Faster! Harder! Shake Harder! | H3 Motion Booster
To be completely transparent: rendering and training large video LoRAs like H3 on cloud GPUs is an absolute money burner 💸. High-tier cloud compute costs add up so quickly with every experiment and epoch iteration.
Every single bit of support helps cover those heavy cloud GPU rental fees, and it directly serves as the motivation and fuel to keep this Bunny training and bringing more high-quality models to you all! 🐰⚡
Ref2VA Edition
A few users have reported that Dynamic V2.0 already works very well with the FL2VA/Ref2VA Hybrid model, so this version is not intended to replace it.
This is a native Ref2VA-trained variant. In my testing, it provides better reference character consistency, with some trade-offs in image quality and overall stability.
Since it's already finished, I'm releasing it so you can try both and choose whichever works better for your workflow.
Use at the start:<Picture 1> is the adult woman.
The woman from <Picture 1> is etc.
Please let me know your testing results. The two versions were trained with different training methods and captioning logic, so I'm very interested to see how they behave across different workflows, prompts, and reference images.
This LoRA is provided as a motion-generation tool. Users are responsible for how they use their reference images and generated outputs.
H3 Motion Booster V2
V2 is a major upgrade over the original Motion Booster — broader motion coverage, stronger impact response, more natural secondary body movement, and added audio support.
What’s New
Expanded motion coverage – more movement patterns beyond simple forward-backward / vertical motion
Stronger impact & rebound – better compression, separation, recoil, and visible body bounce
Improved secondary motion – hips, thighs, torso and chest now react with natural delayed follow-through
Audio support – trained with audio for better contact sounds, breathing, and motion-linked effects
Better rhythm control – handles steady, fast, compact, and heavy impact-driven motion more reliably
Usage
Trigger: dynv2 Recommended weight: 0.6–0.8 (start at 0.7)
Works best with I2V. Start from a correctly posed reference image, then describe motion direction, rhythm, contact, rebound, and audio.
I2V performs significantly better than T2V (T2V needs more rerolls).
When paired with NSFW ALLINONE, it can also handle fast oral motion well.
Recommended prompt structure:
integrated_multimodal_description:
overall_soundscape:
non_diegetic_music:I2V Example
integrated_multimodal_description:
dynv2. The two subjects from preserve the exact starting position, body alignment, and interaction shown in the reference image.
His cock is inserted deep inside her vagina and stays clearly penetrating her for the entire duration.
From the very first frame he/she drives extremely rapid, high-cadence vertical hip motion with short, aggressive strokes — minimal dwell time at the bottom, instant separation, and immediate rebound. The pace is blistering and relentless with zero build-up, maximum visible speed maintained from start to finish. Her hips lift and drop in a continuous, dense rhythm while her breasts bounce heavily with every impact.
extremely rapid high-cadence pelvic motion, compact short-stroke movement, instant rebound, uninterrupted maximum speed, no slow-motion, no acceleration phase. Clear wet penetration is visible as the cock slides rapidly in and out of her vaginal opening.
overall_soundscape: Loud, dense, rhythmic wet skin-on-skin impacts are tightly synchronized with every rapid stroke. Heavier wet slaps land on the deeper thrusts. Continuous heavy breathing mixed with soft muffled moans and short exertion sounds from the woman. Mattress creaks under the intense motion. No spoken dialogue.
non_diegetic_music: None.
Tip: Select he or she depending on who should lead the motion.
H3 Motion Booster V1
This is an experimental motion enhancement LoRA for MiniMax H3, designed to boost action amplitude, fluidity, body recoil, and secondary motion (especially chest movement) in dual-person interactions, fixing the base model's over-soft movement.
Recommended Workflow & I2V / T2V Guidelines
The prompt is optional. The shorter prompts shown in the example images,This trigger just there to make it easier for me to apply them. This trigger has already been written as a generic template, you don’t have to use it—you can simply describe the intensity and amplitude of the shake.
ONLY work with fl2va 8int.
Both I2V and T2V are supported, but I strongly recommend using I2V for this version.
