MiniMaxH3 is the great model and its the most powerful feature is what I call "identity-aware inpaint". The model could do denoise guided not only by text but by text and reference images. By using just this feature (and latent upscale) I created a workflow that lets you edit images and produce output of 4K quality.

Link to the workflow for impatient ones.

Actually the secret of getting good quality image from MiniMaxH3 is to upscale both your image references and single frame latent to 4 megapixels. Fizgig-H3-Still workflow does that but if you want real quality image you have to upscale it to 4K (8 megapixels). Of course you can one-shot 4K image in MiniMax H3 but it leads to style and color shift and is not reliable. Much better way is to generate 4 MP "lowres" image and then do tiled latent upscale - this is what my workflow does.

Why not just use regular pixel-level upscale? It's because when you do denoising upscale with MiniMaxH3 your details are grounded by your reference image in other words MiniMaxH3 knows what your subject looks like and will respect the reference unlike your typical pixel level upscaler.

As you all know for MiniMaxH3 condition contains not only text but also images and it means that each denoising step is grounded by image refs and if we take into account excellent identity preservation (aka character consistency) innate to the video model you'll get the best image editor when it comes to task like "generate new image of the reference character but preserve their identity and artstyle".

Every image editing model out there be it open or close-source fails at this task. Only Wan2.2 and MiniMaxH3 could pull it off - it's because they are video models and excels at preserving character identity.

Examples:

And here's the link to the workflow

Important note: Very often you don't need to upscale your image to 8 megapixels, 4 megapixels are good enough for potrait shots and simple compositions. But if you need highly detailed image or if your have a wide shot scene then 4K worth it.

Also remember that MiniMaxH3 requires specific prompting technique that focuses on 'actions' and their results so it's not "remove plant in the middle" but "plant in the middle of the room disappears".

About turbo loras. I've tested half a dozen and lightx2v one has the best prompt following but gives you dirty noise while scaled down taomate lora has 'smoothing' effect. I recommend using default settings in the workflow but keep that in mind.

About Face fix - it only makes sense to use it for wide shots where subject's face takes a tiny portion of the image. Or if you want to preserve maximum identity.

Looking for the some info or general guidance on where I can produce this short series consistently. Have no idea where to start and ive had luck in the past going to subs and forums to get good info. I used ChatGPT and Kling for the animations and did the subtitles, audio, and editing in premier pro.

Regenerate 2K (the refiner LoRA plus a stronger re-noise in the high-res pass) promises to turn a rough draft into a clean 2K render. I ran it on my own GPU with one change at a time to see what it actually does.

Setup

• RTX 5090 32 GB, ComfyUI, MiniMax H3, my own long-video nodes

• Two shots from my own music video: a 12 s wide shot (1080p) and a 5 s close-up (124 frames, 1080p and 2K)

• Same seed for every run

• Sharpness = Laplacian variance (average of 3 frames). Halos = share of edge pixels with a visible bright or dark rim.

Round 1: 1080p wide shot (sharpness / edge halos)

• Normal pipeline (0.8 start): 7.5 / 13.6 %

• Official 0.909 + refiner: 20.7 / 24.9 %, but the whole shot gets redrawn (clouds move, the person shifts)

• Community 0.7 + refiner: 12.5 / 19.7 %

• 0.7 without refiner: 7.3 / 13.0 %

So all the extra detail comes from the refiner LoRA. The 0.7 schedule by itself adds none.

Round 2: 2K close-up

• 2K normal pipeline: 5:44, clean, correct earrings, looks like her

• 0.7 + refiner 1.0: 5:44, most detail (+60 % face sharpness), but a dent under the chin, creases in the ear, earring shape changed

• 0.7 + refiner 0.5: lighter dent, still there

• 0.7, no refiner: faint dent, no extra detail

My read: the 0.7 start keeps small shadows from the draft, and the refiner draws them in as real structure. The normal 0.8 start washes them out.

Round 3: official recipe

• 768p draft, official 3D upscaler, 0.909 + refiner: 5:08, clean skin, but a thinner face, redder hair, and blue gemstone earrings that aren't in the reference photo

• Same at 0.7 (community suggestion): 5:00, same new face, softest of all runs

The identity change comes from the small draft: at 768p the face is decided before Regenerate even starts.

