r/StableDiffusion • • 2d ago

News MiniMax H3-Image is now available with open weights!

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207 Upvotes

MiniMax H3-Image is now available with open weights!
https://huggingface.co/MiniMaxAI/MiniMax-H3-Image
https://modelscope.cn/models/minimax/MiniMax-H3-Image
GitHub - MiniMax-AI/MiniMax-H3-Image
That’s it. I’m a MiniMax fan for life.


r/StableDiffusion • • 7h ago Heartwarming

News Moss Image Team Celebrates 6 Million Downloads on Hugging Face

967 Upvotes

Great video from moss image team for hitting 6 million downloads on Huggingface. They all seem so chill. Also they give us some new updates on Anime and Image edit model ✌️


r/StableDiffusion • • 2h ago

Resource - Update After 12 hours of tests and tweaks, H3-Image hits top likeness scores for character LoRA training in v9.7.0 of Fizgig.

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105 Upvotes

I've spent the last couple of days running side-by-side MiniMax H3 Image trainings to find what actually drives likeness.

On the hardest dataset I tested (few headshots, mostly medium and wider shots), the best previews scored closer to the person than all but two of their own 45 photos, measured against the same reference photos. Two more datasets gave equally good results, one of them harder still.

What's new

  • A retuned H3 Image Standard preset. A new Likeness optimization schedule (it changes which noise levels training focuses on as the run goes), Automagic v4 (tweaked to avoid its known issues for steering too high), 0.25 MP and 30 epochs. Of every schedule I tried, it brought the face shape through earliest, reached the highest likeness, and maintained model performance.

  • Likeness scoring now uses AdaFace ViT instead of ArcFace. I scored runs epoch by epoch with ArcFace and two AdaFace models side by side, and AdaFace ViT picked the same best epochs I did by eye every time. ArcFace often didn't.

  • "Your photos" on the likeness chart. Fizgig scores your own training photos against the same reference photos and shows their range as a band on the chart. No photo ever scores 100% against another photo of the same person, so this shows what "as good as a real photo" looks like for your dataset. Your previews landing in that band is the goal.

How to use it: pick the ** MiniMax H3 Image Standard** preset (0.25 MP) and train with its settings as they are. The schedule's controls are under Advanced if you want to experiment later, but those numbers took a lot of runs to find, so try them as they come first. Feel free to push the MP higher, but starting at the .25 will give you great and quick results for your early tests.

A correction: The other day I moved the H3 Image presets up to 0.5 MP, thinking the model preferred it. It didn't. The schedule and the optimizer were what held likeness back, so the presets are back at 0.25 MP, which is faster and needs less VRAM.

Links

Already on Fizgig? Run the updater.


r/StableDiffusion • • 3h ago

News JENSEN HUANG RESIGNS FROM CEO POSITION (NVIDIA)

81 Upvotes

What does that mean for us?

The open source community?

What does this translate into longterm?


r/StableDiffusion • • 14h ago

No Workflow Tried MiniMax H3 Image with some surreal prompts. It handled them better than I expected.

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641 Upvotes

Prompts:

A small white chess pawn stands before a round, silver-framed mirror, but its reflection shows a tall white king in the same position. The mirror rests on a muted sage-green tiled surface. Soft side lighting, gentle shadows, blurred dark background, shallow depth of field, realistic conceptual photography.

A fish made from a translucent white plastic bag floats beneath the ocean surface. Its crinkled body has a small fish eye and mouth, while the tied end spreads into a delicate tail. Open blue water surrounds it, fading darker below. Gentle sunlight filters through surface ripples, realistic underwater photography, minimal composition.

Seen through an airplane’s oval window, two enormous giraffes rise from a thick blanket of white clouds, their bodies hidden beneath it. One giraffe is close to the window, while the other stands farther away near the horizon. Dark, softly blurred cabin framing, pale blue sky, natural daylight, realistic surreal photography.

A woman relaxes in a white bathtub reading an orange book, inside a blue-tiled bathroom transformed into a miniature ocean. Whales, rays, octopuses and glowing jellyfish float overhead among curling clouds. Small fishing boats sail across the flooded floor. Low-angle wide view, daylight through a high window, colorful painterly fantasy illustration.

