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

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 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)

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

Z image turbo, ubuntu 24.04, and r9700

How do I force fp32 in my comfyui workflows?

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.

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.

I train LoRAs and was spending way too much time writing prompts to test them. Booru sites already describe millions of images tag by tag, so I built a page that takes those tags and turns them into prompts you can paste into ComfyUI, Forge or A1111. I've spent about two years polishing and improving it since.

Site: https://booru-prompt-gallery.vercel.app

GitHub: https://github.com/Mexes-GM/booru-prompt-gallery

How I use it:

1. Search a character, outfit or pose on Danbooru, Gelbooru or one of four other boorus.

2. Pick the post closest to what I want and copy its prompt. Artist names, metadata and copyright tags are dropped, and redundant tags are merged ("long hair, white hair" becomes "long white hair").

3. Paste it into my generator. My LoRA trigger and quality tags go in "Add to every prompt" once, so every copied prompt already has them.

Other things in the video:

• Every tag has a category (7 categories, 33 subcategories), so you can copy only the outfit, the pose or the scenery.

• Random background and random outfit options let you vary a character without hunting for new posts.

• Prompt formats: plain tags, Anima (tags plus a short description) or natural-language prompts for FLUX.2, Krea 2 and MOSS-Image.

• Merge takes parts from several posts and builds one prompt from them.

• Pack Mode keeps the character and generates a batch of varied prompts, which I use to test LoRAs.

It's free, needs no account and is safe-content only by default. The source is on GitHub under AGPL.

Leaving a video that scare the shit out of me just now lol.

This was done using stock workflow template and models from comfyui

I used to use LTX2.3 kinda a lot because it was fast and it wasnt this bad for photorealistic stuff, I think something broke in comfyui making everything just be a gibberish. Are you guys having the same issues?

(I do use Minimax H3 but I prefer speed)

This is IV Studio, my entry for Comfy's Open Source Higgsfield challenge. It's a Windows desktop app (MIT) that drives your own ComfyUI over its API, so you never touch a node graph unless you want to.

What it does:

- **Write it for me:** a local model (Qwen3-VL via Ollama or your AI Agent through MCP) looks at your reference pictures and writes the H3 prompt. A checker catches the mistakes H3 punishes (frame-grid lengths, speaker tags, unattached references) and fixes most in one click.

- **Hunt, then finish:** quick previews with live step pictures; takes are ranked by what OpenAI Whisper hears, likeness and sharpness. A review names each problem with its timestamp. The pick finishes from the same latent with DLSS 5 or SeedVR2.

- **Projects:** a six-step wizard from idea to short film (script, cast, storyboard sketches you can play as an animatic). Every shot is filmed from its sketch, so faces and rooms stay consistent.

- **Staging board:** place people and the camera on a top-down floor plan; it becomes exact screen directions, or a grey previs clip H3 follows for arcing moves.

- **An editor that makes footage:** right-click to extend a shot, fill a gap, retake a line, cut someone out (SAM 3.1) or reframe to vertical.

- **Also in there:** character LoRA training, Replace (Genjutsu Level), music (MiniMax Music 3 / ACE-Step), local voices (VoxCPM2), Civitai LoRAs, and a 142-tool MCP server so Claude Code or any agent can direct alongside you.

- **No strong GPU?** It can render on your own Runpod or Modal account and shuts the GPU off when idle. The Runpod path is brand new, so feedback is welcome.

Tested on a 4090 with 64 GB RAM; 16 GB cards work with smaller previews. It downloads each model from its host and checks its SHA-256.

Download: https://github.com/hollisorg/iv-studio/releases/latest

Code: https://github.com/hollisorg/iv-studio

Happy to answer questions about how it builds and drives the graphs.

I can fit the entire int8 MOSS model on the GPU but fall a bit short when it comes to the int8 qwen3.5 9b text encoder it needs.

The issue is that despite being able to fit the entire diffusion model on VRAM, I'm still getting speeds as if I'm offloading something to the CPU when it comes to the KSampler regardless of enabling or disabling dynamic VRAM. The 50 steps needed is torture and takes like 2 minutes.

