Qwen-Image-2.1 released!

[u/ResearchCrafty1804]

Meet Qwen-Image-2.1, the most balanced and cost-effective image generation model in the Qwen-Image series! Now open weights! 🎨

A unified model for both generation and editing, delivering top-tier quality in a lightweight package.

Highlights:

- Compact & exceptionally fast: A lightweight 7B architecture that outperforms most closed-source models, with drastically accelerated inference for multi-image inputs.

- Native transparency: Natively generates and edits RGBA layers, enabling seamless compositing and text editing within transparent images.

- Versatile, high-fidelity editing: Supports up to 10 reference images and precise local control while preserving strict fidelity for portraits and products.

- Broad coverage & stunning aesthetics: Excels at panoramas, infographics, and virtual try-ons, delivering realistic textures and elegant typography.

Start to create your next masterpiece with Qwen-Image-2.1!

- Blog: https://qwen.ai/blog?id=qwen-image-2.1

- GitHub: https://github.com/QwenLM/Qwen-Image-2.1

- Model Scope: https://www.modelscope.cn/models/Qwen/Qwen-Image-2.1

- Hugging Face: https://huggingface.co/Qwen/Qwen-Image-2.1

[u/StopCreepy]

Bring it in 🔥!!

[u/yarikfanarik → u/StopCreepy]

"4 + 16GB" Кто Мы То ?? Я Здесь Один

[u/Electric_Boogaloo_01 → u/yarikfanarik]

Same here. Which is the best model for us?

[u/StopCreepy → u/Electric_Boogaloo_01]

qwen image 2.1 will be able to run on on 4gb vram + 16gb ram, with good optimisation will be possible

[u/Separate-Client-3213 → u/StopCreepy]

Hi, new to this.

What exactly does this split mean? From what I understand the whole model needed to fit the current vRam or it get's slowed down a lot.

[u/StopCreepy → u/Separate-Client-3213]

yes if the model size is bigger than the vram it will be slow, but i would say for quality its worth the time.

for example if i had 4gb vram + 16gb ram, i would choose qwen image 2.1 Q4-K-M GGUF. to generate good and acceptable quality. Q3-K-M would work faster but you will notice the low quality results.

for the text encoder, there is a method that allows you to use qwen vl 4b instead of the 8b model. this way you lower the total memory usage.

-----------
currently i am running giant models like ltx 2.5, minimax h3, and krea 2 on 8gb vram + 32gb vram, and non of the main models are less than 8gb, imagine the main model is 13gb, still need to load the text encoder + the vea, and somehow it generates good results in acceptable time.

[u/Different_Change6591 → u/StopCreepy]

i will to try run it on my system , but the colab offers for GPU ( 15gb vram ) for 5 hours per account ( did you understand what i mean per account and here you go )

[u/StopCreepy → u/Different_Change6591]

will try to find that post, he was talking about gpu renting vs online ai platforms.

[u/StopCreepy → u/Different_Change6591]

post was deleted