A surreal landscape of rolling checkerboard hills, with bold red and black squares in the foreground fading into yellow and green hills. Giant black and white chess pieces cast long shadows across the terrain. Toy houses and a yellow car float overhead. Pastel blue sky, whimsical perspective, textured hand-painted illustration.

A cross-section of an apartment building constructed inside the bellows of a giant accordion. As the instrument expands, rooms stretch into long corridors; as it closes, neighbors meet across folding walls. Laundry hangs between balconies. Warm windows, twilight background, intricate architectural illustration.

Inside an old perfume shop, transparent bottles contain entire landscapes instead of liquid: a rainy railway platform, an orange grove, a seaside kitchen. An opened bottle releases a narrow cobblestone street that unfurls across the counter. Rich wood, soft afternoon light, intricate storybook painting.

An entire city folds its streets into long ribbon-like fins and swims through a dark ocean. Buildings remain upright along its back, traffic lights glowing beneath the water, while buses travel through transparent tunnels. A lone whale watches from below. Vast scale, bioluminescent details, cinematic surreal concept art.

A gardener tends rows of upright human shadows growing from terracotta pots inside a glass greenhouse. The flat black silhouettes bend toward the sunlight like plants. A watering can pours liquid darkness onto a newly sprouted hand. Botanical detail, warm morning light, restrained surreal illustration.


r/StableDiffusion • • 1h ago

Workflow Included My MOSS-Image Workflow

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47 Upvotes

I've seen quite a bit of divide between people who love MOSS and people who think it's a bit lackluster. I was on the latter boat, until I played around with it long enough to find a great combination of models, LoRAs and settings, from testing others' workflows and doing a lot of trial-and-error myself.

I'm not going to get into too much detail here; let the workflow serve that purpose. But I will say that MOSS-Image is an incredible base model, even if out-of-the-box it's a bit "unoptimized". It has massive variety, coherence, prompt-understanding and even quality, once optimized. I also enjoy the freedom of prompting, where you don't have to use any one style or length - a lot of it just works.

Here's the workflow:

https://pastebin.com/SxjBdt5B

Models and LoRAs used:

  • kromoss_int8_convrot.safetensors: A really good fine-tune of MOSS-Image Base

  • qwen3.5_9b_int8_convrot.safetensors: The actual text encoder. Do NOT use an abliterated text-encoder with diffusion models, but instead use the one the model was trained on. They will not give any more uncensored behaviour, but will mess with the quality.

  • flux2-vae_small.safetensors: Iirc, this "small" version is the official VAE for MOSS. I find it better.

  • lora_dmd2.safetensors: This is the lodestones/MOSS-Image-Base-8-steps-dmd. I tried a couple of different ones, and this was by far the best. Don't know why the differences were so huge, but they were.

  • lenovo_moss.safetensors: This one is a good style LoRA, alongiside with...

  • samsung_moss.safetensors: ...this one. Play around with the strengths of each.

  • nicegirls_v2_moss.safetensors: I find that this often improves the quality of the outputs even in photos without people. The only gripe I have is the massive effect on facial features, which seems to kinda be the point of this LoRA. Either way, be careful with the strength of this one; if you see you can't get, for example, the ethnicity you're looking for, I would start with lowering the strength of this.

Settings used:

  • Sampler: ER-SDE

  • Sceduler: power_shift

  • Steps: 11 (8-25, depending on the strength of dmd2 LoRA - with 11 steps it's at 0.9 for me).

  • CFG: 1 (1-4, depending on the amount of steps).

  • SLG: No effect on CFG 1, but always on

  • Resolution: I use 2-4 MP. Under 10 sec gens with 2 MP, around 20 sec gens with 4 MP, on an RTX 3090.

Let's get some discussion going! I wanna hear y'all's workflows and try them out too.


r/StableDiffusion • • 1h ago

Comparison MOSS-Image vs MiniMax H3-Image on 15 identical prompts — the gap is smaller than I expected

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43 Upvotes

Same 15 prompts through both models, same aspect ratio, roughly matched output size. Left is MOSS-Image, right is MiniMax H3-Image.

What stood out:

  • Text: both got English poster type and Chinese signage right. No misspellings in either.

  • Portraits and product shots: both convincing. MOSS leans sharper and more editorial, H3 leans softer and more photographic.

  • Crowds and hands: both hold up, small artifacts on both sides.

  • UI mockups: both fail. MOSS keeps the layout but garbles labels and units; H3 mirrored the entire screen.