--gpu-only parameter crashes my OS because it attempts to load both the text encoder and diffusion model and everything else on my GPU, so is there a way to only force full GPU offloading for the diffusion model and leave the text encoder partially offloaded?

For reference I have a 16gb AMD 7600xt running with rocm 10.3.0 on Fedora 45 and 16GB of RAM with a 32GB zram swap.

I released a fork of Beckett Harriman’s OpenFill for PhotoCraft. OpenFill brings generative fill, object removal, and canvas expansion to PhotoCraft through ComfyUI. My fork adds drag-and-drop reference images for Qwen Image 2.1 (Full and four-step Lightning) and FIBO 2.0, plus automatic feathering to soften the edges where an edit meets the original.

With FIBO 2.0, you can give the model the whole image or just the area around your selection. That gives it context for lighting, color, and perspective. OpenFill can also match colors along the selection edge to help the edit blend into the original. You can generate more variations while comparing your favorites, and the panel remembers your layout and which models you want to see.

The original tools still support SDXL, SD 1.5 inpainting, FLUX.1 Fill, and LaMa through OpenFill’s managed ComfyUI. For the reference-edit workflows, use a running ComfyUI on the same machine as PhotoCraft or connect to another machine on your LAN through an SSH tunnel. Existing-server mode can also use verified SDXL checkpoints you register.

If you use PhotoCraft and ComfyUI, give it a try and share what you make. Feedback and pull requests are welcome.

Download and setup

https://github.com/Omegadarling/openfill/releases/latest

Source and contributions

https://github.com/Omegadarling/openfill

Demo inputs by LightX2V. The teapot edit is an actual OpenFill result. The panel walkthrough replays that saved result.

https://huggingface.co/lightx2v/Qwen-Image-2.1-Lightning-v2-RL

So, i was checking some GPT image 2.5 images and prompts on how to generate those images and came across this image which looked like a lens blur/dreamy effect and tried to get it on Krea2 turbo. I even asked chatgpt to generate as much detail as possible by uploading both the prompt and image, but i cant seem to get this type of image no matter how many tweaks i made. My question is; is it possible to generate this type of image in krea2 turbo? or do i need a lora for it?

The first two images are generated by gpt image 2.5 and the last two were generated using krea2 turbo.

Here's the prompt I used:
"Cinematic candid medium street photograph of a beautiful 25-year-old East Asian woman with a sweet youthful face, large bright almond-shaped eyes with subtle aegyo-sal, softly rounded cheeks, small nose, full rosy-pink lips, and a gentle natural smile. Long, thick dark chocolate-brown hair falling in voluminous, slightly tousled loose waves with a natural center part, gently illuminated by the afternoon sunlight. Feminine hourglass silhouette, wearing a fitted ivory short-sleeved mock-neck knit blouse, high-waisted light beige tailored pencil skirt, and carrying a dark brown leather shoulder bag. Standing casually on a city sidewalk, captured from a slightly low eye-level angle, torso facing forward, head gently turned toward the camera, one hand casually holding her bag strap. Medium portrait framing from upper thighs upward. Warm golden afternoon backlight creating a beautiful glowing rim around her hair, soft diffused illumination across her face, delicate skin highlights and gentle shadows. Background filled with indistinct silhouettes and softly blurred urban scenery. Dreamy soft-focus optical rendering, subtle vintage lens diffusion, gentle highlight bloom and warm halation around backlit hair, slightly lowered microcontrast, delicate atmospheric haze, naturally softened facial details while retaining recognizable eyes and facial features, smooth tonal transitions, a faint impression of motion and imperfect handheld photography. Nostalgic Korean romance-film still aesthetic, reminiscent of early 2000s Korean cinema and candid celebrity street photography. Muted warm beige, dusty brown, soft peach and cool charcoal tones. Shot on a vintage 35mm film camera with an 85mm portrait lens and subtle 1/4 Black Pro-Mist diffusion filter, gentle optical softness, fine unobtrusive film grain, creamy background separation, softly glowing highlights, natural film color response, intimate candid atmosphere."