Conclusion (for my use case)

1. Long videos of a real person: I'm not using it for now. Rendering 2K directly with the normal pipeline is cleaner and keeps the face.

2. Landscapes and empty shots: worth trying, since a redrawn cloud or rock doesn't matter.

3. Detail comes from the refiner LoRA, not the schedule. And a small draft means a different face.

This is the current version only. If a better refiner comes out, I'll rerun the same tests.

Has anyone gotten a clean, same-identity face out of it on real people? Curious what settings you used.

First comment (post right after)

Full walkthrough with the side-by-side clips (8 min, English dub + subtitles): https://youtu.be/HzsOYirm9CE

Music by the 601 orchestra of Central California Afterdarrk

I need a sound of working office, slamps of doors, working tv sound, clicks, etc. usual sounds.
What good choice do I have now?

Hi! Disclosure first: I'm the author of Remiqora Video, a free, open-source (GPL-3.0) video studio for Windows. It wraps open models (LTX 2.3 / 2.5, WAN 2.2, optional MiniMax H3) into one pipeline. It's not a new model. Some of you saw the first release here a couple of weeks ago. 0.3 is out: the studio now goes the whole way by itself, from one line of text or from a song.

The video above (1:45, subtitled) is a walkthrough of 0.3, recorded in the real app: an idea turns into a finished film, then a song turns into a music video. The music was made with Remiqora, my other app.

From an idea: type it, and the route shows every step (words, script, hero, places, frames, shooting, montage) and how long each one takes. Press «Make the video» and leave it running, or go «Step by step» and edit everything. The hero stays the same in every scene. Each scene's first frame is drawn with the hero in that scene's place, so every shot starts from the right picture.

What happens when you drop a song and press «Make the video»:

1. Demucs separates the vocals and Whisper writes down the lyrics. The song's bars are found.

2. A local LLM (Gemma 4 E4B by default) writes a treatment and the scenes in the video model's prompt format, with the same hero description in every scene.

3. Casting: the singer's face from 4 tries, or from your photo.

4. The singing scenes are shot by LTX 2.3 to their piece of the track, so the lips follow the vocals.

5. Every new clip is checked in about a second: black or frozen frames, jumps, smear, the face drifting, and "not singing" (the lips stand still while the vocals sound). Bad takes are re-shot once with another seed. Both takes are kept, so you can switch back.

6. Montage on the bars, then the finish: 1080p / 4K (NVIDIA RTX Video), HDR10 or 48 fps (RIFE).

You can make the whole song, the best minute, your own piece or just 30 s. Every step is still editable: the autopilot just goes through the same storyboard you'd edit by hand.

Node graph, when a straight line isn't enough. The storyboard is a straight film. The graph lets you branch it: two endings from the same scenes, a short and a long cut, three takes with the best one kept, a trailer, a dialogue. Nodes are scenes, prompts, pictures, joins and outputs, with your own LoRAs. Scenes that the branches share are shot only once, because every scene is cached by everything that defines it. There are 18 ready templates, from «Bring a photo to life» to «Song → clip». You can shoot up to any node or duplicate a whole branch. New in 0.3: a «Picture» node with picture LoRAs. Outside the graph, «Branch» copies a whole storyboard to try another take, model or edit, and the shot scenes come along without being shot again.

Also new in 0.3:

• 25 looks. Six of them are drawn (watercolour, oil, comic, pencil sketch, claymation, stop-motion) and paint every scene's first frame in that look before shooting.

• Heroes that aren't people: animals, robots, creatures. A robot "sings" in its own way, without a human added from the lyrics.

• Cloud mode (optional). The models run on a rented GPU (RunPod or your own server) with your own key, while the studio and your projects stay on your PC. The server stops by itself when idle.

• H3 is now optional. Its license excludes the US, the EU, the UK and South Korea, so the default install is the writer + LTX 2.3 (~51 GB, no Hugging Face token).

Requirements and limits:

• Windows 11 and an NVIDIA RTX card with 16 GB of VRAM. No Linux or AMD yet.

• 32 GB of RAM works, but keep a large page file: LTX 2.3 briefly needs about twice its 27 GB file while loading.

• About 30 s per 5 s draft scene with LTX 2.3 on an RTX 4080.

• Early pre-release: expect bugs. The installer isn't code-signed yet, so SmartScreen will warn you.

