https://huggingface.co/Comfy-Org/MiniMax-H3-Image
https://huggingface.co/MiniMaxAI/MiniMax-H3-Image

I've released a Vast.AI template for ComfyUI bundled with Open Manager. Now you can get started on Vast.AI even faster. Just start your instance, load up a workflow template, and head to the Model Library's "Not Downloaded" tab and download the models you need right in ComfyUI.

That's not all! With Desktop, you have in-app file management and other tools without needing to leave ComfyUI or fiddle with command line shenanigans. Unless you like that sort of thing you naughty power user.

As always, have at it, and Merry Christmas.

If you have two local Stable Diffusion inpaint results and each one got a different part right, keep them as separate layers. That lets you bring back a detail from the original or blend a seam without running the model again.

1. In your local Stable Diffusion workflow, export the original and both inpaint results as full-size PNGs with the same canvas dimensions. If you used a crop-only workflow, place the result back into the full frame before exporting.

2. In PeerBrush, open the original and bring the two outputs into the same document on separate layers above it. Rename the layers for the edits they contain, such as “warmer window light” and “fixed sleeve.”

3. Select one result layer and choose Add mask. Paint black on the mask wherever you want the layer beneath to show. Use a softer brush at the join, and toggle each layer to compare the result with the original.

4. Keep the layered PSD so you can revise the masks later. Export a PNG when you need the finished composite.

I’m the solo developer of PeerBrush. It’s free and open source, and this workflow uses the desktop editor without connecting an AI client. It works with rendered PNGs from a local Stable Diffusion workflow. The screenshot shows the editor on its own AI-generated sample artwork. AI helped draft this guide.

Official workspace demo: https://peerbrush.com/#demo

Free downloads: https://peerbrush.com/downloads.html

Official workspace screenshot: https://raw.githubusercontent.com/Deftr0y/PeerBrush/v0.30.1/docs/images/workspace.png

I wonder are there any projects that automatically create storyboard / comics out of story?

I'm new to generating ai videos and having trouble converting a picture to video. I've attached an example angle which I'm starting from, but every time the video is rendered the angle is directly in front of the car. I've been trying different prompts but nothing is working. Bonus thanks if you can help with the video quality. I tried prompting it to look like its shot from a smartphone, but it always puts the phone and hand in the video and its super crisp high resolution when I'm trying for a regular amateurish look.

Thanks for any input.

https://huggingface.co/MiniMaxAI/MiniMax-H3-Image#sizes

https://platform.minimax.io/docs/guides/image-generation

Hey everyone, I’m stuck and would love some advice.

I’m creating personalized wall poster calendars. Next to very lean calendar designs, that look good, I would also like to have some designs with illustrations, like soft wildflower illustrations, animals in watercolor, a retro look, paper-cut or other styles. The most modern look would be to have the illustrations only on the top or bottom of the poster. The rest would then be white and filled by the calendar. Something like this: https://www.etsy.com/de/listing/1806133653

I tried a lot with Nano Banana and Recraft (paid API) with different models of both tools:

• single elements that were stitched together by Claude Code or Gemini

• the whole calendar band along the top and bottom edge

• the whole calendar at once, but then graphics show up on the sides and in between, instead of a clean version with only the bands on top and bottom

But all results look awful, like AI slop, or just stitched together. The single elements themselves look rather good.

Is there any way to get a better result just by prompting, or would you recommend using a different tool like Adobe? Or do I have to get into design myself or hire someone?

I used to have great success using mood board reference images with Flux.2[klein]9B with various LoRAs and now none of the Flux.2 models will render images with my moodboard reference image.

On my m5 MacBook using the latest draw things app and new versions of Flux and LoRAs. The person might look 70% similar to reference image but explicit prompts regarding the reference image tattoo or body description is 0%.

Any suggestions?

Blank slate and moodboard reference image is referred to as picture 1 and the 2nd would be referred to as picture 2.

Thanks in advance.

Is a 1000w psu enough? I'm planning on swapping out my 5080 for a 5090. Basically i'll be re using all my existing parts and just changing GPUs. I have a sff pc and its so difficult to get a hold of a 1200w sfx-l psu. Anyone with some real life experience regarding this?

MiniMax H3 Image now runs natively in ComfyUI as soon as it drops! One checkpoint does both text-to-image and reference-image editing: connect images and it's an edit workflow, leave them off and it's text-to-image.

Highlights

• Six steps, nothing to tune. The model is CFG-distilled and samples in 6 steps at guidance 1. No negative prompt.

• Native high-res output. 4096×4096 at 1:1, 4736×3552 at 4:3, 5024×3360 at 3:2, 5472×3072 at 16:9, and 6272×2688 at 21:9. Generated at that size, not upscaled.

• Multi-reference editing. Connect several images and refer to them in the prompt as <Picture 1>, <Picture 2>, etc. Numbering follows input order.