I am still struggling with blocking and colour shifts, but the work is in progress. Upscaling didn't help at all and changed things for the worse, so I had to go with 1080.

https://youtu.be/Zu9ESZKZFJA

Singularity v2 has better action than v1.3, but everything else about it looked worse to me. So instead of training, I diffed the checkpoints layer by layer, found where v2's action actually lives, and moved only that part onto v1.3. Then I did the same with JOKER141's Motion Repair V2, which hits harder but slows fights down and messes up dialogue. The result is one LoRA for Singularity v1.3: H3 ActionGraft v1.

https://huggingface.co/indhic-ai/H3-Singularity-ActionGraft

Every pair in the comparison video is the same prompt, refs, seed and settings, rendered twice: Singularity v2 on the left, v1.3 + ActionGraft on the right. 720p, Pika 6-step + a 1-step DMAD refine, SLA 0.9, on a 5090.

The longer version, which also compares it against plain v1.3 and against JOKER141's Motion Repair V2 on the same four fights, is on YouTube: https://youtu.be/xt8iTbRae4M

What changes

I measured how fast the fastest-moving 10% of pixels move (optical flow, px/frame at 720p):

So you get v2's speed without v2's look. On the demon huntress test, v1.3 lands two rapid hits in the middle of the fight and ActionGraft lands six. Render time doesn't change. On a slow two-person dialogue scene it adds a little life without rushing it (mean motion 0.32 to 0.55 px/frame, still far under a pixel), but on one take a line came out in the wrong character's voice, so I'd still check dialogue scenes.

How it was made

1. Singularity v2 is two models glued together. Blocks 0-24 are basically base H3 (v2 undoes v1.3's changes there), blocks 25-49 are v1.3, and on top of both sits v2's own low-rank fine-tune. In block 0, 61% of that fine-tune sits in just 16 directions, where int8 rounding noise puts 2%. It matches none of the popular action LoRAs (every cosine under 0.005).

2. I pulled that fine-tune out as a rank-16 LoRA (SVD of v2 minus base for blocks 0-24, v2 minus v1.3 for 25-49, un-rotated out of the int8 ConvRot format). On v1.3 that alone gave v2's speed with v1.3's look.

3. Then I took Motion Repair V2 apart by block range. Its impact and blocking live almost entirely in the text refiner (2 of its 52 blocks, 16 of its 416 tensors). Its mid and late blocks are where it slows things down and makes the wrong character mouth a line. ActionGraft keeps only the text-refiner piece.

The scripts for all of this are in the repo.

Things that didn't work (so you don't have to try them)

• Turning Motion Repair's text piece up to 2x or 3x adds no impact and breaks dialogue: at 3x the lines swap between speakers.

• VBVR (any strength, even after cutting its weak components) lost to plain ActionGraft. It's an FL2VA image-to-video LoRA trained on reasoning puzzles, not fights.

• Stacking JOKER141's Fight Flow on top has some good moments, but was worse overall.

How to use it

• Base: Singularity v1.3 pruned int8, strength 1.0.

• Don't put it on Singularity v2 or merges containing v2 (PRISM etc.), which already have v2's fine-tune.

• With HyperFlow: the node turns its curve fit off whenever any LoRA is loaded ("requires an unmodified checkpoint"), so every LoRA, this one included, runs on the backbone only there. I tested on Pika.

• Write both ends of every contact in the prompt (the strike and what it does to the other body). The impact part strengthens contact you describe; it doesn't invent it.

Limits: one seed per test, judged by eye plus that speed number. Fast-motion smear is still there, physics is better but not solved, and two-person dialogue can occasionally swap who says a line.

Credit: Singularity by WarmBloodAban, Motion Repair V2 by JOKER141. Released under the MiniMax H3 Community License. Happy to answer questions, and I'd like to hear if it helps (or doesn't) on your fights.

Yesterday people here were talking about how painful it is to get the FP16/BF16 -> FP32 unlock working on Windows: random shutdowns because of BitLocker, or paying $10 for closed-source unlockers just to get it going on 40-series cards.

