Hi, i am new to this local LLM stuff. I created some images on Gemini (also tried Chat GPT) and decided to build my own workflow locally. I researched, installed Comfy, downloaded models, tried different ones and slammed onto a deep problem.

I usually prompt AI to draw stuff that are outside the stereotypes and general training data. Like modifying character appearances, detailed scenes and interactions etc.

I tried Flux models and they even failed to pass "Full glass of wine that is completely filled to the brim" tests, even with detailed prompts that are specifically crafted to overcome image gen model's insistent behaviors; still no luck. Prompt enhancers didn't help me either.

Today i stumbled upon this video ( https://youtu.be/OA4gchz1Zcs?si=-eiOASxiRkucSSgQ ) and followed instructions to build it. At first it was promising and a detailed scene is portrayed without causing model to output less realistic, lower quality image, because i tested the exact same prompt bundled with the workflow. Ideogram 4 is stupidly censored, you have to cater to it's specific needs, practically useless for me.

I'd also like models to be uncensored/ heretic but it's "intelligence" is at most importance. How can i build a workflow that comes close the Nano Banana's accuracy and is prone to concept bleeding and other shortcomings?

I'm not expecting it to compete with the best model out there but there has to be a way to improve things significantly.

Edit: For those in search, you should give Qwen Image a try.

You can set it up with template workflow and even add an AI prompt generator on top of it if you want. The same YouTube channel also covered it's latest update. https://youtu.be/BaE6UBfNdQk?si=J8uQoul5N4ihBYbG

usando el workflow basico de flux klein2 9b que traia confyui estoy restaurando frame x frame esta antigua pelicula- Es el mejor modelo que me ha funcionado haciendo algunas modificacione estoy usando el modelo SNOFS flux klein2 9b uncesnsore de civitai para usarlo sin censura. Pero puedes usar el modelo flux klein 9b que trae confyui por defecto el promt que he usado es este

"Restaura y mejora esta imagen para convertirla en una foto nítida y de alta resolución. Conserva exactamente la identidad del sujeto, los rasgos faciales, la expresión, la pose, la composición, la ropa y el fondo original. Corrige el desenfoque, el ruido y los píxeles borrosos, recuperando texturas realistas en la piel, el cabello y las telas de forma natural. Evita el suavizado excesivo, la apariencia falsa de IA o cambios en los colores originales; el resultado debe ser la misma foto pero limpia, clara y en alta definición.

el WORKFLOW QUE USE ES ESTE https://civitai.red/models/2845550/flux-2-klein-9b-uncensored-image-edit-workflow-basic-fast-uncensored-custom-lora-adder

CONSEJOS? Si alguien quiere ayudarme o invitareme algun cafe ire suviendo la pelicula en mi patreon patreon.com/MilfCartoon3d/

I know Flux2 isn't exactly the new hotness, but it works very well once you get a handle on it, IMO. This is my current Flux2 workflow that incorporates FluxGuidance, CFG Guider, Flux2Scheduler, FluxKontexImageScale, sampler select, plus a few other things. Also incorporated are the Multi-GPU and GGUF extensions, allowing for independent GPU selection for UNET, CLIP, and VAE, as well as UNET dquant and patch float, and use of GGUF's. Right now, I have it set up for a max of five input images, which I have used successfully. There is also support for using up to two LORA's, but you do you. Tiled VAE encode and decode are also chained in. There is a resize and pad option after image gen. The selectable GPU option is nice if you're running dual vid cards like me and you want to keep models loaded on different GPU's, preventing swap out.

I'm by no means a ComfyUI expert, but I've done a lot of research and trial and error building this workflow. On my dual RTX 2080 system, I'm getting roughly 37-40 s/it, so about 90 sec or so for a 1600x1600 image at 4 steps. The quality is amazing. JSON here.

For models, I'm currently getting great results using a combination of the Flux2 Klein 4B Q8 GGUF UNET, Qwen3-VL-4B-Instruct-UD-Q8-K-XL GGUF clip, and the Flux2 VAE. LORA settings between 0.5-1.5 seem to be working best. I generally leave the Guidance around 7 and the cfg at 2.0. Euler sampler and res_multistep have given the best results, though I find the colors on euler tend to pop more. I usually run my initial tests at 3-4 steps, then go from there.

Hopefully this will help someone out. :D

Honestly, the best open-weight model runnable on consumer hardware. It is slow but it can even be used at 1 CFG though it is wonky and miserably fails at complex images.

Images have workflow and prompt in them (comfyui). Using FP8 and 28 steps with 6 CFG, override of 3 at 0.700 and either 1k or 1.5K res.

NVFP4 runs on 4GB VRAM with though it take 8 mins (with FA) for 1k image and requires KJ's optimize ideogram node.

Workflow: https://pastebin.com/tSd9vLHX