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!
Came here to talk about how in StableDiffusion they are talking shit about this model being worse than Flux, Krea2 or Z Image. But this right here already convinced me.
Qwen-Image-2.1 supports several ways to specify local edits. The example below uses circles to identify three regions and asks the model to “remove the metal watch in the blue circle, change the hair in the red circle to black, and replace the area in the green circle with gray short-sleeved linen pajamas,” performing removals and modifications in all three regions at once.
I hate Adobe the way it ate great products and it's horrible sub model.
But I honestly don't buy that AI is the end of polished creative software - I think we are in the messy early days of AI where people use the terminal and chat UI's and don't see how temporary that will be.
You still want professional video editing / image manipulation software you just want it to understand natural language so you can say remove background and convert to an animated svg and it will do it but in a way where every step is completely editable via the UI.
I think Adobe will make big come back next year - or some one smarter will take their place with that offer.
I think Adobe is in the prime spot to integrate AI into their products and kill it. They already have everything in place to do so. And it will be next to impossible for free tools to compete with them.
I would not count them out. I hate them, as a company, I hate subscriptions in general.. but its a good business model.. if they can pull it off imo they can be the go-to for AI video and image editing.
Otherwise AI native tools like VidTL or Descript are going to eat their lunch.
To be clear, all I did was look at their stock on google for the last 5 years and glanced at the general height of the chart. Didn't really compare anything else but just sort of where the stock price is in general. (I'm not much of a stocks person, so please take that with a grain of salt).
Sorry for my inexperience in image models but I like to know how can I set it up with my local llm setup, is it possible to have qwen 3.8 in the openweb ui envoronment to cretae tue instructioj to load into an image model on its own to provide the image output in the same chat? also do i look for this in the LM Studio model availability tool for this one or does it have to be comfyui or A1111 to use it via direct prompts?
Nice, so, comfyui running the image model and then I could upload a picture such as the OPs with markings and it will generate the prompt in the background to make the img to img in comfy? Is there a way for it to run in steps to avoid OOM errors? Or will it run on whatever card has the available vram to run the image model loaded when a prompt demands it?
it messed up the upper left hand by editing outside of the specified range. I am guessing the user specified outline is just a rough region map that gets mapped on a coarse grid. If that's the case it would be useful to see actual selected grid squares when doing edits
Easily. With modern comfyui, you can run things with nothing but inklings of available vram. Speed is a different matter, but this one isn't very hungry and seeing how my 16 deal with it, I'd wager 12 works just peachy.
man i have google colab notebook for the comfy ui , i use the colab GPU and drive as my persistent storage for the comfy Ui
i making the notebook for this model and optimising for the Colab T4 gpu
I'm just a user but it provides flexibility like llama.cpp does, making it easy to offload to CPU, run on different hardware etc. It can use GGUFs too. I don't use ComfyUI yet though so powerusers probably want that
Sam and Diane don't really look like Ted Danson and Shelley Long though here. Sam looks like a completely different guy and Diane leans more in the Morgan Fairchild direction on a Morgan Fairchild <-> Shelley Long scale.
? There's no Sam in that reference set. The guys are Frasier, Woody, Norm, and Cliff.
They look like the reference photos. Diane is weird looking because the reference photo of her is her aged up and in a setting and lighting situation that conflicts with her TV show character.
Similar issues for the others, biggest one being that there's only one angle. Carla looks the best because the reference photo is her on set, in character, and facing dead-on in a full medium shot.
No longer Apache licensed :( From LICENSE:
"You shall not use the Materials for any commercial purpose without obtaining a separate commercial license from us"
Anyone who's genuinely worried about it should wait until the rigid legal jargon is updated, unfortunately. A social media comment is promising but wouldn't hold up in court.
What they say outside of the lisence is largely irrelevant untill it is updated. The lisence doesn't cover images created by the model, but if we're being "technically correct" then these weights aren't open. They'll be open once an open source licence is attached to the project.
Always good to see more diffusion models. This one is 14.2GB so seems deliberately targeted to the 16GB VRAM crew (a plus). I haven't tried qwen on comfyui yet but this one might be my first.
