Instructions to use devin-lai/MiniMax-H3-Image-mlx with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- MLX
How to use devin-lai/MiniMax-H3-Image-mlx with MLX:
# Download the model from the Hub pip install huggingface_hub[hf_xet] hf download devin-lai/MiniMax-H3-Image-mlx --local-dir MiniMax-H3-Image-mlx
- Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- LM Studio
- Atomic Chat
Download comparisons/README.md from devin-lai/MiniMax-H3-Image-mlx: direct link, hf CLI and curl.
- Browser
- Download file 3.81 kB
-
https://huggingface.co/devin-lai/MiniMax-H3-Image-mlx/resolve/main/comparisons/README.md
- Command line
-
hf download hf://devin-lai/MiniMax-H3-Image-mlx/comparisons/README.md
-
curl -L -o README.md https://huggingface.co/devin-lai/MiniMax-H3-Image-mlx/resolve/main/comparisons/README.md
Image comparison gallery
All comparison pictures are actual recorded inference outputs. Each stack contains labeled full frames, identical 1:1 crops and absolute RGB differences amplified eight times. Metrics apply to full-resolution images, not previews.
| Comparison | Viewer | Image stack | Native detail crops |
|---|---|---|---|
| 2K product: BF16 tuning, Q8, Q4, three-pass preview | Open | Frames | Details |
| 2K portrait: native BF16 vs Q8 | Open | Frames | Details |
| Same final latent: VAE batches 1, 4, 8, 16 | Open | Frames | Details |
| Saved CUDA BF16 vs MLX, product | Open | Frames | Details |
| Saved CUDA BF16 vs MLX, portrait | Open | Frames | Details |
| Saved CUDA BF16 vs MLX, native 4K | Open | Frames | Details |
The editing demonstration places the input reference beside the native MLX emerald-glass edit. It is a functional example, not a pixel-similarity comparison.
The CUDA comparison uses the original saved RTX 5090 BF16 run with upstream
quality=lossless. Its hardware and decoder quality setting differ from the
MLX native tile recipe. It provides visual context; it does not isolate port
error or establish a same-hardware speedup.
The default MLX BF16 output is the reference for the quantization/tuning comparisons. Q8, Q4, fused kernels and fewer steps change its pixels. Read the experiment report before selecting a profile.
Full-resolution Mac outputs and trace tensors are retained locally under
outputs/suite/ (ignored by Git). Source hashes, configuration, memory and
timing records are exported under reports/inference/ and each gallery's
metrics.json. Original model weights are not included.