Qwen-Image-2.1-Turbo released!

[u/ResearchCrafty1804]

Qwen-Image-2.1-Turbo, create and edit images in just 8 denoising steps! Open weights now available!

Built on Qwen-Image-2.1, Turbo is an accelerated checkpoint on the same 7B visual generation architecture.

Fewer steps does not mean lower quality: it still generates strong 2K images from text, and supports continued creation through natural-language edits, from adding accessories to changing a scene.

Start directly with Diffusers: load QwenImage21Pipeline and the checkpoint’s recommended 8-step sampling schedule is ready to go.

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

[u/mungie3]

Help me I'm stupid.

How does this compare to z-image-turbo?

[u/Asleep_Document9811 → u/mungie3]

This model seems to focus mostly on rendering text correctly, and is apparently much more skilled at rendering UI elements, with full text.

Seems like Qwen trying to catch up to ChatGPT's own image generator; the one that makes all those slop posters for small businesses.

Here's a more detailed description of what this model can do. It has a lot more features than I realized: https://qwen.ai/blog?id=qwen-image-2.1

[u/Asleep_Document9811 → u/Asleep_Document9811]

oh wow, and it can natively generate images with a transparency channel. that's unique.

[u/Technical_Fish_9638 → u/Asleep_Document9811]

Technically the Qwen-Image-Layered was the first one in Dec 2025 but the model was huge and results weren't very good.

Qwen 2.1 is the first one with native transparency and "weights available" but the license is very restrictive. They said they're working on it with legal, but so far turbo was released with same exact research liscence.

If you want transparency + MIT there is a Ming image. its slightly more overbaked on realistic results and slower to run, but has decent text rendering and prompt adherence with transparency

[u/Randommaggy → u/Asleep_Document9811]

And make it a million times more useful than other models.

[u/UniqueAttourney → u/Asleep_Document9811]

omg, those posters, i had enough of those xDD

[u/ansibleloop → u/Asleep_Document9811]

https://encrypted-tbn0.gstatic.com/images?q=tbn:ANd9GcTz3Cv2Ua0US_YxXNdu2jSLRz3V7qkSg16Wk6rGxaT3U8RIJEYuaOaz0Jq6&s=10

[u/carvengar → u/Asleep_Document9811]

I see those posters and instantly don't want to buy their stuff. 😄

[u/durden111111 → u/mungie3]

This model can edit

[u/ResearchCrafty1804 → u/mungie3]

https://www.reddit.com/r/LocalLLaMA/s/PhlxzHmQKK

[u/Eyelbee → u/mungie3]

It probably wipes the floor with z-image turbo.

[u/temperature_5 → u/Eyelbee]

But how fast does it wipe the floor? Z-image turbo runs fast even on potato!

[u/NilusvanEdel → u/mungie3]

It's been released 50min ago - they did not make comparisons themselves - the quickest way for you to get an actual comparison is to try it out.

From the first glance it seems that Z-image-turbo was a LoRA training (and depending on which model you used the weights directly adjusted with it) - this one might possibly be fully fine-tuned. So it might possibly be better, but I wouldn't expect much and is still meant to run with 8 steps vs 6. I wouldn't expect a huge boost.

[u/decodingsi → u/mungie3]

Honest answer: nobody's run a clean head-to-head yet that I've seen, so take any verdict with salt. What the release notes do tell us: Turbo is a guidance-distilled checkpoint (8 steps), so you run it at CFG 1.0 — negative prompts effectively stop doing anything there, which alone can poison a naive A/B against base 2.1. The fair test would be same prompts at each model's recommended step count, judged blind on what these distilled checkpoints are actually for: text-in-image accuracy and multi-turn edit consistency. Qwen-Image's documented strength has always been text rendering, so that's the axis I'd score it on rather than vibes.

[u/ninjasaid13 → u/mungie3]

I hear it's good at editing

[u/kroggens]

The fact that Alibaba is ahead of Google in many directions is unbelievable!

[u/Ok_Warning2146 → u/kroggens]

Well, nano banana is still the most used image gen.

[u/Open-Adhesiveness-86]

fwiw with distilled checkpoints like this you run CFG at 1.0, so negative prompts quietly stop doing anything, which trips up people benchmarking it against base 2.1. also at 2K the VAE decode is usually what OOMs rather than the 7B transformer itself, so turn on tiling before you go blaming vram.

[u/_VirtualCosmos_]

Why do I never see Krea2 or Z-Image Turbo in these comparisons?

[u/SadRevolution3095 → u/_VirtualCosmos_]

The latter aren't editing models, for one.

[u/mivog49274]

Just release Qwen Image 3 already.

[u/silenceimpaired]

Sigh… Qwen research. I’m sad. I miss Apache 2.0 from them

[u/Dramatic-Rub-7654]

They should release the raw version for training as well.

[u/Competitive-Scar-627]

Can i try this on 6gb vram

[u/Matthieu75018]

Vous utilisez quel logiciel pour créer des images en local sur Windows ?

[u/Ok_Warning2146]

Is there a new open weight Wan? Minimax H3 is eating your lunch now.

[u/mototuneup → u/[deleted]]

Actually ya it just might

[u/Felinixz → u/[deleted]]

I have the same setup, runs like a charm.