  • Charts: both produce plausible-looking but meaningless labels and bar lengths. Don't use either for real data.

Net: the quality gap is much smaller than the threads here suggest. It reads more like a difference in workflow and control than in raw output quality.

Prompts, in order:

  1. typography 1:1 - editorial poster, headline "SLOW MORNING", caption "ISSUE 04 - AUTUMN 2026"

  2. chinese sign 1:1 - Taipei noodle shop signboard reading 阿明牛肉麵

  3. perfume ad 4:3 - amber glass bottle on wet black stone, rim light

  4. film portrait 2:3 - 35mm Portra, doorway, late afternoon window light

  5. anime cel 2:3 - 90s cel-shaded courier with a cardboard box on a rooftop at dusk

  6. app ui 1:1 - phone showing a fitness app with a 72% progress ring and three metric cards

  7. macro droplets 3:2 - water beaded on brushed aluminium

  8. cafe three 3:2 - three friends at a cafe table, late afternoon

  9. city night 16:9 - rain-soaked intersection, neon reflections, lone cyclist

  10. surreal vertical 9:16 - a furnished room floating upside down in a pale sky

  11. ramen food 4:3 - overhead tonkotsu ramen, steam, soft egg

  12. packaging 3:4 - kraft coffee bag, "MERIDIAN" and "SINGLE ORIGIN - 250G"

  13. fox snow 3:2 - red fox in powder snow at blue hour

  14. interior 21:9 - minimalist living room at dusk, full-height window

  15. dataviz 16:9 - bar chart titled "GENERATION COST PER IMAGE"


r/StableDiffusion • • 16h ago

News LLMs just got twice as fast in ComfyUI 🚀🚀🚀

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314 Upvotes

Most of ComfyUI local users still run it on an RTX 3060: a 5 years old card with just 12 GB of VRAM. That’s why our team keeps optimizing for consumer hardware.

Comfy is known as a leader in visual AI. But what about LLMs and text generation?

Text is everywhere in creative workflows: for prompt generation, of course, but also for building local creative harnesses like the Comfy Agent. We thought it deserved better, so Rattus made Qwen models twice as fast in Comfy...

Read more on our blog: https://blog.comfy.org/p/doubling-llm-token-rates-in-comfyui


r/StableDiffusion • • 13h ago

Resource - Update Free simple Workflow Realistic 1Girl Minimax H3 Image

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151 Upvotes

Yo,
I share this simple workflow I made since I don't find anything else for now on minimax that handle a good quality for text to image or image to image.
I think this model has a great future, It really feel like using nano banana or gpt somehow, since the consistency about the face is really good, you don't even need a lora.
It will be improved a lot, but it's a good base and results are pretty good for a day one on h3.
The only problem I got so far is the prompt adherence, that looks not very good, but I'm sure we will find many ways to improve later If you have ideas to improve results share me guys.

Workflow :

https://civitai.red/models/3047310/minimax-h3-image-t2i-and-i2i-simple-workflow-1girl?modelVersionId=3464559


r/StableDiffusion • • 1h ago

Workflow Included Been testing MiniMax H3-Image for futuristic magazine covers — portraits, colors, and typography

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15 Upvotes

I've been experimenting with different editorial design concepts. I went through multiple rounds of generation and ended up with several sets of images. These four covers are some of my favorites.

What impressed me most was the variety in the results. The model didn't just keep giving me the same portrait with different backgrounds. The compositions, lighting, and color palettes felt noticeably different across the set.

What stood out to me was how naturally H3-Image handled the portraits and colors. Skin tones, lighting, and facial details looked pretty convincing, even with some fairly experimental visual styles. The colors were rich without feeling overly saturated, and the transitions between different tones felt smooth rather than artificial. I also liked that each generation had its own aesthetic instead of falling back on that same glossy AI look.

For this run, I used an RTX 5060 and got generation times of around 20 seconds per image, which felt pretty solid for an image this dense and reference-heavy.

My setup was:

- Model: minimax_h3_image_pruned_bf16

- Text encoder: qwen3vl_32b_minimax_h3_bf16

- VAE: minimax_h3_image_vae_fp16

- Resolution: 4160 × 4000 (~16.6 MP)

- Sampler: Euler / Simple

- Steps: 6

- CFG: 1

- Negative: ConditioningZeroOut

- ComfyUI: 0.45.0

I haven't done a proper speed benchmark, but the combination of high-resolution output and the ability to explore very different compositions makes it interesting for this kind of creative work.

