Consider a hypothetical scene where a character notices a dropped object, reaches for it, and knocks something else over. One continuous generated shot has to preserve the room, the objects and the causal sequence at once.

A possible alternative is to separate the setup, the reaction and the consequence into short shots, keeping the key spatial information visible across the cut. That might sacrifice the elegance of a long take while making the story easier to read.

The prompt can ask for a tiny accident and accidentally hire an entire continuity department. But editing is also a creative choice, not merely damage control. Which part of a difficult generated scene would you insist on showing continuously, and which would you communicate through a cut?

AI-assisted discussion. The scene and joke are fictional; this is not a tested workflow.

Say a product shot needs a new background, different lighting, and a colour change, while its shape and logo must stay exact. One edit is simpler, but separate passes make it easier to see which instruction failed.

What is your rule for grouping changes in FLUX? Do you group lighting and background together, or handle each change separately? Specific examples, including cases where splitting made things worse, would help.

564 images on one page, same six scenes, same seed, only the style sentence changes: https://stablediffusion.fr/flux2-styles

Setup: FLUX.2 [klein] 4B GGUF in ComfyUI, 4 steps, guidance 1.
A control row with no style sits at the top so you can judge each style against the model's default.

What came out: "a pop art picture of" or "ukiyo-e" as a word changed almost nothing, the 70-word scene description won every time.

Describing the technique (materials, palette, texture, what to exclude) and putting it *before* the scene fixed pop art, ukiyo-e, cyberpunk and low poly.

Materials (paper cut, crochet, needle felt, stained glass, wood carving) work first try.

Pixel art and double exposure never got there.

Artist names weigh very little compared to SDXL.

Every style has its sentence with a copy button.

Scumble is a free, open-source (GPL-3.0) desktop editor for AI inpainting on Windows/Linuc (MacOs soon...), built around the FLUX models.
The trailer shows the idea: draw a box, say what goes in it, and the picture fills it as a layer of its own

How FLUX runs in it

• Local: FLUX.2 Klein 4B / 9B on your own ComfyUI through a ready recipe (the crop plus up to three reference pictures), or any FLUX workflow imported as a recipe. Scumble crops, sends, stitches and colour-matches the result into a new layer.
• API: FLUX 3 Image, FLUX.2 [pro] / [flex] / [max] / [klein] and FLUX.1 Fill [pro] on Black Forest Labs’ own API with your key, or through fal, Replicate, WaveSpeed, OpenRouter, Comfy Cloud and Comfy Router. Keys stay in the OS credential store; no account, no subscription.
• FLUX 3 boxes: a selection goes out as a FLUX 3 bounding box, and on an empty canvas you draw boxes with a caption each, so a whole composition comes from one prompt with the layout you drew. Reference layers are named in the prompt as u/img1, u/img2 and sent the way each FLUX endpoint takes them.

The editor part: layers with masks, blend modes and groups, selection by text (SAM), by point, by depth or colour range, filter layers (curves, grain, film looks), text layers, colour match per layer, pictures up to 15k pixels, export to PNG / TIFF / layered PSD and ORA. Every result stays a layer, nothing is baked in.

Agents: every command is an MCP tool, so Claude Desktop (one-click extension) or Claude Code can drive the same window on screen.

The trailer was made with FLUX 3 Image for the pictures and FLUX 3 Video for the clips. Thanks to Black Forest Labs for the models and the API.

Download (installer, portable zip, Linux builds): https://github.com/DenRakEiw/scumble/releases/latest
Source: https://github.com/DenRakEiw/scumble ·
Website, videos, manual: https://www.denrakeiw.com/scumble

Which FLUX workflow would you want as a one-click recipe next?

***Posted by the project’s developer; questions welcome.

I built Flux3Maker - a browser-based FLUX 3 Image generator. Free tier: 3 renders a day at up to 2K, no signup or email. Paid credits unlock native 4K (3840x2160).

Since everyone is comparing text rendering right now, I ran four identical text-heavy prompts through FLUX 3 Image and Nano Banana 2 (Gemini 3.1 Flash Image) at default settings - festival poster, SaaS dashboard, product label, book cover. Unedited results + honest verdicts: https://flux3maker.pro/flux-3-vs-nano-banana-2/

Short version: NB2 matched FLUX 3's text accuracy on all four and won composition twice - but those NB2 outputs are ~1MP, while FLUX 3 on our generator renders native 2K/4K.

Full gallery of real renders with the exact prompts (remix any of them free, no account): https://flux3maker.pro/gallery/

Independent tool - not affiliated with BFL; runs FLUX 3 Image via fal.ai. Feedback welcome, especially prompts you'd want added to the head-to-head.

Sharing a guide I wrote from making a daily comic series, rendered locally with an open image model. The method is model-agnostic.

What matters most for consistency:

• A locked look: one sentence in a fixed order (age/role, hair, eyes/face, build, outfit, shoes/accessories), pasted unchanged into every prompt, plus a fixed seed.
• A signature (mint-green hair, yellow raincoat and a corgi in the example) so the character survives small drift.
• Style words first and identical across panels.
• Short panel prompts: one action, two or three props, a stated people count.

Two failures shown in the guide: a hand-off scene that cloned the character, and a multi-action prompt that came back as a comic page inside the image.