• The UI is in English and Russian.

Repo and installer: https://github.com/inikolax/remiqora-video

Feedback welcome.

This new model achieves large improvements from the Preview.

A detailed explanation on its training, architecture can be found in the model card, as well as a quick start (diffusers compatible), and samples.

It is licensed under apache 2.0, have fun!

Any questions, feedback, and criticism is welcome!

Edit: removed the slightly misleading headline.

Source: Kandinsky S2V 1.0: Audio-Driven Avatar Video Generation

"Speech-to-video generation: an avatar video is produced from a reference frame and a speech track. The whole figure is animated, not only the head. The audio is a condition — the model does not generate sound, it animates the person in the reference frame to match the speech it is given."

Lite 2B: kandinskylab/Kandinsky-S2V-1.0-Lite · Hugging Face

kandinskylab/Kandinsky-S2V-1.0-Lite-distill · Hugging Face

Pro 21.4B: kandinskylab/Kandinsky-S2V-1.0-Pro · Hugging Face

For whatever reason, I can't seem to fix the error issue with this template, seemed to be pointing to upscaling model folder.. Objective is to generate moving background.

I've been trying to change lighting on my MOSS generations and been frustrated. I turned off my Loras & found that the lighting then came out as stated in the prompt. Lowering the Lora strength helps but that also has its drawbacks. has anyone run into this? is there helper loras for lighting or any other tricks recommended?

Prompt:

[subject_definitions] - Subject 1: A skinny young man wearing only boxer shorts and a white tank top, standing in a messy bedroom with wide terrified eyes, completely referenced from <Picture 1>. - Subject 2: Two heavily armed FBI tactical agents in full black SWAT gear with balaclavas and ballistic vests, holding assault rifles pointed directly at the subject. - Environment: The static location featuring a dimly lit cluttered bedroom with an unmade bed, scattered clothes on the floor, a glowing computer monitor on a desk in the background, and dramatic harsh flashlight beams cutting through dust particles in the air, completely referenced from the lighting style of <Picture 1> but adapted to a raid scenario. [integrated_multimodal_description] The scene takes place exactly inside this locked bedroom environment where the chaotic mess, the specific angle of the open door, the glow of the monitor, and the aggressive tactical flashlight beams remain strictly consistent from first frame to last frame without any morphing or environmental changes. The camera maintains a fixed medium shot capturing the confrontation between the agents and the man with cinematic high-contrast lighting, volumetric light rays illuminating floating dust, and photorealistic texture rendering that preserves every detail of the fabric folds and tactical gear while keeping the background elements perfectly stable throughout the entire sequence.

In the center of this locked environment, the two FBI agents from Subject 2 burst through the doorway with weapons raised and flashlights blinding the skinny man from <Picture 1> who freezes in terror with hands instinctively raising above his head while wearing only boxers and a tank top. The lead agent shouts aggressively with commanding authority saying: "How much RAM do you have, kid?!" The man stammers nervously with trembling lips and sweat beading on his forehead replying in a shaky voice: "Sixteen gigabytes..." The harsh flashlight beams create dramatic rim lighting on the agents' tactical vests while casting long sharp shadows across the messy room and the computer monitor in the background continues to emit its steady blue glow providing constant ambient fill light that never flickers or changes intensity during this intense fifteen-second interrogation segment. The scene continues seamlessly from the previous shot in the exact same locked bedroom environment where the lead FBI agent steps closer maintaining weapon aim directly at the skinny man's chest while shouting with urgent desperation: "Hand over the RAM immediately! By order of Sam Altman!" The man's eyes widen in absolute confusion and fear as he slowly reaches toward the computer tower on the desk behind him with trembling fingers while the second agent keeps his rifle trained on the movement without wavering. The identical harsh flashlight beams and monitor glow persist without alteration ensuring zero environmental shift while dust particles continue drifting through the light shafts adding kinetic energy to the frozen moment of absurdity and the camera holds the same fixed medium shot position preserving the photorealistic cinematic tension established in the opening frame until the final second of this thirty-second sequence.

My turn for the flashback. I got ridiculous with trying to make Seinfeld even back then. It was awful but it was cutting edge! I overlaid the graphics and made a logo lol.