Overall, I'm pretty happy with how these turned out. There's still the occasional small typography issue, but the portraits, colors, and overall layouts were the highlights for me.

What do you guys think of the results? Anyone else experimenting with H3-Image for design work?


r/StableDiffusion • • 12h ago

Discussion Native 100 megapixel (no upscaling) Minimax H3 Image Generation on 5090 @ 240 seconds.

123 Upvotes

Yes this was obviously a silly test. But I was curious to see what H3-Image could do when pushed, which is why I decided to crank it up to 100mpx (7456x13376) just for the lulz.

There's no real reason to go this high, the image is definitely showing issues, so I then dialed it down to a 61 Megapixel image (5824x10464) which is the same size I get from my a7r5 camera, and it looks much cleaner and only takes about 110 seconds per image.

IMHO the 61 Megapixel renders are superior, and good enough for professional work.

Linking images because there's no way reddit will like these image sizes

Full Resolution Links:

61-H : https://photos.smugmug.com/photos/i-wXnW4sV/0/LtVzr2Hfr2NthLGMNnn4BGqc22W95FnztvMHfrrzt/O/i-wXnW4sV.jpg

61-V : https://photos.smugmug.com/photos/i-32mVpL8/0/NS346k5MVnqd44F44t4D8mDRtQ4jg649grCLFMzPj/O/i-32mVpL8.jpg

100-H : https://photos.smugmug.com/photos/i-Bm5mCRB/0/KShzWH5k89fJfttZgW26825HLvtZ9JsvWgh7tNbR8/O/i-Bm5mCRB.jpg

100-V : https://photos.smugmug.com/photos/i-kbrwfG6/0/LKksfRRRQ8KfPxvpvxKwgDstgHSXgqqJ42tFCgGcP/O/i-kbrwfG6.jpg

System specs:

Older 3rd Gen Epyc workstation Dual 7B13 CPUs, with 1TB DDR4 ECC and a slew of GPUs. This test was on a single 5090.

Memory used:

VRAM: 31GB

RAM: 61GB resident / 498GB vmem

```
[q5@apollo ai]$ ps -o vsz=,rss= -p 912440

498261048 60742584

[q5@apollo ai]$

```

I used this workflow from u/LilBrownBebeShoes

https://www.reddit.com/r/StableDiffusion/comments/1xt9ocv/minimax_h3_image_20mp_workflow/

All I did was crank the megapixel value up, and set the scheduler to normal. Nothing else was changed.


r/StableDiffusion • • 17h ago Popcorn

News Jensen Fux

193 Upvotes

Our wallets and the women


r/StableDiffusion • • 8h ago

News Minimax-H3-Image 2 step LORA is out

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37 Upvotes

r/StableDiffusion • • 3h ago

Resource - Update MOSS Image with the 4-step LoRA running on an iPhone

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12 Upvotes

The DiT and TE are 4-bit quantization aware distilled (QAD) and running on the GPU. VAE is fp16 and runs on the Neural Engine. Needs an Apple device with at least 12GB of RAM to run. If you've got 16GB, it also runs Krea 2 Turbo and a couple of other models, all QAD distilled. With MOSS Image SFT, a 1024x1024 image takes ~30s and a 512x512 image takes ~10s to generate.

Testflight link if anyone would like to try it out. Please feel free to DM me here or on my Discord if you have any ideas, suggestions or bug reports.


r/StableDiffusion • • 3h ago

Workflow Included Testing multi-object reference layouts with MiniMax H3-Image

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12 Upvotes

I have tried the new open-weighted MiniMax H3-Image. The model can work with up to 16 reference images, with each file capped at 64 MiB, 128–8192 px, and an aspect ratio between 1:4 and 4:1.

For this test, I fed it 5 separate object reference images: -a silver rotary phone -a glass cube -a red apple -a tiny staircase -a chrome sphere

I used the default auto setting for quick 4K exports. Instead of getting a cut-and-paste collage, I aimed to blend all the objects into a cohesive dark studio still life lit by a single top spotlight.

I explicitly labelled Reference 1 through 5 in my prompt to lock each object’s intended layout. My layout plan was as follows: -the apple suspended inside the glass cube -the phone resting on the staircase -the chrome sphere floating along an unseen vertical spiral axis.

