Downloads · 30 days
590K
55% of all-time downloads
Abiray/MiniMax-H3-Pruned-GGUF
MiniMax-H3-Pruned-GGUF is a image-text-to-video model from Abiray. Use it for the image-text-to-video task on the model card, and read the license before you ship it in a product. The card lists the license as other.
<video controls autoplay loop muted style="width: 100%; border-radius: 8px;" src="https://huggingface.co/Abiray/MiniMax-H3-Pruned-GGUF/resolve/main/video/MiniMaxH300002-audio.mp4"</video
Downloads · 30 days
590K
55% of all-time downloads
All-time downloads
1.1M
Public
Repo size
197 GB
Likes
79
Trending 1
Click a slice to open those files.
.gguf197 GB · 100%
From the Hugging Face model README
<video controls autoplay loop muted style="width: 100%; border-radius: 8px;" src="https://huggingface.co/Abiray/MiniMax-H3-Pruned-GGUF/resolve/main/video/MiniMax_H3_00002-audio.mp4"></video>
This repository (Abiray/MiniMax-H3-Pruned-GGUF) provides pruned and quantized GGUF weights for the MiniMax H3 omni-modal generative model. MiniMax H3 is designed for unified multimodal context processing, capable of generating synchronized high-definition video and 32 kHz stereo audio from text, image, audio, and video inputs.
ComfyUI-GGUF workflows using the native MiniMax backend.FL2VA (First/Last Frame) and Ref2VA (Omni-Reference) modes.Note: For optimal performance, Q4_K_M is recommended for 16 GB GPUs, while Q5_K_M is recommended for GPUs with 24 GB VRAM.
| Quantization | File Name | Size | Target Hardware / Use Case |
|---|---|---|---|
| Q3_K_M | MiniMax-H3-FL2VA-Pruned-Q3_K_M.gguf | 8.9 GB | Low VRAM (~12 GB GPUs) |
| Q4_K_M | MiniMax-H3-FL2VA-Pruned-Q4_K_M.gguf | 11.6 GB | Recommended Balance (16 GB GPUs) |
| Q4_K_S | MiniMax-H3-FL2VA-Pruned-Q4_K_S.gguf | 11.6 GB | Compact 4-bit K-Quant |
| Q5_K_M | MiniMax-H3-FL2VA-Pruned-Q5_K_M.gguf | 14.1 GB | High Quality Balance (24 GB GPUs) |
| Q5_K_S | MiniMax-H3-FL2VA-Pruned-Q5_K_S.gguf | 14.1 GB | Compact 5-bit K-Quant |
| Q6_K | MiniMax-H3-FL2VA-Pruned-Q6_K.gguf | 16.7 GB | Near-Lossless Precision |
| Q8_0 | MiniMax-H3-FL2VA-Pruned-Q8_0.gguf | 21.6 GB | Maximum Fidelity / Reference |
| Quantization | File Name | Size | Target Hardware / Use Case |
|---|---|---|---|
| Q3_K_M | MiniMax-H3-Ref2VA-Pruned-Q3_K_M.gguf | 8.9 GB | Low VRAM (~12 GB GPUs) |
| Q4_K_M | MiniMax-H3-Ref2VA-Pruned-Q4_K_M.gguf | 11.6 GB | Recommended Balance (16 GB GPUs) |
| Q4_K_S | MiniMax-H3-Ref2VA-Pruned-Q4_K_S.gguf | 11.6 GB | Compact 4-bit K-Quant |
| Q5_K_M | MiniMax-H3-Ref2VA-Pruned-Q5_K_M.gguf | 14.1 GB | High Quality Balance (24 GB GPUs) |
| Q5_K_S | MiniMax-H3-Ref2VA-Pruned-Q5_K_S.gguf | 14.1 GB | Compact 5-bit K-Quant |
| Q6_K | MiniMax-H3-Ref2VA-Pruned-Q6_K.gguf | 16.7 GB | Near-Lossless Precision |
| Q8_0 | MiniMax-H3-Ref2VA-Pruned-Q8_0.gguf | 21.6 GB | Maximum Fidelity / Reference |
v0.30.0 or higher is required for native MiniMax-H3 architecture support.ComfyUI-GGUF custom node package installed..gguf variant from the table above..gguf file into the ComfyUI/models/unet/ directory.UnetLoaderGGUF node.H3-Base-FL2VA (First-and-Last-Frame Mode):
H3-Base-Ref2VA (Omni-Reference Mode):
MiniMax H3 is released under the MiniMax H3 Community License Agreement. Please refer to the MiniMaxAI/MiniMax-H3 repository and the repository's LICENSE file for full terms and commercial usage guidelines.