Instructions to use MiniMaxAI/MiniMax-H3-Image with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use MiniMaxAI/MiniMax-H3-Image with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("MiniMaxAI/MiniMax-H3-Image", dtype=torch.bfloat16, device_map="cuda") prompt = "Astronaut in a jungle, cold color palette, muted colors, detailed, 8k" image = pipe(prompt).images[0] - Notebooks
- Google Colab
- Kaggle
Test, comparison with the original MiniMax H3
Thanks for the model, it's really impressive!
Here's a quick comparison with the original MiniMax H3.
The level of detail has improved significantly, and it now feels like a fully capable image generation model. This is what we were missing.
The only thing I've noticed is that character likeness seems slightly worse. The video model still does a better job of preserving character identity and resemblance.
Which is a bit of a shame, since that was one of the model's strong points.




Yeah, the video model was able to make character sheets almost perfectly with references and grabbing the first frame. This image model is faster even with higher resolution if you know your prompt and skip the enhancer, but the face likeness is not good most of the time. At least the couple of video LoRAs I tried did work for the image model, so I love that compatibility.