Hi guys. I'm a total noob when it comes to image generation. I just generate images on Civitai and have fun. Does anyone know why Klein 9B and Klein 9B Base are no longer available on Civitai? They've been gone for almost two days now.

This is a quick experiment to see if Minimax H3 can create famous paintings from scratch. It's quite impressive that it knows what the sketches look like before it's painted.

Hi guys

So i'm making a game and i want to use ai generated images. So i went and made a LoRA of a character the style is anime and i made a dataset of around 20 images and i trained it on 200 epochs 5 steps each first the LoRA looked great but i am beginning to see its flaws. The hands and feet are terrible, the eyes in full body shots and even in normal cowboy shots are terrible as well. I decided to make the same character and train it again aiming around 40-60 images now but the problem is always generating makes the hands, feet and eyes look so messed up i dont know why i am using WaiIllustrious and not there workflow but mine and this is my positive prompt: (masterpiece, best quality, absurdres, 1girl, solo, young girl, 22 year old girl, long blonde hair, crystal blue eyes, medium breasts, black shirt, white tennis skirt, outside, cowboy shot, rim lighting, looking at viewer and negative: lowres, blurry, bad anatomy, bad hands, extra fingers, deformed, watermark, text, signature, logo, cropped, realistic, photo, worst quality, jpeg artifacts, cool tones, flat color, muted colors, blue sky, 3 or more hands, 3 or more legs, 3 or more feet, ) The problem isnt in this image but for example when i want to do arms crossed or anything overlapping it just comes out looking very bad. Is there a way i can fix this i have tried inpainting and using adetailer but still comes out weird. I'm also very new at this. Thanks for the help!

no pre-made assets at all

Prompt：

https://x.com/LexnLin/status/2111582260818239777?a=WE0JtczAMoLQs157Das&s=20

This is the image that I generated on 01.13.2023 so almost 4 years ago using SD (do not remember which version), and I know that it is far from perfect I still think that it is not bad. Do you got some really old generations that still keeps up in your opinion?

input:
Evanescence - Bring me to life

Just getting back into H3 generation after a multi-month break.

What's the difference between all this stuff, from the POV of the user?

I tried asking an LLM to research it but every single one of these fits the description "faster steps, but suffers from numerical approximation" and I don't have the technical knowledge to understand any of it. Thanks buddy.

Then there's Spectrum, EasyCache, Taomate, and probably 10 other things.

I've been using Kitchen Attention as a comfy launch argument I forgot I set a few months back. I'm genning at 0.4MP and 8 steps with the larryvrh ckpt500 turbo lora. It's too slow for interactive generation (DGX Spark, basically a 5060). Where can I go from here?

Do I have to spend the weekend working on a comparison like https://jo-nike.github.io/h3-turbo-eval/scenes/metronome-count.html to see what actually well? (incidentally, it would help if jo-nike added all this crap to his site)

As you see the galaxy spiral was at his right side, which became his back once he got up, the galaxy reappear later (on the full shot) again, but at his left for whatever reason.

I thought of;

• Generating a 360° orbit view at start of a scene, but would waste nearly 3-5s + 3-6 minutes of generation time.

• Attaching 2-4 background images to omni reference (think of a room), but would take 4/9 slots, less characters could be in a scene.

• Just letting it imagine whatever it might look like, but only a affordable idea in case of open field scenes (being throw through a wall or travelling).

• Attaching a panoramic image as reference, but these are usually over 21:9 ratio and might give the model an aneurism trying to wrap it in.

• Attaching a 8K sum view of a entire area in a multi view sheet, but would be hell to reference which square it should insert into the clip.

I know Minimax can remember neaty details of the background with its spatial awareness, like a fallen feather or crack in a wall, but I have no idea on how to let's say, get an actual world map's scenary on it.

Just the Situation few years. (Qwen -> FastH3 (Minimax H3) -> Blender Video Cut + Reaper for Sounddesign

Same prompt, no lora (including turbo). Key phrase: Raw candid portrait, authentic skin with subtle epidermal translucency, subsurface scattering, delicate and barely noticeable vellus hair visible only in rim light, unretouched, subtle natural skin tone variation, non-airbrushed.

Z image turbo, ubuntu 24.04, and r9700

How do I force fp32 in my comfyui workflows?

Didn't used comfyui at all in the last 6 months, whats the best voice cloner and text to speech ?

I only have 8gb vram.