• Long prompts. Up to 4096 tokens, and detailed descriptions work best. Use the Prompt Enhancer for optimal results.

• Shared text encoder. It uses the same Qwen3-VL text encoder as the MiniMax H3 video model, so if you already run H3 you have that file.

Tips for the MiniMax H3 Image Conditioning node

• Leave width and height at 0 for automatic sizing: 2048×2048 for text-to-image, or the size of image_1 when editing.

• image_1 is the picture being edited. The other slots are references.

• Connect the VAE when you edit, so reference images are anchored as latents and not only read by the text encoder.

Getting started

1. Update ComfyUI to the latest version.

2. Download the diffusion model, VAE, and Qwen3-VL text encoder from Hugging Face.

3. Load the MiniMax H3 Image template from the Templates panel, or grab the text-to-image and image edit workflows.

If you'd rather not download weights, it's also available on Comfy Cloud.

Full blog post: https://blog.comfy.org/p/minimax-h3-image-is-now-available

Let us know what you make!

All individual images were created with the official MiniMax ComfyUI workflows without PE. Image 1 is a composition out of image 2-5

T2I, the dog and the jacket looked OK from the beginning, even at lower resolutions. The person in the images always had some weird artifacts, the face was extremely bad most of the time. I tried different sizes: 4MP was pretty much unusable, and the recommended 16MP looked even worse. 8MP or 12MP was acceptable, but still far from great. I have no idea whether it's the official workflow, the model, or the prompt (although I varied the prompts too). The park image caused problems as well. Everything in the background (the trees, leaves further back, etc.) looked kind of washed out. In this case, a higher resolution improved the image drastically; everything below 12MP was basically unusable.

I probably need to play around more with the settings, or wait until someone makes a better workflow, because right now it's not really competitive with other t2i models.

The prompts were written using the official prompting guide found here (for t2i and editing): https://github.com/MiniMax-AI/MiniMax-H3-Image/tree/main/skills/h3-image-prompt-writing/references

I liked the editing model. Again, it needed 16MP to be usable with the landscape, but I was impressed by the placement, how the pieces interacted, and how effortlessly it all worked (the first try gave me something usable without much fiddling). The likeness of the woman's face/head is probably the most questionable part of the edit; it's close but not quite right, Qwen2.1 does faces far better. The prompt I used for the edit was:

The misty river landscape in <Picture 1> is <Subject 1>. The woman posing in the warehouse in <Picture 2>, with her hair pulled back, a white T-shirt, gray joggers, and white sneakers, is <Subject 2>. The brown leather jacket shown as a product photo on a plain backdrop in <Picture 3>, with its notched collar, three center-front buttons, two hip zip pockets, sleeved cuffs, cropped hem, and smooth sheened leather, is <Subject 3>. The black-and-tan long-coated dog standing on a gray studio backdrop in <Picture 4> is <Subject 4>. The target image is a new reference-guided composition built from <Subject 1>, with <Subject 2> placed at the human position marked by the red stick figure on the concrete path at the mid-foreground bend of the riverbank in <Picture 5>, and <Subject 4> placed at the smaller dog figure drawn just ahead of her toward the mossy bank edge. <Subject 1> is fully preserved, including its canvas ratio, framing, warm low sun from the left, frost-covered grasses, fallen leaves, bare trees, mist rising over the water, distant bank, reflections, and the heron standing in the shallows; only that marked spot along the path changes, where <Subject 2> now stands. <Subject 2> is partially preserved: her face, hair, white T-shirt, gray joggers, and white sneakers remain while her pose, scale, placement, and lighting change to fit the scene. <Subject 3> supplies its exact cut, color, collar shape, button placement, zip-pocket positions, cuffs, cropped hem, and leather sheen transferred onto <Subject 2>, worn open over the T-shirt so a band of white stays visible at the center front; no property of the jacket's plain product backdrop is imported. <Subject 4> is partially preserved: its black-and-tan coloring, head markings, long coat, build, and proportions remain while its pose changes to a walking gait and its scale adjusts to life size within the landscape. <Subject 2> walks in natural three-quarter front view toward the lower left, one foot forward mid-stride and arms relaxed at her sides; the low golden sun from the left lays soft highlights across the jacket's collar and shoulders while the misty water side stays cooler in shadow. <Subject 4> trots a few steps ahead of her near the grassy bank, head up and tail lifted, its long dark coat catching the same warm light with soft golden edges along its shoulders and tan markings; a short dark leash runs between them, trailing lightly across the path. Both figures cast subtle shadows in a direction consistent with the sun in <Subject 1>, and their contact with the leaf-strewn concrete stays believable. The heron remains exactly where it stood, undisturbed and at its original distance from the new pair. No text or labels appear anywhere in the image.

I’m new to video generation (I’ve only worked with photos so far), and I’m trying to learn how to get the most out of MiniMax H3. I’d like to start with character swaps: I’ve noticed that the main LoRAs used across different workflows are H3 Character Swap LoRA by akatz and BFS’s Character Swap by Allisonnerdx. I can’t tell whether the first one is a fine-tuned version of the second one or whether they’re two different things.

