aptech0081 / MiniMax-H3-Acc-LoRAs-ComfyUI

MiniMax-H3 Acc LoRAs — ComfyUI conversion

ComfyUI-key repackaging of the official alibaba-pai/MiniMax-H3-Acc-LoRAs 8-step PDD acceleration LoRAs for 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 ). Loading them requires the companion custom node pack:

➡️ 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

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 (Apache-2.0 release) and the PDD authors (Shaul et al.); base model by MiniMaxAI . This repo is a format conversion only.