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The capabilities of local LLM text-to-image is honestly pretty damn impressive. IMO, I think local image generation is currently ahead of local code generation. I can get an image in seconds locally with the quality being way higher than what I'd expect from a local model. However with coding it's much slower and much less impressive. I'm sure there's a reason for this and I'm not an AI expert so I'll let the smarter folks tell me why, but that's just been my observation thus far.
I mean I’m sure it’s the reverse for an artist. They would be less impressed with the image and more impressed with the code quality
To generalize, LLMs are great at what you are not skilled at.
That's how they're sold, isn't it?
That's a fair statement, I agree. I'm quite an abysmal artist so I could be a victim of my own bias here
The point I think is interesting is that this is just 7B. The current SOTA 7B LLMs are barely usable for quite simple coding.
I've played with diffusion models on and off since the first release of Stable Diffusion - just for amusement, without a particular goal.
Recently, I've been helping a friend's wife with some basic vector images for her sewing hobby (she has what is essentially a CNC sewing machine) and have been super-impressed with FLUX.1-Kontext, which I've been running on my Macbook Pro with mflux. Its ability to (for example) take a photo of a human or an animal and return a line drawing which is recognisably them (rather than just a generic similarish image as I've experienced with other models) is excellent.
It's an older model now, but (AIUI) has the text-handling features baked in, and in my various testing is very reliable at giving me the outputs that I want, without the randomness I've experienced previously. It's big and relatively slow (~3 mins per 512x512 image edit on my M1 Max Mac) but excellent to work with. It's also very straightforward to set up, without the harness complexity of e.g. comfyui.
is the cnc sewing machine an off the shelf model or something DIY? I'd love to hear more
Off the shelf - it’s a Brother. It prints via a proprietary file format (.PES) but there’s an extension for Inkscape that supports creation and export.
Image gen you eyeball one frame and stop, code needs hundreds of tokens all correct in sequence, one bad line and the whole thing fails.
Interesting in the example of assembling the Cheers team how the otherwise great result genericizes Shelley Long.
The result seems a pretty good representation given the source image wasn't that great. I think that Woody Harrelson comes across much worse.
Very impressive, and kind of worrying a 7B model can have such capabilities. The implications are huge. And Qwen does no watermarking (yet) yeah?
They always had a fourier space mark in their models even without the VAEs are usually pretty easy to detect.
Ah I wasn't aware, thank you
God I love the Qwen team. Easily the most diverse set of models from all the Chinese labs. Only Gemini/DeepMind comes close.
How do you use this model locally, similarly to using `llama-server -m <model>`?
(I mean: outside direct or substantial use of Python, and running the Neural Network in the most efficient way.)
Probably ComfyUI is one of the easiest way to get started with local image/video models. Or perhaps vLLM, if they have support for it already, would be something like `vllm serve <model> --omni --port 9080`
why not just as you suggested i.e. https://qwen.readthedocs.io/en/latest/run_locally/llama.cpp.... then get the result either via a UI or wget/curl it back?
I am not sure that llama.cpp also supports image generation models.
it's multimodal, see https://github.com/ggml-org/llama.cpp/blob/master/docs/multi...
Multimodal doesn't guarantee input and output.
Seems I'm missing something. Does this model support other inputs?
Image outputs are supported, videos I'm not sure but I don't think that's an output, just a preview of the equirectangular example, so, same question here, what does this model outputs that isn't supported?
on the linked GitHub page they list support Diffusers, ComfyUI, vLLM-Omni, SGLang, and LightX2V with links to each
I think that's all Python (not a direct executable).
You could just do (see the "Quick Start") four `pip install` and have a dozen lines script to generate the image. But `llama.cpp` and similar do not require e.g. installing Torch (or PyTorch) - you can use `llama.cpp` on a non-specialized machine.
There is difussion.cpp which is intended for those types of models. I set up krea-2-turbo with the help of ChatGPT 2 months ago, if you have a capable computer that's what I would suggest once it becomes supported.
Boy do I love waking up to find a new awesome toy from the Qwen team waiting for me to play with! Pulling it now
A 7B diffusion model can now render CJK text better than Microsoft Windows.
Just think about how recently we got that feature in the official ChatGPT image gen. And now we have that running locally — assuming that is, I can figure out how to get this running on my Mac — blows my mind.
Pretty sure comfyui has a mac executable
Is ChatGPT really that good?
Back in Apr, ChatGPT Images 2.0 has some broken Chinese texts in its featured examples, and they later removed that from blog post. Is 2.5 better now?
Ideogram 4 has been around for a while haha
I am really grateful to the Chinese Labs for open sourcing their best models. If it was left to the Americans, we would be forced to pay obscene API fees to use them.
Note that the license on this has this in it:
It probably will be much cheaper to use than other image models, but it seems that will be up to the whims of Qwen/Alibaba rather than just being the cost of putting it in a cloud provider.
https://github.com/QwenLM/Qwen-Image-2.1/blob/main/LICENSE
Good luck to them enforcing that license.
A lot of the previous Qwen models seem to have used Apache licenses, among others:
https://en.wikipedia.org/wiki/Qwen#List_of_models
Unfortunately, it looks like this model is using a much more restrictive license:
https://github.com/QwenLM/Qwen-Image-2.1/blob/main/LICENSE
Was going to post about this: the last image models with Apache 2.0 license seem to be from 2025, recent Qwen models are "non-commercial use".
I love the non-commercial clauses because of how many people are using these for deceptive ads and “virtual staging” and fake social media accounts. Anything that makes those guys lives harder while still letting me make silly pictures for my kids and tapestries for my D&D campaign feel fine by me.
You think they care about the probably unenforceable license terms?
Companies can use llm to license-wash open source code regardless of license.
How difficult would it be to use this model to create a second model without licensing issues?
Why would you even do that? Just... use it? There hasn't been any legal precedent on if models can even be copyright restricted. Labs just keep publishing license documents as if they matter.
Well, it is an indication that it matters to the lab, so if you don't want legal fees to be the first one to set precedent, then it does matter a great deal.
I'm willing to bet a nonzero amount of its training material is GPL, so I'll treat it as GPL licensed instead and use it however the fuck I want.
If AI labs get to ignore licenses, so do we.
What are the top image models that still use a less restrictive license today?
Calling open-weights as open-source in marketing materials is the usual misrepresentation. But now with the restriction on commercial use (which is against opensource definition) it is not even open-weights, technically it would be more accurate to call it weights-available.
They finally fixed their VAE. It really held back their models over the last 2 years.
Can you share the sources?
Its happy to see a new open image model from qwen. But the license is a let down. And it dosent even beat their closed qwen3 image wich is already a bit old.
Qwen Image 3 was released two months ago: https://qwen.ai/blog?id=qwen-image-3.0 I think you have it confused with another model.
While I'm impressed with the Bluey example, the lack of Muffin disappoints me.