My preferred workflow is to first create a clean, anatomically correct two-person starting image using KREA2 or an image-editing tool, then feed it into H3 I2V along with this LoRA.
Using single-person images or relying solely on T2V often leads to unstable positioning, incorrect interactions, and flawed anatomy.
Trigger Words & Motion Directions
Choose the corresponding trigger word based on the primary direction of movement in your starting frame.
The prompt has been set to a general format; you can modify it to be more specific as needed, as long as you keep the key trigger words.
Forward / Backward Motion (dynfb1): Best for standing, doggystyle, leaning forward, or any front-to-back reciprocating motions to enhance hip push and body recoil.
integrated_multimodal_description:
[Shot 1] dynfb1, keep the characters, clothing, environment, and overall composition from the first frame consistent. The two figures remain in close interaction while performing extremely strong, rapid, repeated forward-and-back body motion at maximum visible intensity. The hip movement is large, forceful, and high-amplitude, with deep repeated thrusting motion and very fast rhythmic pacing. The bodies show powerful momentum, strong recoil, and aggressive weight transfer with every cycle. The torso, shoulders, chest, waist, hips, hair, and limbs all display intense secondary motion, violent follow-through, and pronounced shaking from the force of the movement. The chest bouncing becomes very strong and highly visible, and the entire upper body reacts dynamically to the repeated high-force motion. The pace continues to build, becoming faster, harder, and more energetic over time. Preserve stable anatomy, keep both figures clearly separated, and keep the camera mostly steady so the body motion remains the main source of intensity.Vertical / Up-and-Down Motion (dynvt1): Best for cowgirl, reverse cowgirl, or vertical bounce/rising poses to amplify vertical amplitude and upper-body secondary motion.
integrated_multimodal_description:
[Shot 1] dynvt1, keep the characters, clothing, environment, and overall composition from the first frame consistent. From the very first frame the two figures are already locked in extremely fast, maximum-intensity vertical rising-and-dropping motion with zero build-up. The repeated upward lift and downward drop run at the highest possible speed and frequency for the entire duration, delivering relentless, non-stop, high-amplitude pounding without any slowing or pause. Every cycle is large, forceful, and aggressive, creating continuous deep recoil, violent weight transfer, and explosive body momentum. The hips and lower body drive the motion at blistering pace, while the torso, shoulders, chest, waist, hair, and limbs shake violently with strong secondary motion and heavy follow-through on every single stroke. Chest bouncing is extreme, constant, and highly visible from start to finish. Preserve stable anatomy, keep both figures clearly separated, and keep the camera mostly steady so the ultra-fast body motion remains the sole source of intensity through the final frame.For more simplified or variant prompts, see the example image.
Current Status & Known Issues
This 1600-step proof-of-concept model was trained on RTX 4090D (48GB) using 20 video clips, aimed at validating motion feasibility rather than acting as a fully generalized solution.
Audio dynamic performance remains experimental and inconsistent, which will be further refined alongside dataset expansion and motion decoupling in future releases.
Description
FAQ
Comments (38)
Note: I encountered audio issues when using the 4-step LoRa workflow, but the audio worked fine when I used the official 25-step workflow. If anyone knows how to fix this problem, please let me know.
I solved this problem using a 4x lora with a weight of 0.9 in 9 steps. I also use the "spectrum for minimax" node to speed up
@FourBunny make sure you update kijai nodes and use the turbo lora sampler, "MiniMax-H3 Turbo Sampler (4-step)" Also set general steps to at least 6 or higher, even if it says "4step lora". Try MiniMax-H3-Turbo-Lora / minimax_h3_turbo_4step_ema_ckpt850.safetensors. Avoid "cache" nodes for now.
