Updated: Nov 10, 2026
base model
MiniMax-H3-Image for ComfyUI: fp8, NVFP4 and GGUF
The precisions of MiniMax-H3-Image that Comfy-Org's ComfyUI repack doesn't
include. These files are the diffusion model only. The text encoder, the VAE
and the bf16, int8 ConvRot and w4a8 versions are at
https://huggingface.co/Comfy-Org/MiniMax-H3-Image
Versions
- fp8 scaled, 21.0 GB: RTX 40 and RTX 50
- NVFP4, 12.5 GB: RTX 50, the fastest
- GGUF Q6_K 17.5 GB, Q4_K 12.5 GB, Q3_K 10.0 GB: any GPU, through ComfyUI-GGUF
- GGUF Q2_K mix, 9.25 GB: experimental, visibly softer
Requirements
- ComfyUI 0.44 or newer (MiniMax-H3-Image support was added on 10 November 2026)
- Text encoder qwen3vl_32b_minimax_h3_nvfp4_awq (or int8convrot) and VAE
minimax_h3_image_vae_fp16, both from Comfy-Org's repository above
- GGUF only: ComfyUI-GGUF must accept the "minimax_h3" architecture, or it
stops with "Unexpected architecture type in GGUF file: 'minimax_h3'". Until
that is merged upstream, run the patch script from the GGUF repo with the
Python that runs your ComfyUI, then restart ComfyUI:
https://huggingface.co/LSDJesus/MiniMax-H3-Image-GGUF/blob/main/patch_comfyui_gguf.py
python patch_comfyui_gguf.py PATH/TO/ComfyUI
python_embeded\python.exe patch_comfyui_gguf.py ComfyUI (Windows portable)
Or make the edit by hand: add "minimax_h3" to IMG_ARCH_LIST near the top of
custom_nodes/ComfyUI-GGUF/loader.py (the folder may be called comfyui-gguf).
How to use
Open ComfyUI's "MiniMax H3 Image" template and choose the file in Load
Diffusion Model. For a GGUF, replace that node with Unet Loader (GGUF). Keep
the template's settings: 6 steps, euler, simple, cfg 1. The model works best
between 4 and 20 megapixels, does poorly at low resolution, and expects long,
detailed English prompts (the template includes a prompt expander).
What was changed
Each file quantizes the same 200 transformer layers that Comfy-Org's int8 and
w4a8 files do, 95.8% of the weights. Everything else is unchanged from Comfy-Org's bf16
file. Side-by-side comparisons and full details:
https://huggingface.co/LSDJesus/MiniMax-H3-Image-fp8-nvfp4
https://huggingface.co/LSDJesus/MiniMax-H3-Image-GGUF
License
These files are modified (quantized) versions of MiniMax-H3-Image.
MiniMax-H3-Image is licensed under the MiniMax-H3-Image Community License
Agreement, Copyright © 2026 MiniMax. All Rights Reserved.
Full license: https://huggingface.co/MiniMaxAI/MiniMax-H3-Image/blob/main/LICENSE
By downloading or using these files you agree to that license, including its
use restrictions (Section V) and its Acceptable Use Policy (Exhibit A), which
apply to you. In particular:
- The license grants rights only outside the European Union, the United
Kingdom, South Korea and the United States.
- The model and its outputs may not be used to improve any other AI model.
- Above USD 1 million in annual revenue, or to offer the model as a hosted
service, you need written permission from MiniMax first:
https://platform.minimax.io/license
- Commercial products and services using it must display "MiniMax-H3-Image".
Powered by MiniMax-H3-Image.
====================================================================
ABOUT THIS VERSION (one per file)
=================================
--- fp8 scaled (minimax_h3_image_pruned_fp8_scaled.safetensors, 21.0 GB) ---
fp8 e4m3 weights with one scale per tensor. Runs natively on RTX 40 and
RTX 50: 2.1 steps/s at 2048x2048 on an RTX PRO 6000. The MLP output layer
(mlp.fc2) runs its matrix multiply in bf16, as in Comfy-Org's own H3 fp8
files; without that, images drifted badly. Modified file: quantized from
Comfy-Org's bf16.
--- NVFP4 (minimax_h3_image_pruned_nvfp4.safetensors, 12.5 GB) ---
4-bit floating point with an fp8 scale per 16 values. Runs natively on
RTX 50 / Blackwell, and is the fastest version: 3.4 steps/s at 2048x2048 on
an RTX PRO 6000. Other cards run it more slowly. Modified file: quantized
from Comfy-Org's bf16.
--- GGUF Q6_K (minimax_h3_image_pruned_Q6_K.gguf, 17.5 GB) ---
6.6 bits per weight; the closest of the GGUFs to the 8-bit versions. Needs
ComfyUI-GGUF patched for minimax_h3 (see the description). GGUF is about
1 step/s at 2048x2048 on an RTX PRO 6000. If your card runs Comfy-Org's w4a8
(RTX 30 or newer) or int8 ConvRot (RTX 20 or newer), those are faster at a
similar size. Modified file: quantized from Comfy-Org's bf16.
--- GGUF Q4_K (minimax_h3_image_pruned_Q4_K_imat.gguf, 12.5 GB) ---
4.5 bits per weight, quantized with an importance matrix from 12 calibration
images. Needs ComfyUI-GGUF patched for minimax_h3 (see the description). Modified file: quantized
from Comfy-Org's bf16.
--- GGUF Q3_K (minimax_h3_image_pruned_Q3_K_imat.gguf, 10.0 GB) ---
3.4 bits per weight with an importance matrix. The smallest version that
holds up well. Needs ComfyUI-GGUF patched for minimax_h3 (see the description). Modified file:
quantized from Comfy-Org's bf16.
--- GGUF Q2_K mix, experimental (minimax_h3_image_pruned_Q2_K_mix_imat.gguf, 9.25 GB) ---
Mostly 2-bit with an importance matrix. The first and last four blocks are at
Q4_K, and the attention output and MLP output layers are at Q3_K, because
plain 2-bit turns this model's images to noise. Images stay coherent but are
visibly softer: fine texture smears and small text can break. Only 0.75 GB
smaller than Q3_K. Needs ComfyUI-GGUF patched for minimax_h3 (see the description). Modified
file: quantized from Comfy-Org's bf16.