MiniMax H3 Kiss LoRA V0.1 Released

Hi everyone,

After I released my Wan2.2 Kiss LoRA, it received some positive feedback and support from the community.

However, Wan2.2 is starting to feel quite old to me now. The model itself has many limitations, and after MiniMax recently open-sourced H3, I almost immediately lost interest in continuing with Wan2.2.

H3 is an extremely powerful model, and I personally believe it has a good chance of becoming one of the mainstream open-source video models in the community, while Wan2.2 may gradually fade into the background.

Since H3 was released, I have been experimenting with many of its features, especially its multi-image reference video generation, which I find very interesting and fun to use.

Naturally, I decided to try training my Kiss LoRA on H3 as well.

Training Settings

I used the same video dataset that I previously used for my Wan2.2 Kiss LoRA.

The dataset itself has some limitations. Most of the source videos were collected quite a while ago, and many of them are relatively low-resolution and not particularly sharp.

Training settings:

• Resolution: 512 × 512

• Video length: about 5 seconds

• Frames: 124 frames

• FPS: 24

• Audio: disabled

• Training steps: 1750

• LoRA Rank: 32

Important Note About H3 LoRA Training

Please keep in mind that H3 has only been open-sourced for a very short time, and LoRA training support is still highly experimental.

At the time I trained this V0.1 model, I used AI Toolkit's early MiniMax H3 training implementation.

Interestingly, shortly after I finished this training, AI Toolkit added an alpha version of a dedicated MiniMax H3 Training Adapter.

This may be important because some early H3 LoRA users have reported strange behavior with previous training implementations, such as:

• LoRAs training successfully but having weak effects

• inconsistent behavior between I2V and reference-based generation

• image or audio quality degradation

• LoRAs becoming unstable after additional training

There is currently some speculation that H3's architecture and guidance-distilled training design may require more specialized handling than conventional video LoRA training.

Therefore, this V0.1 LoRA was trained before the new alpha Training Adapter became available.

This is another reason why I consider this release highly experimental.

I plan to test the newer H3 training implementation in future versions.

Does It Work?

Surprisingly, yes.

Despite all of the above, the LoRA does have an effect.

However, its behavior depends heavily on the generation mode.

I2V

For standard Image-to-Video, the effect seems relatively weak or inconsistent.

Sometimes I can see the LoRA influencing the motion, while in other generations the effect is barely noticeable.

I am currently not completely sure why this happens.

Multi-Image Reference / Reference-to-Video

With H3's multi-image reference / reference-based video generation, the LoRA works much more noticeably.

This is currently the workflow where I get the best results from V0.1.

However, the generated video can sometimes look a little blurry.

My current guess is that this is mainly caused by the relatively low quality and limited resolution of my original training dataset, although the still-evolving H3 training implementation may also be a factor.

Trigger Words

As with my previous Kiss LoRA, there is no special trigger word.

Just describe the action directly.

For example:

• kiss

• tongue kiss

• passionately kiss

• spit

• and similar descriptions

Feel free to experiment with your own prompts.

Recommended LoRA Strength

I recommend starting with a LoRA strength of 0.5.

In my testing, this LoRA generally works best at relatively low strengths. I recommend keeping the strength below 0.7 whenever possible.

Suggested range:

• 0.4–0.5: Recommended for most cases

• 0.5: My current recommended default

• 0.6–0.7: Stronger effect, but may start affecting image quality or motion stability

• Above 0.7: Generally not recommended

Higher strength does not necessarily produce a better kissing motion. In some cases, pushing the LoRA too strongly may introduce more blur, artifacts, or unnatural motion.

For this experimental V0.1 release, I recommend starting at 0.5 and adjusting slightly depending on your prompt and reference images.

Future Plans

For now, I will most likely stop updating the Wan2.2 version of this LoRA.

My future development will mainly focus on MiniMax H3.

For the next version, I plan to experiment with newer H3 training methods, including the newly added AI Toolkit H3 Training Adapter, and possibly improve the training dataset with higher-quality video clips.

This V0.1 release should therefore be considered a first experimental H3 version, rather than a finished or fully optimized LoRA.

Feel free to test it, experiment with different H3 workflows, and share your results.

And finally, thank you to MiniMax for open-sourcing such an impressive model.