@mrsanders1313840 Did you replace it with the cache node? is the spectrum node faster than the cache node? I heard it is. I will test it anyways
@bhopping I'm not sure if the old caching nodes even work with this new system. spectrum is working. The minimum value of warmup_steps =3, the last 3 steps are never cached
@mrsanders1313840 there has been an update for spectrum and defaults to 1. you can try 3 through
@mrsanders1313840 I did a lil testing. 160s with just Easycache, 197s just Spectrum, 209s with neither. I’m definitely noticing quality loss with Easycache though. I think I prefer spectrum for better quality. Setting the spectrum to warmup_steps =3 helped with speed I think thanks. I might do more testing tomorrow to test 1 instead of 3. This was the settings I tested with Easycache if anyone was curious: reuse_threshold: 0.30 start_percent: 0.20end_percent: 0.90 verbose: false
@bhopping I definitely insist on 11 sampler steps, 9 steps also give a good sound, but 11 is much better. I also use an average resolution of 640x832 with "rts video super resolution" interpolation, maybe this will help you.
@mrsanders1313840 How do you upscaling a 640×832 video? Do you save it first and then upscaling it?
@FourBunny DaSiWa MiniMax H3 Workflows has it, its a solid workflow
@FourBunny After "vae decode", I set "RTX Video Super Resolution" with a coefficient of 1.5
this lora is what we needed from a long time
its working but can you make this like wihout using any pormpt,
OP literally posted a "with Lora" and "without Lora" example. Looks like it's doing its job to me
Feel free to test it without any prompt and see what results you get. It was mainly trained to work with trigger prompts, so without them the effect may be less consistent, but it’s worth trying.
@existentialcrisis that's not what this person is asking.
要速度不要画质也不行呀
示例图都是4步加速lora出来的,0.4比例,要画质的话可以加大步数和分辨率
Why are the trigger "words" so long? Do that actually need to be pasted into the prompt exactly like that?
The prompt is optional. The shorter prompts shown in the example images, just there to make it easier for me to apply them. This trigger has already been written as a generic template, you don’t have to use it—you can simply describe the intensity and amplitude of the shake.
Hilarious that he just copy pasted what he wrote in the description
thanks for trianing this! what settings did you use to train, if you used aitoolkit? I got up to 500 steps on a test lora then my samples in aitoolkit just turned to noise. I'm using a 5090.
The key is labeling and the dataset. Your dataset videos should ideally be no longer than 5 seconds. Select “Automatic Frame Count Training,” and make sure the camera doesn’t shake. For labeling, use the two official prompt template files. Send them to GPT or another AI model and ask it to tell you how to label your dataset; it will also advise you on the best settings. Basically, the default settings will work fine—just change the labeling rejection rate to 0.
Also, I disabled samples in aitookit, I tested it directly in ComfyUI.
will this work for positions like Mating Press?
I'm not sure either, but you can give it a try. It mainly enhances the shaking effect. I've tried it with SFW videos and it works well, so it should be compatible with most formats.
this is a great start ! now we just need the wan 2.2 sloptwerk lora (the best always on body/boob/ass.. flop, jiggle, fold, and bounce, lora) dude to make an h3 version so we can mix it with this and we be jammin' ;)
This works quite well. but it does have bugs. if you try to do forward\backward on a leaning forward cowgirl, the guy on the bottom disappears 😅
不知道为什么一直报错,这个是非剪枝模型和剪枝模型都通用的吗,还是只适用于其中一种,我之前用剪枝效果明显,但是剪枝有爆音,我就删除剪枝模型,下载了普通的int8模型,最近使用发现没有效果了,而且控制台报错
AITOOLKIT训练的,理论上可以通用,剪枝模型用最新出的那个加速LORA权重设置0.65就不爆音了,控制台报错你应该复制给AI看看是什么插件导致的,LORA文件一般不会导致报错
您好,我测试过了,确实是prun就不会报错,动态效果也会增强,一旦用了非剪枝模型,就一直报错,然后不生效
@www658qqcom899 感谢测试,那应该就是我这个版本的AITOOLKIT训练的不支持非剪枝模型
Perhaps you should mention what models it works with. It doesn't fx work with ref2va int8 convrot.
OK
Does anything work with ref2va for you bro? why am I able to get it to work?
Will you be making a version that works with ref2va?
I'll have to figure out how to get AITOOLKIT to support REF2VA training.
To get around the weird, robotic movement, try strength at .4 or even lower. If find it better to not have any camera movement in your shot, too.