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MiniMax H3 user seeks VAE optimization for faster video generation

A user on Reddit's r/StableDiffusion subreddit is seeking to optimize the generation speed of MiniMax H3, a video generation model. Profiling indicates that the variational auto-encoder (VAE) decoding process accounts for approximately 43% of the total generation time, translating to about 5.5 minutes per 15-second clip on a high-end RTX 4090 GPU. The user has attempted several optimizations, including using an fp8mix VAE and different temporal chunking strategies, but has seen minimal improvement. They are inquiring about faster VAEs compatible with their WanGP setup, potential benefits of newer CUDA and PyTorch builds, and whether hardware limitations like VRAM might be the primary bottleneck. AI

IMPACT Users may find optimization tips for VAE decoding in video generation models like MiniMax H3, potentially improving rendering times on consumer hardware.

RANK_REASON User-level optimization query for a specific AI model and software setup.

Read on r/StableDiffusion →

AI-generated summary · Google Gemini · from 1 sources. How we write summaries →

MiniMax H3 user seeks VAE optimization for faster video generation

COVERAGE [1]

  1. r/StableDiffusion TIER_2 English(EN) · /u/Prestigious_Cat85 ·

    MiniMax H3: VAE decode is 43% of my generation time (~5.5 min per 15s clip on a 4090) — anything I can do in WanGP?

    <table> <tr><td> <a href="https://www.reddit.com/r/StableDiffusion/comments/1vtgggq/minimax_h3_vae_decode_is_43_of_my_generation_time/"> <img alt="MiniMax H3: VAE decode is 43% of my generation time (~5.5 min per 15s clip on a 4090) — anything I can do in WanGP?" src="https://pre…