It won't bridge the gap to gpt-image-2.5 though, and it's going to slow down the process further.
With a 4090, Qwen Image 2.1 Turbo takes around 15s per image, depending on the resolution. That's without the prompt enhancer.
At the risk of stating the obvious, you can't really compare local models to proprietary frontier models. For all we know, those models are heavily subsidized and have trillions more parameters than the smaller, modest ones you can run on a single GPU.
I've been running a prompt-adherence benchmark site [1] all the way back since the days of SDXL. If you look at the progress dropdown, I do think the gap is closing.
June of this year saw the release of some of the biggest open-weight bangers (Krea 2, Ideogram 4, and the kind of slept-on Boogu-Image 0.1), though the license terms can be kind of meh.
The best locally hosted model scores 8 out of 15, while the proprietary ones score 12 out of 15 on the text-to-image metric. If you want something that can reasonably decent for local gen while still being relatively small for modest GPUs, take a look at the recently released Moss-Image model [2]. But if you're expecting results at a level of something like GPT-Image-2.5 Sunburst, you're going to be disappointed.
Just visit Civitai, look at the pages for the base models, filter for images with the ComfyUI workflow in them, then you can just download and drag and drop them onto your local ComfyUI app.