MiniMax H3 FL2V LightX2V 4-Step Int8-ConvRot
_Clip 1: v1 4step | Clip 2: v1 8step_
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_v0.1 4step demo_
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Model description
Requirements
- ComfyUI (recent - tested on master 0.31.0)
- ComfyUI-LoraInt8Loader custom node (standard ComfyUI LoRA loaders cannot dequantize it)
Files
| File | Size | NDownload |
|---|---|---|
| minimax_h3_fl2v_turbo_4step_v1.0_int8_convrot | 991 MB | download|
| minimax_h3_fl2v_turbo_8step_v1.0_int8_convrot | 991 MB | Download |
| minimax_h3_fl2v_turbo_4step_v0.1_int8_convrot | 991 MB | Download | 0.99 GB | Full LoRA |
- Both are quantized from the KJ comfy-converted BF16 LoRA.
norefiner variant
The full LoRA also patches the model's token_refiner - the text/audio
conditioning refiner. The norefiner variant removes those 8 patches so the
conditioning path runs at base quality (_some video clips had bad audio. This solution fixed it, but keep in mind it doesn’t happen always_).
If audio/text conditioning feels weak with the full LoRA at 4 steps, try the norefiner variant.
_First clip: with refiner | last clip: norefiner_
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Usage (ComfyUI)
1. Unzip the ComfyUI-LoraInt8Loader custom node into custom_nodes, restart
2. In your MiniMax H3 workflow, add LoRA Loader (Int8-ConvRot), select the
file, strength 1.0 (the training scale is already baked in)
3. Sample at 4-6 steps
Download model
Download them in the Files & versions tab.