Instructions to use lightx2v/Minimax-h3-Turbo with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use lightx2v/Minimax-h3-Turbo with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline from diffusers.utils import load_image, export_to_video # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("lightx2v/Minimax-h3-Turbo", dtype=torch.bfloat16, device_map="cuda") pipe.to("cuda") prompt = "A man with short gray hair plays a red electric guitar." image = load_image( "https://huggingface.co/datasets/huggingface/documentation-images/resolve/main/diffusers/guitar-man.png" ) output = pipe(image=image, prompt=prompt).frames[0] export_to_video(output, "output.mp4") - Notebooks
- Google Colab
- Kaggle
I tested EVERY sampler Γ scheduler combo for MiniMax-H3 + LightX2V FL2V Turbo 4-step 1.0 so you DON'T need to
What I tested
The setup uses MiniMax-H3 with LightX2V's fl2v_turbo_4step LoRA:
I tested the full sampler Γ scheduler combination matrix.
Interestingly, there are quite a few combinations that produce good results besides the ones that have been discussed so far.
I also included combinations that normally benefit from higher step counts. They're not necessarily optimized for 4 steps, but I included them for completeness.
There's also a rating system at the top of the site. Since different sampler Γ scheduler combinations can produce surprisingly different results, I split the ratings into four separate dimensions:
Graphic Quality β overall image quality and whether the rendering looks correct
Motion Quality β motion, action sequencing, and whether the physics feel natural and coherent
Sound Effect Quality β whether voices and sound effects are generated correctly and match the scene
Music Quality β whether the background music is appropriate and correctly generated
Each category is rated from 1 to 5 stars.
If you find a combination that performs particularly well in any of these areas, please give it a rating. This should make it easier for everyone to identify which sampler Γ scheduler combinations are worth trying for different use cases.
I was short on time, so I used 480p instead of 768p for the comparison. The differences between the combinations are still quite apparent.
For consistency, all tests use the Baker example from Case 1 of the official MiniMax prompting guide.
Comparison:
Which one is the base (no lora) . It's hard to compare without it
this is so helpful, thank you.
What is your own verdict?