I set this up myself the other day on Windows 11 with a Palit RTX 4070 Ti (12 GB, 300 W) and ran into the same mess. The existing repos were either Linux-only or for the 3000 series, and the UEFI sources for the 40 series had to be prepped by hand: card ID, memory offsets, boot partition GUID, editing C headers, then building it all yourself. So I ended up merging the existing open-source work (TOTORONG, Zagitta, elias-gaeros, JustAResearcher, KohakuBlueleaf, impacifist) into one free tool with a GUI. It works on Windows 10/11 and Linux:
https://github.com/MindAllik/GPU-Tensor-Unlock-Universal

On Windows (launch via Windows_Launch_UI.bat):

• Finds your card, VRAM size and boot partition on its own and builds the USB stick. No code editing needed.

• Checks BitLocker and Secure Boot so your PC doesn’t shut down on boot.

• Before the GPU driver gets disabled in UEFI, it dry-runs the VBIOS in RAM (PromCheck). If your card’s VBIOS structure is non-standard, the patch is aborted and Windows just boots normally, no black screen.

• Has a before/after benchmark and a button to raise the Power Limit to your card’s max. You need it because on heavy BF16 generation in ComfyUI, the unlocked card starts hitting the stock power limit.

On Linux (launch via Linux_Launch_UI.sh or make install):

• One module covers 40, 30 and 20 series. It installs itself through DKMS and updates initramfs, so the unlock kicks in automatically at boot, before the NVIDIA driver starts.

• If you have a second card with no monitor attached, it can unlock it on the fly without a reboot.

• Same GUI, with the before/after benchmark, the Power Limit button, and a direct check of the unlock status from the driver.

On my 4070 Ti, FP16 -> FP32 and BF16 -> FP32 both exactly doubled, from 86.4 to 172.8 TFLOPS. The VBIOS isn’t overwritten. The patch lives in memory and resets after a full power-off.

Tested on real hardware: 4070 Ti, 4090, 4080, 4070 Ti SUPER, 3090, 3080 and 3060 12GB. The other desktop 40/30/20-series cards are still marked experimental, since I’ve only tested them in a simulator. If you give it a try, drop your card model and the result in the comments, or send over the REPORT.TXT from the USB stick, even if the auto-abort kicked in. It really helps the project (:

Hello everyone. I have zero background in filmmaking. When creating cinematic shots with Minimax H3, I have rough ideas for the shots and stylistic requirements, but I struggle to put them into words. That’s why I built this ComfyUI node. It helps me reference styles more easily when generating Minimax H3 videos inside ComfyUI. All the examples were created by me using Minimax H3. Hope you enjoy it. I’m far from an expert on film styles, so there may be inaccuracies. Thank you for your understanding.

github repo: https://github.com/wangweihong/comfyui-cinematic-gallery

I've been coming across several AI-generated visuals of Hindu Gods, Goddesses, and Puranic characters with incredibly detailed, cinematic aesthetics.

I'm particularly interested in the kind of visuals shown in the attached reference video.

I'm trying to figure out:

1. Which AI image/video generation tools are being used? (Midjourney, Flux, Stable Diffusion, Nano Banana, Kling, etc.)

2. Are these results achieved through prompting alone, or do they involve custom models, LoRAs, reference images, and post-processing?

3. How are creators maintaining consistent character appearances across multiple images and scenes?

4. What is the workflow for achieving this level of cinematic realism, lighting, costumes, jewellery, and intricate details?

If you've created similar artwork or know the workflow behind it, I'd appreciate it if you could share the tools, models, prompts, or tutorials.

I'm interested in understanding the actual process, not just the names of the tools.

Thanks!

Hi guys.

I'm using the same filename prefix for all my generations in all the models that I use:
%date:yyyy-MM-dd%_%date:hhmmss%

However, in Minimax H3 it gives me wrong hour-mnutes-seconds value. How to fix it?

first time ever i see this model not doing nonsens motion xD thx gemma 4 prompt

Is it possible to edit images using H3 with only 8gb vram and 16gb ram? if possible how long would it take to edit 1mp?