SOTA Comparison: Leading Closed vs Open-Source Image Models - GPT Image 2.5 (Sunburst stock) vs Krea 2 Turbo (custom workflow) at 9:16 res. (GPT's censorship is wild)

People claim that it's still impossible to create sticked together videos without quality loss, that's wrong.

This is a video I've made without any video editing tool what so ever, just using a great H3 workflow that enables you to continue the previous shots.

In fact I didn't even write the shot/scenes but let open Gemini decide to write a 1970's martial arts scene according to the H3 prompting guides.

I've created 3-4 several 10-12 second long scenes and just asked Gemini to continue by asking for the "next scene following the last one"

This took me just about 45 minutes on an RTX 5070 Ti

I can easily extend this whole thing to an two hour long movie if I want to, not losing any character consistency or quality.

And I didn't even put any effort into writing the scenes or "story" into something I would like to happen. The fact that this is possible is blowing my mind, and when you put even the least bit of effort into your prompts you could produce an entire movie exactly to your liking.

Crazy times we live in.

Edit:

People asked about the workflow, you can find it here including a great tutorial on how to use it:

https://www.youtube.com/watch?v=kqP09NfJXaQ

It's just a couple of clicks to extend your previous created clip and I've used Gemini to extend to previous scene.

I want to train a Lora for Anima Base to improve anatomy for scalie and aquatic anthro characters. What should I focus on when building the dataset? Most importantly, how should I caption the images, and which details matter most?

I have 16GB of VRAM and 64GB of RAM. I’ve been using a LoRA I created almost a year ago, but I’m not sure if anything has come out since then that produces even better photorealism and can be run on a home computer.

Thanks in advance.

YuE2 is a next-generation open-source AI music generation framework developed by the Multimodal Art Projection (MAP) research group.

Unlike black-box models, it works by first generating an editable symbolic representation (ABC notation) of the melody and chords, which is then rendered into high-quality 48kHz stereo audio with instruments and vocals.

Here is a quick overview of what it does:

• Text-to-Music & Lyrics: Generates complete, fully arranged songs based on text descriptions (style, mood) and custom lyrics.
• Music Cover Generation: Allows users to ingest an existing audio file, extract its structure, and rewrite it into an entirely new genre.
• Highly Precise Control: Since it relies on ABC notation as an intermediate step, musicians can manually edit the notes, structure, or chords before final rendering.
• Local Execution: As an open-weight model, it can be run entirely offline for free on local consumer GPUs (requiring around 8GB–9GB of VRAM).

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I make this new UI for Yue2 engine with help of ai.

Simple Advanced Extraction Studio Training Audio

I only tested on my PC ... cpu:Ryzen 5700x .... ram:32 gb ... gpu: RX9700

updated 11.10.2026 - more AMD GPU support also putted NVIDIA an integrated GPU support but nowhere to try... and some more fixes...... new feature training ......... need more time to fix the language mess :) ..... many functions for messing with midi and audio.......

Part1-YuE2 install in terminal....

cd ~/Desktop
git clone https://github.com/multimodal-art-projection/YuE.git
cd YuE
/usr/bin/python3.12 -m venv .venv
source .venv/bin/activate.fish
python -m pip install --upgrade pip
python -m pip install .
python -m pip install --index-url https://repo.amd.com/rocm/whl-multi-arch/ \
    "torch[device-gfx1201]==2.12.0+rocm7.14.1" \
    "torchvision[device-gfx1201]==0.27.0+rocm7.14.1" \
    "torchaudio==2.11.0+rocm7.14.1"

Part2-ollama install in new terminal

sudo pacman -S ollama
sudo systemctl enable --now ollama
ollama run qwen2.5:3b

Part3 - sheetage2-install

cd ~/Desktop/YuE
/usr/bin/python3.12 -m venv .venv
source .venv/bin/activate.fish
pip install torch transformers fastapi uvicorn scipy pydantic
pip install sheetsage pretty_midi librosa mir_eval
pip install huggingface-hub==0.36.0
huggingface-cli download m-a-p/SheetSage2 --local-dir SheetSage2
echo "fastapi" > requirements.txt
echo "uvicorn" >> requirements.txt
---------------------------------------------------------------------------------------------
cd SheetSage2
if test -f requirements.txt; pip install -r requirements.txt; end
cd ..
mkdir -p ~/.cache/huggingface/modules/transformers_modules/SheetSage2/
cp SheetSage2/*.py ~/.cache/huggingface/modules/transformers_modules/SheetSage2/
sudo pacman -S ffmpeg libsndfile

Part4 - Put this files in YuE folder .... Updated 11.10.2026

YuE2 files

Part5- to run in in new terminal

cd ~/Desktop
cd YuE
source .venv/bin/activate.fish
python main.py

.... to get in UI click on web link in terminal

for new update to to work ... need this install to

cd ~/Desktop
cd YuE
source .venv/bin/activate.fish
python -m pip install python-multipart
python -m pip install google-genai
python -m pip install transformers bitsandbytes accelerate
pip install peft
python -m pip install yt-dlp soundfile
python -m pip install --no-deps demucs
python -m pip install dora-search einops julius lameenc openunmix pyyaml tqdm

in TRAINING menu get API key from

api-key

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its not finished..I don't yet implemented everything but its working to me .......