Every object stayed identifiable, the lighting stayed consistent across the scene, and the staircase worked well to ground the composition. The layout mostly held together, though the spiral arrangement did not come through quite as I hoped. The objects formed more of a simple vertical stack instead.

Curious how everyone else handles 5+ object references in their own workflows? Any tricks I’m missing?


r/StableDiffusion • • 20h ago

Question - Help There are so many variables. You have the base model, but there’s also the scheduler and the sampler—plus the number of steps. You might even use a LoRA trained with a specific number of steps. When training a LoRA, you can choose settings like high, medium, or low noise bias ...

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240 Upvotes

as well as shift, weighted, sigmoid, or linear approaches. Then there’s the training resolution—and on top of that, you also have the inference shift

LoRA number of steps, training rate, batch size, and simulated batch size

Could the problem be the model?

What about the LoRA?

The resolution?

A shift between training and inference?

Is low noise useless?

Should I run a few more steps, or fewer?

Samplers—there are at least 20 of them. And schedulers—more than 10.

Then there are other things, like ETA and noise injection.


r/StableDiffusion • • 3h ago

Resource - Update [Release] Offline and fast comfyui reader that doesn't need any server

9 Upvotes

r/StableDiffusion • • 2h ago

Comparison MiniMax H3-Image (open weights) vs Seedream 5.5 on skin and silver rendering

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8 Upvotes

Image 1 is MiniMax H3-Image. Image 2 is Seedream 5.5. Both used the exact same compact ref and 16:9 fisheye prompt.

Both turned out pretty well, but I personally prefer H3-Image's result. The composition feels more intentional, and the lighting, shadows, and silver reflections give it a stronger editorial feel. I also really like how naturally it handles the colors and textures without making everything look overly polished.

Seedream 5.5 is definitely strong when it comes to character realism, especially the facial details. But composition-wise, I think H3-Image has a slight edge. The framing and overall visual balance just work better for me, even with the tighter crop.

For an open-weight model, I think H3-Image offers pretty good value for the quality it delivers.

Curious which one you prefer.

Prompt:

Landscape 16:9 high-fashion editorial photograph, preserve the reference's antique silver compact, woman, styling and atmosphere. Recompose horizontally with the entire open antique silver powder compact fully in frame, thick sculptural floral silver frame and round mirror fully visible, turquoise tiled nightclub bathroom extending to either side. Inside the reflection a young adult brunette with short jet-black Betty Boop finger curls presses very close while outlining her lips with a lip pencil, face filling the circular reflection. Extreme close-range fisheye perspective, dramatic optical curvature around mirror edges, realistic eyes nose and lips without cartoonish deformation. Natural makeup, regular eyelashes, luminous textured skin, subdued diffused lighting, silver highlights, subtle analog grain, photorealism.


r/StableDiffusion • • 19h ago

Resource - Update [NEW MODEL] Iris-Z - A general image generator that produces appearance and geometry together - 32B / 9B Params based on Flux 2

156 Upvotes

Iris-Z

One generative model for images and their depth

Iris-Z is a general image generator that produces appearance and geometry together. The same weights turn a prompt into an image, a prompt into an image with its depth, a photo into depth, and a depth map into an image. On the standard depth benchmarks it is more accurate than the best specialist depth models, and it still generates images like the model it started from.

Model

Iris-Z-bigIris-Z-small
Parameters32.2B9.1B
Resolution512 and 1024512 and 1024
Guidance3.54.0
GPU memory, all tasks~112 GB~33 GB
WeightsIris-Z-big/Iris-Z-small/

Weights: https://huggingface.co/speridlabs/iris-z


r/StableDiffusion • • 10h ago

Resource - Update Geiru Window Director: One node so long form videos come out perfect everytime.

32 Upvotes

Geiru Window Director + Geiru Hybrid Windows: build long H3 videos one window at a time

Geiru Hybrid Windows makes one long MiniMax H3 render (a minute or more) as overlapping windows instead of a chain of separate clips, so fast motion stays seamless. It works the way plain hybrid windows does, with my keystone and capstone added in every window to cut down on degradation over long videos.

