Compressed W4A8 models of about 12 GB, plus a smaller 3 GB int8 video VAE. With Spectrum and sage attention they could run on about 8 GB VRAM; demoed with an orbit shot of a car.
MiniMax H3 W4A8 experimental models
by Kijai
Community-quantized W4A8 and int8 VAE checkpoints of MiniMax H3 video model for ComfyUI, by Kijai.
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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.
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.
- 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)
As seen on YouTube
Watch the moment: the exact second top creators show it. Videos load only when you press play, via youtube-nocookie.com.
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