---
license: other
license_name: minimax-h3-community-license
license_link: LICENSE
base_model: stdstu123/LynnReal-Onmi-beta-0.1
tags:
- minimax-h3
- vae
- video-generation
- text-to-video
- onnx
- tensorrt
- diffusers
---

# MiniMax H3 — light video VAE decoder (diffusers + ONNX)

A converted copy of the **light video VAE decoder of LynnReal-Omni** (LynnReal-AI), made for the
**MiniMax H3 WebUI on Google Colab**. It decodes ordinary [MiniMax H3](https://huggingface.co/MiniMaxAI/MiniMax-H3)
latents with **26 transformer blocks instead of 36**. **Unofficial** — not affiliated with, endorsed by, or
supported by MiniMax or LynnReal-AI.

> ⚠️ **Modified files.** Source: [stdstu123/LynnReal-Onmi-beta-0.1](https://huggingface.co/stdstu123/LynnReal-Onmi-beta-0.1),
> `comfyui/models/vae/lynnreal_omni_light_vae_fp16.safetensors`
> ([github.com/LynnReal-AI/LynnReal-Omni](https://github.com/LynnReal-AI/LynnReal-Omni)).
> We did not retrain it. We (1) converted the ComfyUI key layout to the diffusers layout (the fused
> `to_qkv` projection was split back into `to_q` / `to_k` / `to_v`, head-interleaved, head dim 64),
> (2) stored it in fp16, and (3) exported one decoding tile to ONNX (RMSNorm rewritten with basic ops
> for opset 17).

## Files

| File | What | Size |
|---|---|---|
| `lynnreal_light_vae_decoder_fp16.safetensors` | `decoder.*` and `post_quant_conv.*` with diffusers `AutoencoderKLMiniMaxH3` key names, fp16 (26 decoder blocks) | 3.3 GB |
| `lynnreal_light_vae_decoder.onnx` + `lynnreal_light_vae_decoder.onnx.data` | One tile, `decoder(post_quant_conv(z))`: latent `latent_tile` `1×24×7×16×16` → pixels `pixel_tile` `1×3×28×256×256`; no normalization in or out (same interface as `lihaoyun6/MiniMax-H3-VAE-ONNX`); opset 17, fp16, external data in one file | 3.3 GB |
| `.complete` | File sizes and SHA-256 | — |

The encoder, latent space and temporal structure are those of the official MiniMax H3 VAE; only the
decoder differs. Take the encoder (and the audio VAE) from the official repository.

## Usage

**diffusers** — load the official `AutoencoderKLMiniMaxH3`, keep the first 26 entries of
`vae.decoder.transformer_blocks`, then load this file:

```python
import torch.nn as nn
from safetensors.torch import load_file
vae.decoder.transformer_blocks = nn.ModuleList(list(vae.decoder.transformer_blocks)[:26])
missing, unexpected = vae.load_state_dict(load_file("lynnreal_light_vae_decoder_fp16.safetensors"), strict=False)
# missing should list only encoder.* / quant_conv.* weights
```

**TensorRT** — compile the ONNX file with a fixed input profile `1×24×7×16×16` (FP16), then tile the
latent in time (5 latent frames + 2 overlap) and space (256 px tiles, ≥64 px overlap) as diffusers'
`_decode` / `_decode_clip` do.

Measured on RTX PRO 6000 (G4), 1280×704 / 124 frames: **5.2 s with TensorRT** (official decoder with
TensorRT: 7.1 s; this decoder in PyTorch: 8.3 s). TensorRT output matches the PyTorch output at 52.8 dB.

## License

This is a **Model Derivative of MiniMax H3** (LynnReal-Omni's decoder is a distilled derivative of the
MiniMax H3 video VAE decoder) and is distributed, as LynnReal-AI distributes it, under the
**MiniMax H3 Community License Agreement** (`LICENSE`, a copy of the original). By downloading or using it
you agree to its terms and its Acceptable Use Policy. No additional or different terms are imposed.

> MiniMax H3 is licensed under the MiniMax H3 Community License Agreement, Copyright © 2026 MiniMax. All Rights Reserved.

Main points of the Community License (read `LICENSE` for the binding text):

1. **Territory** — no rights are granted to use, reproduce, modify, distribute or display the model
   or its outputs in the **European Union, the United Kingdom, South Korea or the United States**.
2. **Commercial use** — if your commercial products and services generate more than **USD 20 million**
   in yearly revenue, you need separate prior written authorization from MiniMax (api@minimax.io). A commercial
   product or service that uses MiniMax H3 must **prominently display "MiniMax H3"** in its user interface.
3. **Outputs** — do not use the model or its outputs to improve any AI model other than MiniMax H3 and
   its derivatives.
4. **Acceptable Use Policy** — Exhibit A of the license applies to every use.

---

## 日本語概要

LynnReal-AI の **LynnReal-Omni** が配布している軽量の映像 VAE デコーダーを、**MiniMax H3 WebUI on Google Colab** 用に
変換したものです。MiniMax H3 の潜在を、transformer **36 ブロックではなく 26 ブロック**でデコードします。
**非公式**で、MiniMax 社・LynnReal-AI とは無関係です。

> ⚠️ **改変したファイルです。** 出典は [stdstu123/LynnReal-Onmi-beta-0.1](https://huggingface.co/stdstu123/LynnReal-Onmi-beta-0.1) の
> `comfyui/models/vae/lynnreal_omni_light_vae_fp16.safetensors` です。再学習はしていません。
> **名前の並びを diffusers 形式に変換（結合された to_qkv を to_q / to_k / to_v に分割）・fp16 で保存・
> 1 タイルぶんを ONNX に書き出し（RMSNorm を基本演算に書き換え）**の改変をしています。

| ファイル | 中身 |
|---|---|
| `lynnreal_light_vae_decoder_fp16.safetensors` | diffusers の名前の decoder.* と post_quant_conv.*（fp16・26 ブロック） |
| `lynnreal_light_vae_decoder.onnx`（＋ `.onnx.data`） | 1 タイル（潜在 1×24×7×16×16 → 画素 1×3×28×256×256）。TensorRT 用 |

エンコーダー・潜在は公式の MiniMax H3 VAE と同じです（エンコーダーと音声 VAE は公式から取ります）。

**ライセンス**: MiniMax H3 の派生物として、配布元（LynnReal-AI）と同じ **MiniMax H3 Community License Agreement**（`LICENSE`）で
配布します。追加の条件は付けません。詳細は `NOTICE`。

- **地域**: **EU・英国・韓国・米国**では、モデルと出力の使用・複製・改変・配布・表示の権利は与えられていません
- **商用**: 商用の製品・サービスの年間売上が 2,000 万米ドルを超える場合は、事前に MiniMax の書面許諾（api@minimax.io）が必要です。MiniMax H3 を使う商用の製品・サービスは UI に「MiniMax H3」を目立つように表示します
- **出力**: モデルや出力を、MiniMax H3 とその派生以外の AI モデルの改善に使ってはいけません
- **AUP**: ライセンスの Exhibit A（利用規定）が適用されます