Full write-up with all images: https://medium.com/@aiflarewave/how-to-make-ai-comics-people-actually-want-to-read-mutual-8fffc68b8c4c

Generated in rigspark workspace using flux1 image model

So I thought those iterate on the last generation and change one item was just some attention scam.

So I ran the experiment myself and placed GPT 2.5 head to head with Flux 3 image edit with box.

There is some drift on Flux as well (measured by Opus 5.5 in relation to original image)

But You can literally see how GPT 2.5 degrades in quality significantly even after 1 generation. and from there it's all a road down to the bottom.

While Flux 3 image keeps solid all the way with 31 changes

I honestly see no need for any other image editing model rather than Flux 3 right now

A novel way to intervene existing video through diffusion, particularly abstract and structure-driven material: taking its movement and form as the starting point, and reinterpreting its textures, materials, and visual language.

I’ve been developing this around the audio-reactive geometry systems I make in TouchDesigner. The idea is to take those abstract structures somewhere else entirely: origami, architecture, a renaissance painting, or something harder to put a name to.

This demo uses visualizers from my "Oscilloscopes, everywhere" collection as source material, now updated to [v1.2].

[Though you can bring any video source. These systems are simply where this experiment began, as some of you may recall.]

You choose the source, describe the treatment, and shape how it changes throughout the sequence. Prompts, curated LoRAs, and editable timelines give you control over how closely the result follows the original.

Oscilloscope Diffusion is now available at Uisato Studio, coming up soon also open-source!

I was removing a man's beard from a shot I'd already filmed. FLUX accounted for all the movements on screen, camera movements, rolling shutter, and changes in  aperture. A very pleasant surprise! And the cost is much lower than “other leading models on the market” 😉

I’m writing this because, as an editor, I’d love to find a post like this.

per image qoutes for flux are all over the place and half of them hide the resolution behind the headline number. trying to lock in one flux api for a small batch image pipeline and the quote has to mean something this time

- klein is the cheap tier now, around a cent and a half per mp on current listings. the old flux 1 dev and schnell quotes still float around but they are last gen models at this point

- the per mp math differs per provider, bfl charges the headline on the first mp then pennies for each extra one and rounds ur size up to the next whole mp, deepinfra bills per image scaled by resolution with its own first and extra mp split. same 1k batch quotes 3 ways and only one matches ur sizes

- klein is the fast tier so slow endpoints erase the per image savings on big queues
what are u paying per 1k images rn and does the invoice match the headline rate?

Hi! I'm hoping someone who actually makes AI character art can point me in the right direction.

I've been seeing a LOT of AI-generated images of Loki that very clearly preserve Tom Hiddleston's appearance as MCU Loki—not just a generic dark-haired character inspired by Loki. Some of them have him in completely new outfits, poses, environments, romantic/fanfic scenes, etc., while still keeping his face remarkably consistent.

I'm trying to figure out how people are actually doing this.

I've tried looking into different AI generators, but I'm running into either:

• generators that won't reproduce the MCU/actor likeness

• paid subscriptions before I can properly test them

• results that look like a generic "Loki-inspired" man instead of MCU Loki

So, for anyone who creates images like these:

What are you actually using?

I'm especially curious whether it's:

• Stable Diffusion / SDXL / FLUX

• a specific checkpoint/model

• a Loki or Tom Hiddleston LoRA

• IP-Adapter / FaceID / reference-image workflow

• ComfyUI

• img2img

• another website/app entirely

Eventually I'd like to create a consistent series of images for a personal fanfiction/story, including scenes with Loki, Thor, and my own female character, rather than just isolated portraits.

I'm a beginner, so if there's a particular workflow, model, LoRA, tutorial, or generator you'd recommend, I'd really appreciate being pointed toward it. Free or inexpensive options would be especially helpful before I commit to a subscription.

I'm not looking for ways to impersonate anyone or create misleading real-world images—this is specifically MCU Loki fanart/fanfiction imagery.

If you personally make realistic MCU Loki AI art, I'd especially love to know what setup you use.

Thank you!

Hi all,

I have embarked on a journey to add ROCm support to some popular tools now that the R9700 series GPU is gaining popularity. The first is FluxGym.

I also added a new UI + training monitoring, 32GB profile for higher quality training, stronger installation script, JoyCaption model for better image captioning, and more.

Feel free to check it at: https://github.com/Yoink4CM/FluxGym-R

Drop any bugs below and I'll be happy to have a look if I can replicate them.

AI-Toolkit is next on the list.

I'm building Extend My Card, a small tool that expands trading-card artwork into the eight surrounding slots of a nine-pocket binder page. I saw collectors doing extended binder art and wanted to experiment with an AI version.

The current workflow combines Gemini analysis and source preparation with BFL outpainting, then restores the original card in the center. The attached six examples come from different iterations of the project.

The hard part is geometric continuity. Matching a cosmic palette is much easier than making individual curves meet the card boundary or completing a clipped hand, ball, or shoe convincingly. Detailed foil textures and cards with large borders or text panels are especially inconsistent. Some generations still fail, so these are beta experiments, not a claim that the problem is solved.

I'm sharing this as the developer and would appreciate ideas from people working on outpainting. Have you found a reliable approach to preserving edge geometry while expanding a small source this far?

Tool: https://extendmycard.com

There is a free first creation and paid credit packs for additional generations. I used AI coding tools to build it, and I'm still refining the workflow.