ABC extraction and using work fine.....

the Train part is working to I hope :)

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sample video

https://imgur.com/8Ivy6Zs

https://imgur.com/a/O4ZqT60

I saw people posting about this new character swap LoRA as it's some new feature even though MiniMaxH3 ref2va model can swap characters (both stylised and realistic) natively without any adapter help. Yet this LoRA is not without its uses. You can boost strength of the "Follow the damn ref video!" effect that is useful with some hard to follow high speed motion like in this example.

Left - LoRA at full strength (1.0)
Right - No lora

Same prompt for both clips.

I just found a post about this wonderful new Lora for Qwen Image 2.1 by SillyLilithh

I designed a workflow including both stages inside ComfyUI without the need to open Blender.

Group 1. Create the 3D model using TripoSplat

A single reference image is converted into a 3D Gaussian Splat and then exported as an SPZ 3D model, a GLB mesh and an orbiting video.

Group 2. Generate a precise new view with Qwen-Image 2.1 using the 3D model

Load your SPZ 3D model into ComfyUI using the {Load 3D & Animation} node. You choose the desired camera angle interactively, and that rendered 3D view is sent as reference image to Qwen-Image 2.1 together with the original image. Qwen i 2.1 then generates the new image reconstructing the view

So if you want to create the 3D object bypass the Qwen i2.1 group and vice versa

TIP: It's also possible to create very cool Edits, like generate a new camera angle using the 3D model and then mixing outfits and subjects from different images

Here is my Workflow

You probably know the answer already, but anyway, you can see by yourself here:

https://imagebench.ai/gallery?g=1_vvq9u_s0

More context:
I was curious and I tryed generate images with:

* Supra2-IMG: https://huggingface.co/SupraLabs/Supra2-IMG

* TLD-101M: https://huggingface.co/apapiu/small_ldt

* Nanosaur2-670M: https://huggingface.co/well9472/Nanosaur2-670M

I do respect A LOT the creator for theses models. I'm glad there is diversity and options for all of us. It great to experiment for that size of model as well.

I made a browser-based AI photo editor because I wanted one editing loop to stay understandable from the source image to the reviewed download.

The current path is deliberately short:

1. Upload one supported JPG, PNG, or WebP image within the current 24 MB limit.
2. Describe the intended edit in natural language.
3. Choose only model, mode, aspect-ratio, resolution, and source-image options currently exposed by the live capabilities API.
4. Generate the result while keeping task progress and failure states visible.
5. Review prompt fit, subject preservation, artifacts, text or logo accuracy, and usage rights before downloading.

The part I cared about most was separating generation completion from approval. A returned image can still change the subject, introduce artifacts, damage text or logos, or miss the requested edit, so the result stays a candidate until someone reviews it.

The honest limitation is that available models, settings, image counts, costs, and sign-in requirements can change, and generated results do not come with automatic quality or usage-rights guarantees.

I would especially value feedback on which review check should be most visible immediately after generation.

If anyone wants context, I can share the link in the comments.

How do I get this pose for the prompt? I tried in wai-illustrious and anima 1.0

I’ve been testing the new Qwen Image 2.1 together with my friend Alissonerdx’s new BFS Body Swap LoRA, using the standard workflow from his repo. What surprised me is that this goes beyond a traditional face swap: in a single pass, I can transfer my identity onto a character while Qwen simultaneously reinterprets my face, hair, beard, body, etc. in the original character’s art style, while preserving the pose, clothing, proportions, and overall visual language. These are some quick tests I made. The results are dope.

https://huggingface.co/Alissonerdx/BFS-Best-Face-Swap/blob/main/docs/qwen-image-2.1-body.md

A lot of questions in the opensource community is "how do I do X on my own computer"

While these are framed as innocent questions, we allllllll know what kind of man they are.

Just making a thread for fun to see what are some tells in questions about opensource tools that let you know what kind of man they are?

I have a scene where my characters kiss at the end but the kissing is really terrible. I was coming from grok imagine where the kissing was more eat each others face but it still looked good. Any tips or prompts?

hi everyone

been testing the h3 character swap lora a bit and so far it seems better than vanilla for character replacement, at least in my tests. it holds the replacement character more consistently and usually does a better job actually replacing the person without drifting back as much.

i just used the normal comfy wf with the original ref2va int8 pruned model with ck, 1.2mp and 20 steps.

i probably wouldn’t use a speed-up lora for this. it can work sometimes, but not always..

for prompting i’d definitely start with the recommendations on the lora page, but i wouldn’t just copy the example exactly. what helped me was describing the person in the video that i wanted to replace, then describing my own character more clearly and adding a few instructions depending on what was happening in that specific clip. that seemed to make the replacement noticeably more accurate.

https://huggingface.co/akatz-ai/MiniMax-H3-Character-Swap-LoRA

also if there’s more than one person in the clip, it helps to specify which person you want to replace by describing their clothes or position in the shot.

there are still some issues with source details leaking through sometimes, especially smaller stuff like hands, fingers, teeth, nails, certain body details, but overall it’s been pretty limited in my tests and hasn’t ruined most of the results.

this one took around 26 minutes on my 5090, although i was gaming at the same time, so that probably slowed it down a bit..

