QuantFunc/Minimax-H3-Quantfunc-4bit

text-to-video model by QuantFunc

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🌐 Website  |  🐙 GitHub  |  🤗 Hugging Face  |  🤖 ModelScope  |  🎮 Discord 4x compression, quality held. QuantFunc INT4 cuts MiniMax H3's core weight precision from 16-bit to 4-bit. Character detail, style fidelity and fast motion stay clear and coherent, while H3's native video+audio generation is fully preserved. In our internal FL2VA evaluation, QuantFunc INT4 vs the BF16 baseline (same prompt, same seed) measures 23.7 dB PSNR. All clips below were generated by MiniMax-H3-QuantFunc-4bit — click a player to watch. On an RTX 4090, 768 × 768, 5s, 124 frames: Prompts, reference images/videos, audio assets and the rest of your workflow nodes stay unchanged. Both weight sets already have the acceleration LoRA, Token Refiner, INT4 Refiner and INT8 Conv Sidecar fused in — no extra components to attach. Runs on every NVIDIA SM75+ GPU: RTX 20/30/40/50-series, A100, H100, H200, B100, B200, GB300. 4-bit weights significantly cut the weight-bandwidth…

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Model overview

QuantFunc/Minimax-H3-Quantfunc-4bit is a text-to-video model repository published by QuantFunc on Hugging Face. The source reports the diffusers library.

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Model facts

Task: text-to-video
Library: diffusers
Recent downloads (30 days): 15,137
Cumulative likes: 15
Hugging Face trending score: 15
Reported safetensors parameters: Not reported
Architecture: MiniMaxH3Pipeline
License: other
Access: Not gated by Hugging Face
Created: 2026-09-28T13:55:48.000Z
Last modified: 2026-09-28T16:15:33.000Z

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