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MiniMax H3 W4A8 experimental models

by Kijai

Community-quantized W4A8 and int8 VAE checkpoints of MiniMax H3 video model for ComfyUI, by Kijai.

Updated EU status checked Last shown

MiniMax H3 W4A8 experimental models at a glance

What is MiniMax H3 W4A8 experimental models?
MiniMax H3 W4A8 experimental models is a model from Kijai. Community-quantized W4A8 and int8 VAE checkpoints of MiniMax H3 video model for ComfyUI, by Kijai.
Who makes MiniMax H3 W4A8 experimental models?
MiniMax H3 W4A8 experimental models is made by Kijai.
Does MiniMax H3 W4A8 experimental models work in the EU?
Available in the EU. Weights are freely downloadable from Hugging Face for local use; no EU restriction found, though the license is not stated on the page. Last verified 14 Nov 2026.
How much does MiniMax H3 W4A8 experimental models cost?
Open source. Free to download from Hugging Face; run locally in ComfyUI.
Where was MiniMax H3 W4A8 experimental models shown?
In 1 creator video by AI Search. Most recently by AI Search on 12 Aug 2026, at 11:39 in “The BEST local AI video generator just got BETTER!”.

Sources: the vendor's own pages (linked above) and creator videos at the linked timestamps. EU status is information, not legal advice; see how we check.

About

MiniMax-H3-experimental is a Hugging Face repository by Kijai containing experimental compressed checkpoints of the MiniMax H3 video generation model, packaged for ComfyUI. The main files use a W4A8 format (4-bit weights, int8-convrot activations) and require ComfyUI 0.31.0. The repository also lists a work-in-progress W6A8 variant (6-bit weights), with a related comfy-kitchen pull request referenced.

Additional files include int8-convrot quantized video VAEs, which the author says speed up VAE decoding (about 2x for the main VAE with ComfyUI 0.36.0, about 1.3x for a pruned "light" VAE). The repo also holds converted LoRAs: PDMD 2NFE/4NFE and DMAD distillation LoRAs, a rank-reduced extraction of the Singularity v2 finetune (the author notes it captures perhaps 40-50% of the full finetune), an experimental reference LoRA, and a 2K refiner component only.

According to a YouTube review, the W4A8 models are about 12 GB with a roughly 3 GB int8 VAE, and with Spectrum and sage attention can run on about 8 GB of VRAM. The files are labelled experimental by the author; license and model card details were not provided on the page.

Key features
  • W4A8 quantization (4-bit weights, int8-convrot activations), about 12 GB
  • Reported to run on about 8 GB VRAM with Spectrum and sage attention
  • int8-convrot VAEs for faster decoding (~1.3x to ~2x)
  • Converted PDMD, DMAD and Singularity LoRAs plus a 2K refiner
  • Experimental W6A8 variant in progress
  • Requires ComfyUI 0.31.0 (0.36.0 for the full VAE speedup)
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