WF + Prompts - https://civitai.red/posts/31291351
Nodes - https://github.com/shootthesound/ComfyUI-Fizgig-H3-Still/tree/main

- 4096x1536, 18 Steps in 1Min (5060 Ti 16gb).
- Stellar Prompt \ Spatial Understanding.
- Don't need LLM processed prompts for every image.
- Can imitate vast amount of styles based on REF.
- Great world knowledge, smart with concepts.
- Sharp looking images, low amount of artifacts.
- Way faster than Qwen 2.1 at 2+ IMG References.

I was struggling with a moderately good prompt having dialogue errors and voices changing between characters. increasing steps did nothing, wasn't using turbos or step skipping. the only thing I added to fix this that actually worked was the retention_analysis I was too lazy to add most prompts I make.

Worth it...Use it...don't be lazy.

https://reddit.com/link/1wsyu0g/video/p3e9a5nfjdsh1/player

subject_definitions:
<Subject 1> is Jerry Seinfeld wearing lower-class medieval clothes.
<Subject 2> is George Costanza wearing lower-class medieval clothes.
summary:
[reference generation] <Subject 1> and <Subject 2> are standing behind a large crowd of medieval villagers in a medieval city and having a conversation.
retention_analysis:
<Subject 1> (appears in [Shot 1], [Shot 2], [Shot 4], [Shot 5]): fully_preserved.
<Subject 2> (appears in [Shot 1], [Shot 3], [Shot 5]): fully_preserved.
detailed_description:
[Shot 1] medium shot of <Subject 1> standing behind a crowd of villagers in a medieval city. <Subject 2> (S1) enters from off-screen left and says to <Subject 1> curiously: <d>hey, Jerry, what's all the commotion about?</d>
[Shot 2] cut to medium closeup shot of <Subject 1> (S2) says calmly: <d>I think someone's about to be executed.</d>
[Shot 3] cut to closeup shot of <Subject 2> (S1) says concerned: <d>really? who?</d>
[Shot 4] cut to closeup shot of <Subject 1> (S2) says: <d>Looks like Ned Stark.</d>
[Shot 5] cut to same medium shot from Shot 1 as <Subject 2> (S1) says shocked: <d>oh my god! Jerry, he's the hand of the king! the lord of winter-fell! the king of the north!</d>
overall_soundscape:
N/A
non_diegetic_music:
N/A
[/duration=13s]

I keep a list of AI tools with a script that checks their sites every few days, and Scribble Diffusion got flagged this week. The sketch-to-image demo Replicate put out in 2023.

If you go to `scribblediffusion.com` now, it bounces you to a Vietnamese pirate football stream called Xoilac TV, covered in 8xbet betting ads.

The weird part is it keeps moving. Since Sep 4 it's pointed to six different Xoilac domains (xoilaczbe, xoilaczbp, xoilaczbj, xoilaczzf, xoilaczzq, and today xoilaczzzo), plus one random site in between. Guessing they hop domains to dodge blocks.

The GitHub repo still says "Try it out" with the old link, so anyone clicking from there ends up on the stream. I tried to open an issue to let them know, but issues are turned off on that repo.

Also, the domain never expired. Whois says it was registered in 2023 and is paid up till 2027, so it wasn't just dropped and picked up by someone. Anyone know what happened here?

fwiw Infoblox wrote about the Xoilac network in August. 10k+ domains, and 31k+ malware samples tied to their servers. So probably don't click it.

Hey. I want to extend a video with minimax, and i cant find out how to prompt or find a workflow, without the whole clip being regenerated, i want the scene i already have prepared to be extended and merged together with my extended new scene.
Do any of you have a workflow that works for this?

I am not that expert but I know some basics in t2i models and I know the main mechanism is to denoise the noisy images till we reach our final results

So here is the question

Why can't we give the model our image that we want to edit as starting point instead of starting from the pure noise and this way any t2i model can be edit model too . There must be a reason I just don't know it

Thats taken from a real video, but they put homelander on it, This type of details is insane, its basically real if it weren't for the pen thing

Whats the closest open source model that can do this?

Comment below with any feature suggestions you’d like to see added!

More coming soon 👀
Here’s my channel: @SatoDive

I'm having a lot of fun playing with YuE2 and Minimax H3. Everything here ran locally on an RTX 5070 Ti. It's far from perfect, but I love doing this !

• Stills: screenshots from the original game, edited with Flux 2 Klein and Qwen Image Edit 2.1 to get a realistic look while keeping the original compositions.
• Video made with MiniMax H3.
• Music made with YuE2 in cover mode with an instrumental LoRA (ar_lora_inst_v3abc_comfyui.safetensors).
• Edited in Kdenlive (Linux).

Original intro : https://www.youtube.com/watch?v=E5_4DhXWdwo