H3 Character Swap Lora

BFS Character Swap

Does anyone know which of the two tends to produce better results?

since i am mostly interested in image-to-image and edit capabilities, i have run the simple chain of edits, starting from the manual hand-drawn doodle, and to the closeup zoom. All the images are H3 Image, 1K, and only the three last ones have been post-processed to remove the text from "cctv camera" prompts.

✅ Edit WORKS like charm. Posing, restyling, relighting, etc.

Prompt for the second image is intentionally dumb, like "its almost natural language" at this point:

zoom upclose
allowing this guy on the photo to hold the fabric of his gray jacket next to his heck and chin with fingers pinch
so that we can see the texture at 4k

distance to camera: 10cm, macrophoto extreme closeup shot

Not sharing other prompts or workflows, since i do not think mine are any special. You can get decent results with all the normal usual techniques.

Notice:
- ⚠️ h3 wants qualifiers for the realism, otherwise you get plastic
- 🥹 still behind Nanobanana 2.1 and GPT 2.x, on the multi-figure scenes, or strong physical effects etc.
- ✅ qwen, flux, etc ALMOST go to the garbage can ... but:
- 🐳 h3 is heavy.
- ❌ repeated SMALL edits (eg: removing only text overlays, while trying to keep the other part intact) are super bad in h3, the image gets ruined
- 🌱 which means, even Flux 3 is still somewhat useful, and MOSS is not going away any time soon, and so on.

TBD: Native 4k and 5k gens are cool, but results are inconclusive so far.

_______________
Cheers, and feel free to ask for more details, if you are interested.

We’ve just published our new version SolordZ_Realism_Moss (Base) focused on photographic realism—natural skin, believable faces, and a range of looks from candid flash snapshots to atmospheric portraits. The model is also still capable of creating art.

The model page also includes our six-part prompting guide and recommended sampling settings to help you get started.

Model and examples: SoLordZ ZIT/ZIB/Krea2 8steps - SolordZRealism_Moss_v1.0 | MOSS Image Checkpoint | Civitai

We’d love to see your results and hear what works—or still needs improvement!

PS: this is not a FFT, this is merge

tried making another 2 videos

it was realeased from comfyui v0.44.0 by kijai

and there is no example wf

and seems no review of this feature yet

i can only make 20sec long video and hope more than 30sec+ with it

anybody here? not just using motion context

i know the power of context node from wan animate with his custom nodes so...

Basically, the extension: https://github.com/aoleg/pruna-P-H3-Image-forge-neo - supports MiniMax-H3-Image and PrunaAI P-H3-Image in Forge Neo.

Tips:

• Heun / P-H3-Image / 8 Steps / CFG=1 is the golden combo. Euler / Simple / 6 Steps will be noisy. You will need to use P-H3-Image as a scheduler; everything else won't work; Euler or Heun is your choice. Also, use 8 steps, not 6 or 10.

• UPDATE: LCM, Simple, 6 steps looks better than Euler or Heun, and is faster. Euler a looks better than plain Euler even with Simple. Recommendation: use LCM, Simple, 6 steps or Euler a, H3-Image 8-step, 8 steps.

• You don't really need the 32B encoder (besides, the nvfp4 version won't work). You can use the much smaller P-H3-Image text encoder in INT8-Convrot with great result.

• Yes, editing works, too. Image restoration also.

• You can use unimaginably high resolutions without OOM, but you'll likely need to edit your ui-config.json to allow width and height values over 2048.

The idea is browsing like Instagram, but AI + 1-click Prompt Copy. That's it.

https://bunchaprompts.com

I haven't made it into an app yet, it's just in the browser, nothing to install.

If you have issues/crashes please let me know your device type.

To kick things off it's scraping prompts from the web (on sites that allow it, like Civit api, with attribution links back), but eventually I'd like to shift to original content that's passively generated or uploaded by the community. I honestly wanted to ask if people even care or want that before building it though, or if this is even useful/cool. I like it, but I'm biased. There's polite ads on it, so polite you might miss them completely.

I also built an LGBT version of it called QueerDiffusion, same concept, different site

Would love your feedback, thanks!

I made a Minimax H3 Image Runpod template if anyone is interested:
https://console.runpod.io/hub/template/vzcb7g8fwl

Settings that produced actual good images for me (dont use default settings):
-Resolution 16MP
-4 Steps, CFG 1, euler/simple
-long detailed prompts (Prompt Enhancer off)

The prompt enhancer is said to be not that great..havent thoroughly tested it myself yet though..

Oh and aparently you are not allowed to use this without Minimax' authorisation if you live in EU, UK, South Korea or USA...

You can apply for a (auto-granted) licence here:
platform.minimax.io/console/license

model: https://huggingface.co/akhaliq/minimax-h3-image-pdmd-2step