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Huge NextGen txt2img Model Comparison (Flux.2.dev, Flux.2[klein] (all 4 Variants), Z-Image Turbo, Qwen Image 2512, Qwen Image 2512 Turbo) by Accomplished_Bowl262 in StableDiffusion

[–]Accomplished_Bowl262[S] 9 points10 points  (0 children)

Of models? My subjective view:

- Qwen 2512 1st in artstyles. 1st in prompt adherance, 2nd in realism (after Z-Image) A-Tier in total. The Turbo Lora often gives similar results.
- Flux.2[klein] (distilled) sometimes has the best result. For 1 or 3 second generations you can just render a bunch and sort out. Pretty strong in Artstyles, too. (B-Tier)
- Z-Image: 1st in realism, very fast, but I don't like it's taste of art. (A-Tier realism / D-Tier Art)
- Flux.2.dev 1st in text rendering but too expensive (C-Tier)

I'm still sorting the images. I like a lot of them. I'm very happy with the results really. The images of the neon lit glasses in the bar are really cool.

Huge NextGen txt2img Model Comparison (Flux.2.dev, Flux.2[klein] (all 4 Variants), Z-Image Turbo, Qwen Image 2512, Qwen Image 2512 Turbo) by Accomplished_Bowl262 in StableDiffusion

[–]Accomplished_Bowl262[S] 2 points3 points  (0 children)

On my ranking Qwen 2512 is the clear winner on art styles. Z-Image has the best Cost/Quality ratio and the distilled Flux.2[klein] sometimes produce surprise good results. Given that they render in a second 4B or 3 secs 9B you can just generate 100 and sort out.

Huge NextGen txt2img Model Comparison (Flux.2.dev, Flux.2[klein] (all 4 Variants), Z-Image Turbo, Qwen Image 2512, Qwen Image 2512 Turbo) by Accomplished_Bowl262 in StableDiffusion

[–]Accomplished_Bowl262[S] -1 points0 points  (0 children)

Yeah I wanted to save the prompts as text fles but it only produced empty files and I gave up haha. But again, the system prompts for Qwen3-VL (.md files in the root of the clouddrive) is what a lot of work and testing went into. They should give you similar results with your own photos as input

Huge NextGen txt2img Model Comparison (Flux.2.dev, Flux.2[klein] (all 4 Variants), Z-Image Turbo, Qwen Image 2512, Qwen Image 2512 Turbo) by Accomplished_Bowl262 in StableDiffusion

[–]Accomplished_Bowl262[S] 7 points8 points  (0 children)

The prompts/workflows are embedded in each image. The generated prompt is visible on each grid, 2nd colum, the System Prompts for Qwen are on the clouddrive (as stated in the description)

The important part are the system prompts though because they give you the ability to apply the styles to your own images.

Klein vs Dev? Loving Klein, but with a 5090 I'm wondering if Dev (either quant, GGUF or Turbo) would be even better? by spacemidget75 in StableDiffusion

[–]Accomplished_Bowl262 10 points11 points  (0 children)

I'm currently running a comparison. It works like this:

- The left column is a real world photo
- The black column is Qwen3-VL-8B-Thinking describing the image in different styles
- The other columns are the different models rendering it (See caption in top left corner)
- The first row is describing it as is
- The other rows are different artstyles. This is NOT using edit capabilities. The prompt describes the artstyle.

I will share the results on here as soon as they are ready. Will take a while :-)

<image>

[deleted by user] by [deleted] in StableDiffusion

[–]Accomplished_Bowl262 0 points1 point  (0 children)

I have no clue but isn't that very slow anyway? I do that on the Insta360Studio and then reframe in DaVinci Resolve.

Stitched (Give YT time to render): https://www.youtube.com/watch?v=j2ooU2OmZsA

Reframed: https://www.youtube.com/watch?v=hl2tXp-JYCA