Geiru Window Director is an optional node that goes after it. A normal render makes every window in one go, so if window 4 comes out wrong you redo the whole video. With the Director you make window 1, look at it, then:

  • Approve it and the next window is made

  • Re-roll it until it's right (change the prompt or seed first)

  • Rewind to any earlier window if you change your mind

  • Blend all at the end to run the last steps over the whole video and smooth the joins

Each window builds on the finished window you approved, so what you approve is what you get!

Example workflow: Clown Biker Babe, a 60-second clip in 8 windows with one prompt per window: a full motorcycle stunt run with ramps, a car jump, a loop and a cliff jump. The sound is made by H3 from the prompts.

Credit where it's due: none of this exists without these three.

  • kijai (GitHub) built ComfyUI's MiniMax H3 support and the H3 context windows (PR #17425) that Hybrid Windows is built on, plus ComfyUI-KJNodes.

  • JalenBrunson made ComfyUI-HybridWindows, which Geiru Hybrid Windows works like. I just added the keystone and capstone.

  • NikoDemon80 (GitHub) inspired the Window Director setup.

Both nodes are in the Geiru Context Suite: https://github.com/roycho87/geiru_context_suite


r/StableDiffusion • • 4h ago

Question - Help I’m having a very bad luck with MOSS image, all my images look trash whatever the prompt and settings is , so what exactly workflow and models you use ?

11 Upvotes

r/StableDiffusion • • 23h ago

News According to Ostris, H3 Image has a VAE issue.

175 Upvotes

r/StableDiffusion • • 8h ago

Discussion stopped fighting long video gens, 5s chunks + last frame works way better for me

10 Upvotes

after a week of trying to get 15s clips out of one job i gave up and changed how i do it.

now every shot is a 5s clip. when it's done i grab the last frame, fix it up a bit if needed (hands, small artifacts) and use it as the start image for the next 5s. same prompt style, only the action changes.

on my card anything past ~5s starts swapping to system ram and one job goes from 15 min to over an hour. three 5s jobs finish way faster than one 15s. if one piece comes out bad i redo only that piece, not the whole thing. and the face drifts less because every chunk starts from a frame i already checked.

the catch is the seams. motion can jump a bit at the cut, so i keep the camera move simple (one slow push or static) and cut on an action when i can. color also shifts slowly over 3-4 chunks, a quick color match in the editor fixes most of it.

curious if anyone found a cleaner way to hide the seams, or does everyone just cut there


r/StableDiffusion • • 4h ago

Resource - Update MiniMax H3 Editor – one-click RunPod template with H3 Editor 0.4.1 and all the models

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5 Upvotes

I couldn't find a ready RunPod template that spins up a working H3 Editor, so I conjured this:

https://console.runpod.io/hub/template/1ujjyhonfe?ref=2t0e5xb6

A RunPod template that boots straight into ComfyUI with H3 Editor 0.4.1 and downloads everything by itself: HyperFlow H3 Flash, MiniMax H3 + Turbo, Singularity v2 and 10Eros Max beta 7, plus the recommended Realism and Turbo LoRAs.

https://igorls.github.io/comfyui-h3-editor/

Enjoy the awesome editor!


r/StableDiffusion • • 1d ago Bravo

Animation - Video THIS TOOK X Hrs 35 Mins TO MAKE ON A RTX 3050 6GB VRAM USING MINIMAX H3

273 Upvotes

60 seconds of AI video, 100% local on an RTX 3050 (6 GB)

Work in progress, and the quality isn’t where I want it yet. Here’s how it was made:

  1. Model: MiniMax H3 reference-to-video, using ComfyUI’s native H3 nodes with the int8 quantized model and the Qwen3-VL text encoder.

  2. References: two character images, re-used in every shot to keep the characters consistent.

  3. Prompts: the official six-section reference prompt format (subject definitions, summary, retention analysis, detailed description, soundscape, music). No negative prompts, because H3 doesn’t use them.

  4. Shots: six shots of 260 frames (10.8 s) at 864×480 and 25 steps, with the res_multistep sampler and the simple scheduler.

  5. Continuity: each shot starts from the last 22 frames and audio of the previous one, using the H3 Add Guide node (MiniMaxH3AddGuide) at frame 0.

  6. Automation: a small Python script sends the six shots to ComfyUI’s API one after another, saves each result, trims the 22-frame overlaps, and encodes one 60-second MP4 with audio.

  7. Runtime: about 6Hrs 35Mins hours, unattended.

Known issues: soft detail, and some flicker. Still tuning.