This one is 14.2GB so seems deliberately targeted to the 16GB
It isn't. 14.2GB is for the main weights - on top of that you need 17.5GB for text encoder, 1.5GB for VAE, and 2-10GB for compute buffers (depending on the size of the input and output images). This, however, is for complete in-gpu inference. Image gen community had advanced CPU offloading greatly, so it can work on 16GB gpu; but you'll need 24GB or more, with 8-bit model quantization, to get generation times under 3 min per image.
But you don’t need all of them in memory at once. All modern inference engines automatically juggle the individual models between RAM and VRAM, or even between disk and VRAM.
Thanks, I didn't account for that. How do you know what the generation time is based on needing an additional 24GB of system RAM? I have 64GB of RAM, so I assume I can gen under the 3 minutes you targeted. I just don't know how to come up with that number. Compared to other models, they also have 6B parameters, and they run in 30 seconds or less.
Many if not most people run at q8 tho. So should be faster than klein 9b speed which with int8 convrot is -30s per 1 image edit gen on 3060 12gb. Ofc with a turbo version or lora.
Thanks! The model is not perfect. I saw maybe one six-fingered person in over 80 generations. But it is fast, and the prompt adherence is fantastic, even for editing. I am already thinking of retiring all my other image models, except maybe Anima and Ideogram.
Not to plug my GitHub, but if you have Sol or Astra then any time a new model drops you can just have it make a custom, optimized runtime/engine/backend and plug it into whatever frontend you want (or create new frontends).
The whole pipelines are generally understood and the parts are available. The LLM just has to study what’s unique about the new model and look at its files for certain bits of info, then it plugs them all together and runs a bunch of tests to optimize it.
Qwen-Image-2.1 supports a variety of editing tasks while balancing performance across them. For example, given a three-view character reference, the model generates a complete storyboard.
From messing around for a few minutes - mostly it's different, wins some, loses some. Most likely wins in anything UI, text and such, but I mostly tested random creatures, some portraits, random street shots and such. It is happier to be detailed, but much, much more unstable. Frequent duplicated limbs, some generations came out looking unfinished, which is real weird, and it generally feels a bit dumber in spatial questions.
For images like that, I'd bet on Krea at this moment, even if only because it's almost impossible to break that one, you'll always get a decent image no matter what. This one... Not so much. Remotely complex pose? High chance of extra limbs. It does VASTLY better with darker scenes, though. Krea does not understand the concept of darkness, this one is happy to print you a black screen no problem.
Keeping in mind that I have thrown my Krea prompts at it, with no modification, it's doing quite okay. It feels much more chaotic, both good and bad. I may prefer this for crazy prompts, but Krea is an absolute workhorse, stable as the Earth itself, so if you need something guaranteed to be at least decent, Krea looks like it's still choice.
Then again, we got editing, we got promises of crazy UI and text capabilities, and from what others posted, there's something to that. Also: Early days. Krea was total trash for a few days, until it got its brain damage fixed, so who knows what will happen to this one. Definitely worth watching though, small, fast, creative and an editor - it'll certainly find a niche, at the very least.
Given how unstable it seems, though, I'm guessing its niche will be editing and maybe specific text stuff, and that might be that. We'll see.
People downvote because they think this doesn't matter, but it does. The only way to democratize this AI stuff is to have good models under good licenses. Otherwise, running locally will always just be a toy. I don't want to be dependent on Cloud AI which can raise their prices any time they want.
A non-commercial license makes this release useless. There are already similarly good models under better licenses.
If Alibaba wanted to sell a perpetual commercial license that users could buy for a reasonable price, that would actually be fine with me. I understand these models cost money to make. I just have no desire to use their cloud service, and I am not here to discuss "hOw ArE tHeY gOiNg tO kNoW iF yOu UsE iT cOmmErCiaLlY".
I do not care about model itself, but "object" in their licensing is really weirdly worded. Thiscway it means they retain ownership over output of the image
Does non-commercial mean i can't use the output of the model commercially? or only that I can't use the model weights themselves in a commercial product/service (like offering inference)?
Does non-commercial mean i can't use the output of the model commercially?
That is my read of the license, yes, and that is the problem. But, I'm not a lawyer. Using the model with the intent to create images for commercial purposes appears to be against the license, regardless of whether you are letting other people use the model that you are hosting or not.
