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SanDiegoDude/H3-Turbo-6-Step-LoRA-Comfy
H3-Turbo-6-Step-LoRA-Comfy is a text-to-video model from SanDiegoDude. Use it when you need video from a text prompt. It is set up for minimax-h3. The card lists the license as apache-2.0.
ComfyUI-native conversions of larryvrh/MiniMax-H3-Turbo-Lora, so they load with the stock LoraLoader against core MiniMax-H3 support — no custom nodes, no custom sampler.
Downloads · 30 days
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Updated Aug 7, 2026
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From the Hugging Face model README
ComfyUI-native conversions of larryvrh/MiniMax-H3-Turbo-Lora,
so they load with the stock LoraLoader against core MiniMax-H3 support — no custom
nodes, no custom sampler.
All credit for the actual training goes to larryvrh. These are just format conversions of that work. Base model is Comfy-Org/MiniMax-H3.
These are BF16 and expect a BF16 pipeline. They will not behave correctly in FP16.
Upstream is named "4step". In practice 4 steps is a little weak — 6 steps is the sweet spot. The files here are renamed accordingly; the weights are unchanged.
| file | for base checkpoint |
|---|---|
minimax_h3_turbo_6step_ema.safetensors | minimax_h3_fl2va_bf16 |
minimax_h3_turbo_6step.safetensors | minimax_h3_fl2va_bf16 |
minimax_h3_turbo_6step_ema_fl2va_pruned.safetensors | minimax_h3_fl2va_pruned_int8_convrot |
minimax_h3_turbo_6step_fl2va_pruned.safetensors | minimax_h3_fl2va_pruned_int8_convrot |
Start with the EMA one. It is noticeably cleaner than the non-EMA variant.
The _fl2va_pruned pair are remapped for the pruned int8/convrot checkpoint rather
than the full BF16 one. Match the LoRA to the checkpoint you actually loaded.
Trained for fl2va (first/last-frame), but it works on the ref2va
(reference-to-video) path too, even though it was never trained for it. Pleasant
surprise — worth trying.
Sampler euler, scheduler beta57, 6 steps.
Strongly recommended: schedule the LoRA strength rather than pinning it flat. Using SCG LoRA Scheduler from SanDiegoDude/scg-utils:
| setting | value |
|---|---|
strength_start | 4.00 |
strength_end | 1.00 |
start_percent | 0.100 |
end_percent | 0.990 |
interpolation | linear |
cutoff_outside_window | true |
strength_clip | 1.00 |
Ramping down from 4.0 to 1.0 across the run gives the best output I've found so far.
Apache-2.0, same as upstream.