Alissonerdx/Minimax-H3-ComfyUI · Hugging Face

Source: https://huggingface.co/Alissonerdx/Minimax-H3-ComfyUI

https://huggingface.co/Alissonerdx/Minimax-H3-ComfyUI#minimax-h3-loras-for-comfyuiMinimax H3 LoRAs for ComfyUI

LoRAs forMiniMax H3, built to run in ComfyUI with theComfy-Org/MiniMax-H3weights. Trained and tested mainly against theref2vabase model;fl2vashould also work as a base but is less tested.

https://huggingface.co/Alissonerdx/Minimax-H3-ComfyUI#repository-structureRepository structure

loras/
  minimax_h3_lms_v1.0_r64.safetensors   # the LMS LoRA
workflows/
  minimax_h3_lms_workflow.json          # ComfyUI workflow set up for the LoRA above
examples/
  comparison-1.mp4                      # before/after, no audio
  comparison-2-audio.mp4                # before/after, with audio
  comparison-3-audio.mp4                # before/after, with audio
  comparison-4.mp4                      # before/after, no audio
  comparison-5.mp4                      # before/after, no audio
  comparison-6.mp4                      # before/after, no audio
  comparison-7.mp4                      # before/after, no audio
  comparison-8.mp4                      # before/after, no audio

https://huggingface.co/Alissonerdx/Minimax-H3-ComfyUI#minimax_h3_lms_v10_r64–a-little-more-sharpnessminimax\_h3\_lms\_v1\.0\_r64— “a little more sharpness”

Rank-64 LoRA for MiniMax H3ref2vathat sharpens a source video while keeping it photorealistic. It conditions on the source through guide latents rather than through the model’s native reference-video node.

Trigger / caption:

Enhance this video with sharp, crisp details while preserving a natural photorealistic appearance.

https://huggingface.co/Alissonerdx/Minimax-H3-ComfyUI#how-the-guide-worksHow the guide works

This LoRA conditions on your source video as a latent guide, not as a text description of it.

The source clip is encoded by the video VAE and packed into the transformer’s sequence as a conditioning block that is aligned to the target timeline. Three properties define the arrangement:

• **Same temporal origin.**The guide’s clock starts where the target’s starts, so guide latent frameisits at the same position as target latent framei.
• **Same spatial grid.**The guide is encoded at the target’s resolution, so guide token\(t, y, x\)lands on target token\(t, y, x\).
• **It does not advance the reference clock.**Unlike an ordinary reference block, an aligned guide occupies the target’s own timeline rather than being appended before it.

The result is that attention between guide and target costs nothing positionally — the correspondence is handed to the model instead of being something it has to search for. This is the same arrangement used by in-context video LoRAs on LTX.

The guide is held near-clean during training (about 0.1% noise augmentation) while the target is noised normally, so the model learns to map one to the other rather than to denoise both.

The text encoder never sees the guide. Only the caption reaches it; the video reaches the transformer purely as latents. The model therefore learns a pixel-level correspondence with the source, not a paraphrase of it.

https://huggingface.co/Alissonerdx/Minimax-H3-ComfyUI#using-itUsing it

Feed the source clip into the guide input, anchored at frame 0, at the same resolution as the output. Both the guide and the target must land on the model’s valid clip lengths —17k \+ 5frames (5, 22, 39, 56, 73, 90, 107, 124, …). A guide that is shorter than the target, or at a different resolution, breaks the alignment.

In ComfyUI this is the nativeMiniMaxH3AddGuidenode withframe\_idx = 0— it ships with ComfyUI’s own MiniMax H3 support, nothing extra to install for it. This is a different mechanism from the also-nativeMiniMaxH3ReferenceToVideonode, which passes a reference block with its own clock instead of an aligned guide.

This LoRA was trained specifically forref2va, notfl2va, and primarily to use guide latents alone, so treatMiniMaxH3ReferenceToVideoas optional/experimental here: combining it withAdd Guidecan be worth trying, but expect different — not necessarily better — results, since you’d be feeding two different kinds of conditioning at once. In principle this LoRA is meant for a second pass (sharpening an already-generated clip) rather than direct generation from scratch, though it can be used for the latter too — just expect it to behave differently.

The included workflow (workflows/minimax\_h3\_lms\_workflow\.json) additionally wires inAIToolkitMiniMaxH3RefVideo, a node fromostris/ComfyUI-AIToolkit-MiniMaxH3— clone that repo into your ComfyUIcustom\_nodes/folder for the workflow to load as-is. This LoRA was trained withai-toolkit’s custom fork that added guide-latent support, which is where this node comes from. As far as I can tell it just resizes the clip to the target resolution before feeding it in, so if you’d rather not add the dependency, swap it for any other resize step feeding intoAdd Guide.

https://huggingface.co/Alissonerdx/Minimax-H3-ComfyUI#examplesExamples

https://huggingface.co/Alissonerdx/Minimax-H3-ComfyUI#licenseLicense

Apache 2.0. Base model credit toMiniMaxAIand the ComfyUI-ready weights fromComfy-Org. Guide-latent training support and the ComfyUI node credit toostris(ai-toolkit,ComfyUI-AIToolkit-MiniMaxH3).