---
license: apache-2.0
base_model:
- alibaba-pai/MiniMax-H3-Acc-LoRAs
- MiniMaxAI/MiniMax-H3
pipeline_tag: text-to-video
tags:
- comfyui
- lora
- minimax-h3
- video
- audio
- distillation
---

# MiniMax-H3 Acc LoRAs — ComfyUI conversion

ComfyUI-key repackaging of the **official
[alibaba-pai/MiniMax-H3-Acc-LoRAs](https://huggingface.co/alibaba-pai/MiniMax-H3-Acc-LoRAs)**
8-step PDD acceleration LoRAs for [MiniMax-H3](https://huggingface.co/MiniMaxAI/MiniMax-H3) —
full audio+video generation in **8 (or 4) sampler steps, CFG-free**.

**These are not plain LoRAs.** Each file carries a rank-64 trunk LoRA **plus** a Parallel
Decoding Distillation head bank (32 per-interval final-layer projections per modality,
[PDD — arXiv:2607.26004](https://arxiv.org/abs/2607.26004)). Loading them requires the
companion custom node pack:

➡️ **[Jalen-Brunson/ComfyUI-MiniMax-H3-PDD-Acc](https://github.com/Jalen-Brunson/ComfyUI-MiniMax-H3-PDD-Acc)**
(also loads the original alibaba-pai files directly — this repo just saves you the in-memory
conversion and gives you inspectable standard LoRA keys).

## Files

| File | Base trunk | sha256 |
|---|---|---|
| `minimax_h3_fl2va_pdd_acc_8step_comfyui.safetensors` | MiniMax-H3 **FL2VA** | `1dce71b9…5cda0ea` |
| `minimax_h3_ref2va_pdd_acc_8step_comfyui.safetensors` | MiniMax-H3 **Ref2VA** | `5531fa0d…bdc78a1` |

Put them in `ComfyUI/models/pdd_acc/`. Pair FL2VA with an fl2va UNET, Ref2VA with ref2va
(bf16 or int8-convrot builds both work).

## Usage (recipe is mandatory)

`UNETLoader → MiniMaxH3SigmaShift (12/3) → MiniMax H3 PDD Acc LoRA (Apply) → BasicGuider (CFG 1.0)`,
sampler **euler**, sigmas = **the Apply node's sigmas output** (the trained PDD block
boundaries) into `SamplerCustomAdvanced`. Strengths 1.0, `nfe` 8 (4 is also official). Remove
other distill LoRAs (turbo); don't stack step-caching nodes. A ready-to-run workflow ships in
the node pack's `example_workflows/`.

## What was converted

Trunk LoRA renamed from diffusers to ComfyUI H3 keys (`diffusion_model.*.lora_A/B.weight`
+ `.alpha`, 258 modules):

- `to_q/to_k/to_v` → `attn.qkv_proj`: concatenated `lora_A`, **block-diagonal** `lora_B`,
  alpha ×3 (keeps the per-branch scale exactly 1.0)
- `ff.net.0.proj` → `mlp.fc1`: SwiGLU `[value;gate]` → `[gate;value]` `lora_B` row half-swap
- `to_out.0` → `attn.out_proj`, `ff.net.2` → `mlp.fc2`, `adaln_proj.linear` copied 1:1
  (modulation layouts verified bit-identical between the two implementations)
- `token_refiner.refiner_blocks.N` → `token_refiner.blocks.N`

The PDD head bank (`proj_out` [32,96,5376], `audio_proj_out` [32,32,5376] + biases) is kept
byte-for-byte unchanged. Conversion is verified **bit-identical** to what the node pack
computes in memory from the original files, and the converter CLI + 13-test suite live in the
GitHub repo. Full provenance (source file sha256, transform description) is embedded in each
file's safetensors metadata.

## Credits

All training credit to [alibaba-pai](https://huggingface.co/alibaba-pai) (Apache-2.0 release)
and the PDD authors (Shaul et al.); base model by
[MiniMaxAI](https://huggingface.co/MiniMaxAI). This repo is a format conversion only.