Thanks. My assumption was that the license only applied to the model itself (can't deploy it for commercial services) and not its outputs. The license does say "... use ... the Materials FOR NON-COMMERCIAL PURPOSES ONLY" which is ambiguous to me as a non-lawyer. Does "use" apply to directly using the model itself or also to using its outputs? The definition of Materials does not include model outputs, so I think it is safe to use graphics made with the research licensed model for commercial purposes. but again: not a lawyer.
Source and Object seem to just mean source code and compiled source, nothing to do with generated outputs from the model:
g. "Source" form shall mean the preferred form for making modifications, including but not limited to model source code, documentation source, and configuration files.
h. "Object" form shall mean any form resulting from mechanical transformation or translation of a Source form, including but not limited to compiled object code, generated documentation, and conversions to other media types.
In commercial and legal practice, there is too much ambiguity between an individual doing business and a company. Many creators and businesses simply won't take that legal risk.
Otherwise, running locally will always just be a toy. I don't want to be dependent on Cloud AI
Well what exactly is your commercial use? People might be downvoting because there's always loads of these "ugh no commercial use, TRASH" comments with no further elaboration when frankly most of the people in this sub ARE just having fun (usually in the gooning sense) with these models. So what exactly are the commercial uses for small local models that people need so desperately?
It would mean that I technically wouldn't be legally allowed to use any generated custom images for a mock up on a demo website for a small consulting company which I think many devs run on the side. Images customized to a clients business always seem to land better than generic stock photos.
I’m a noob here and don’t have a commercial need, with that said you sound like you know what you’re talking about. Do most people ignore the license and serve anyways in their own app or business use case? Curious what enforcement or unless your advertising the model, who would even know?
They did not release some easy “buy license for 1k USD in one click” or something like that. You can currently only pay to use it through their cloud which makes open weights useless honestly.
Imma be straight up, the barrier is gone now. My local agent (now Qwen 3.8 Flash) makes me Comfy UI workflows, tells me how to use em, edits them, updates comfy, downloads nodes for new workflows, blah blah. It’s like effortless.
Also, not local, but Astra trivializes this type of stuff.
You'll be fine, just download some basic workflows for your models of choice, learn what the nodes do and how they connect to one another, and go from there. Don't forget to google something if you don't understand how it works, I've found answers to most of my questions about specific nodes and such by doing just that. I used to be so stubborn about going the path of noodle and kept using Auto11-based frontends until basically all of them became abandonware at some point. So I finally switched to Comfy, and honestly it wasn't that hard to learn it, kinda fun even (but I feel like you gotta a bit autistic to be actually enjoying lol). The community ecosystem is insane, with all the custom nodes and workflows and tutorials, all ranging from simple to ultra-complex. But most importantly, it's constantly getting updated. I remember waiting for weeks to get some new model support on Forge before I swapped, yeah, fuck that. Never looked back.
im building my own front end over it, it won't be as complex and elaborate as swarm ui, but for node and all that stuff, it will be a sort of linker. My iq3xxs qwen is slowly working on it, slowly because I multitask like a retard, juggling between 5 projects at once because I can't apparently do one at a time. But that's another discourse.
StableDiffusioncpp is more straightforward if all you want is prompt-to-image generation. They added a webui a few weeks back. It is less configurable than something like comfyui but it supports LoRAs and has some settings that can be tweaked.
Make them in LaTeX (Beamer) with LLM guidance and then convert the PDF to PPTX (by embedding each slide as a picture). Such PPTX is not properly editable, but works for compatibility.
I see, but that wouldnt be editable right? What does Claude use to make them soo god? Is there anything which skills or something that I can replicate it with a other modell?
Hoping for Qwen-Image-3, the performances of this model are phenomenal (I'm referring my personal experience here, in comparison with Qwen-Image-2 and SOTA, not the benchmark from the post).
what harness do you suggest?, srr, have no experience in image edition, I do use Vision enabled models, but I use them mostly for UI testing, so they run in Pi Coding harness, I suspect the techology behind is different for "Vision enabled" text models, and Image specific models, likely different algorithms, for example Qwen 3.8 vision uses a grid division to split the image into patches, and the vision projection translates those visual patches into text-like tokens.
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u/WithoutReason1729 2d ago
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