README.md

---
language: en
tags:
- video-generation
- minimax-h3
- int8
- convrot
- turbo
- h3ddle
- pulpcut
license: other
license_name: minimax-h3-community-license
license_link: https://huggingface.co/MiniMaxAI/MiniMax-H3/blob/939557dc319dd91227e30195a763f272ba7f8765/LICENSE
base_model: MiniMaxAI/MiniMax-H3
pretty_name: PulpCut MiniMax H3 Turbo INT8 ConvRot
---

# MiniMax H3 Turbo · pruned INT8 ConvRot (single file)

## What this repository is

A single-file MiniMax H3 FL2VA diffusion transformer with the lightx2v
**turbo step-distillation merged into the weights**, quantized in the same
pruned **INT8 ConvRot** layout as the Comfy-Org release. It is a drop-in
replacement for `minimax_h3_fl2va_pruned_int8_convrot.safetensors` in any
runtime that reads the optimized INT8 single-file layout — including
[H3ddle](https://github.com/AlexanderIstomin/h3ddle), the open-source native
macOS app it was built for.

This file is **not a standalone model**. It needs the rest of the optimized
package (Qwen3-VL-32B INT8 text encoder, video/audio VAEs, tokenizer) from
[Comfy-Org/MiniMax-H3](https://huggingface.co/Comfy-Org/MiniMax-H3).

## Why this merge was made and republished

Step-distilled turbo checkpoints reach roughly 20-pass visual quality in
6–8 denoising passes, which is the difference between usable and unusable
generation times on low-memory Apple-silicon machines. No hosted turbo
variant existed in the INT8 ConvRot format that memory-constrained
runtimes stream from disk, so we merged and requantized one. H3ddle's
managed model downloads also require a pinned, hash-verified hosted
artifact, which this repository provides.

## Known behavior and limitations

The pruned ComfyUI conversion of the turbo LoRA **drops all 51 AdaLN
adapter pairs** (the source targets AdaLN input dimension 2688, while
pruned "compact-curve" models use dimension 8), and its own metadata warns
that four-step distillation behaviour may therefore be degraded.

In our testing that gap did **not** produce a measurable prompt-adherence
penalty. Every prompt-following miss we observed at 256²–512² with 6–8
passes — wrong subject species, illustration-style output, text-like
artifacts — is reproduced by the **unmodified base package at matched
settings, seed, and canvas**, so those are properties of the base model at
low step counts rather than effects of the distillation. What the merge
does change is fidelity: detail, fur, and lighting improve substantially at
the same step count. We asked the turbo authors about a curve-compatible
variant in
[ModelTC/Minimax-H3-Turbo#7](https://github.com/ModelTC/Minimax-H3-Turbo/issues/7).

Recommended settings: 6–8 denoising passes, euler sampling, all 50 blocks.
A Beta(0.6, 0.6) sigma schedule is commonly paired with turbo checkpoints;
we measured no consistent difference against the released linear grid on
this package.

## How the merge/quantization is done (high level)

For each of the 200 quantized projections, the BF16 pruned base weight is
merged with `strength × B·A` (rank-64, strength 1.0, `ema_pruned`
variant), rotated by the grouped 256-wide Hadamard transform used by the
ConvRot runtime kernels, and requantized with symmetric per-row absmax
INT8 scales. Token-refiner adapters merge losslessly in BF16. All other
tensors are copied byte-identical from the official INT8 file. The
pipeline reproduces the official quantizer exactly: run at strength 0 it
regenerates the official file with all 3,046,400 scales identical and
1,682 of 19.27 billion int8 values differing (rounding ties).

## Source and attribution

- Original model: [MiniMaxAI/MiniMax-H3](https://huggingface.co/MiniMaxAI/MiniMax-H3)
- Pruned INT8 ConvRot base + shared package files: [Comfy-Org/MiniMax-H3](https://huggingface.co/Comfy-Org/MiniMax-H3)
- Turbo distillation LoRA: [ModelTC/Minimax-H3-Turbo](https://github.com/ModelTC/Minimax-H3-Turbo) (lightx2v team)
- Pruned ComfyUI LoRA conversion: [drbaph/MiniMax-H3-Turbo-Lora-ComfyUI](https://huggingface.co/drbaph/MiniMax-H3-Turbo-Lora-ComfyUI)

## Licensing

Derivative of MiniMax H3 weights; the
[MiniMax H3 Community License Agreement](https://huggingface.co/MiniMaxAI/MiniMax-H3/blob/939557dc319dd91227e30195a763f272ba7f8765/LICENSE)
applies. By downloading you agree to its terms.

## What this file is used for in H3ddle

H3ddle installs it as the **"MiniMax H3 · Turbo (Experimental)"** managed
model: the app verifies the SHA-256 below, reuses the shared package files
it already has via hardlinks, and defaults the model to 8 passes. Published by [PulpCut](https://huggingface.co/PulpCut),
whose editor family shares the local-first media generation stack that
H3ddle implements in the open.

## Safety and intended use

Intended for local, personal video generation. The merge changes speed
characteristics, not the base model's content behavior; all usage
restrictions of the MiniMax H3 Community License apply unchanged.

## File inventory

| File | Bytes | SHA-256 |
|---|---|---|
| `minimax_h3_fl2va_pruned_turbo_int8_convrot.safetensors` | 20,970,379,854 | `9ad5c98b533894c122050d32804a14f49fca8edc16c52564a281cdc5825ac934` |

## Reproducibility references

The conversion is a single dependency-free Python script,
[`Scripts/convert-turbo-package.py`](https://github.com/AlexanderIstomin/h3ddle/blob/main/Scripts/convert-turbo-package.py)
in the H3ddle repository, including the strength-0 self-check used to
validate the pipeline against the official file.

## Contact

Open an issue in the [H3ddle repository](https://github.com/AlexanderIstomin/h3ddle/issues).