RunningHub workflow page: https://www.runninghub.ai/zh-cn/post/2086444236236484609?inviteCode=rh-v1111
MiniMax H3 Larry + Attention + Cache Full Acceleration — MiniMax H3 Larry + Attention + Cache Full Acceleration
A MiniMax H3 video graph from episode 291, part of the six-times-acceleration series that compares model tier, LoRA, attention and cache settings.
Saved configuration
71 nodes / 86 links. Three parallel branches: UNET minimax_h3_fl2va_int8_convrot, CLIP qwen3vl_32b_minimax_h3_int8_convrot, turbo-v4 LoRA at 1, euler + beta 6 steps denoise 1; three LoadImage inputs and three outputs.
How to use
The 'full blood' acceleration file: three branches with attention and cache patches layered on the same int8 model and turbo LoRA. Like the SageAttention file, it is a comparison rig; pick one branch's patch stack if you want a single production graph.
Limits and not-verified items
No inference was run for this listing: no speed, VRAM, quality, audio-sync or acceleration-factor claim is made. The "6x" in the episode title is the author's description and was not independently measured. Values are quoted from the saved nodes. H3 weights, LoRAs, encoder and VAEs are not bundled; check their licenses separately. The graph notes credit the official Comfy-Org/MiniMax-H3 model files; preserved as-is, no originality claim. The cover image is a promotional still, not a frame produced by this graph.
Tutorial: YouTube · Bilibili. Workflows supplied through AI-KSK; verify workflow, node, model, LoRA and cover rights separately. No blanket commercial or redistribution license is asserted.
Description
RunningHub workflow page: https://www.runninghub.ai/zh-cn/post/2086444236236484609?inviteCode=rh-v1111
MiniMax H3 Larry + Attention + Cache Full Acceleration — MiniMax H3 Larry + Attention + Cache Full AccelerationA MiniMax H3 video graph from episode 291, part of the six-times-acceleration series that compares model tier, LoRA, attention and cache settings.
Saved configuration71 nodes / 86 links. Three parallel branches: UNET minimax_h3_fl2va_int8_convrot, CLIP qwen3vl_32b_minimax_h3_int8_convrot, turbo-v4 LoRA at 1, euler + beta 6 steps denoise 1; three LoadImage inputs and three outputs.
The 'full blood' acceleration file: three branches with attention and cache patches layered on the same int8 model and turbo LoRA. Like the SageAttention file, it is a comparison rig; pick one branch's patch stack if you want a single production graph.
Limits and not-verified itemsNo inference was run for this listing: no speed, VRAM, quality, audio-sync or acceleration-factor claim is made. The "6x" in the episode title is the author's description and was not independently measured. Values are quoted from the saved nodes. H3 weights, LoRAs, encoder and VAEs are not bundled; check their licenses separately. The graph notes credit the official Comfy-Org/MiniMax-H3 model files; preserved as-is, no originality claim. The cover image is a promotional still, not a frame produced by this graph.
Tutorial: YouTube · Bilibili. Workflows supplied through AI-KSK; verify workflow, node, model, LoRA and cover rights separately. No blanket commercial or redistribution license is asserted.