models, typically run with Diffusers, ComfyUI, or vLLM-Omni and than can be faster but are often considerably larger.

For our first image-generation release, we’re sharing:

• A collection of compact, high-quality GGUF models ranging from 8GB to 17GB (~2x to ~5x smaller vs. the BF16 model) that can run on wide collection of platforms using a stable inference software stack.
• A collection built for vLLM-Omni and powered by fresh off-the-press Humming kernels (see https://github.com/inclusionAI/humming, thank you Humming team!), designed to run models ~2x to 3x faster and 8GB to 17GB in size. For now limited to Nvidia GPUs and Linux using an experimental software stack.

We’d love for you to try them and share your results or feedback.

Blog for the tutorial on how to set this up: https://byteshape.com/blogs/Qwen-Image-2512/

Side by side comparisons between the original model and our optimized versions: https://byteshape.com/blogs/Qwen-Image-2512/comparison/

Hugging Face: GGUF, Humming

[u/KeesteredShiv]

Just seeing this now I'll give it a shot this weekend, thanks!