MiniMax3
Generate MiniMax H3 videos with prompts and workflows
What it does
MiniMax3 is an independent AI video creation platform built around MiniMax H3 workflows. It combines browser-based video generation with practical prompt guides, image-to-video and reference-to-video workflows, ComfyUI resources, camera-control examples, and developer-oriented H3 documentation. Creators can move from learning how H3 works to testing prompts and generating videos in one place. MiniMax3 is an independent product and is not affiliated with or operated by MiniMax.
Try MiniMax3 free with daily credits. Looking for MiniMax 3 video generation? Create with MiniMax H3 using text, image, video, audio, and up to 2K output.
Create 768p or 2K MiniMax H3 videos with native audio. MiniMax3.org is an independent AI video platform for MiniMax H3. If you're searching for “MiniMax 3” video generation, use MiniMax3 to create H3 videos from text, images, video, and audio references with 768p or 2K output and native audio. Sign in and check in daily to claim 10 free credits , with a 30-credit cap. First 5 images are included; each additional image uses 3 credits. MiniMax H3 sample output Sample videos Hover to preview on desktop; tap to load and play on mobile. 8 s 16:9 Hover to preview, click to expand 10 s 16:9 Hover to preview, click to expand 15 s 9:16 Hover to preview, click to expand 10 s 16:9 Hover to preview,…from minimax3.org
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I trained a 125M-parameter transformer to autocomplete piano performances in real time (~108 notes/sec on an iPhone 15). The idea is basically GitHub Copilot or Tabnine, except instead of prompting it with code, you prompt it by playing a few notes on a MIDI piano. The model then continues what you played, entirely on-device. The app is free if anyone wants to try it. Happy to answer questions about the model, training, Core ML, or the many things that didn't work.
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Life & fun · Aug 2026 · toneyalexander.github.io


I trained a 125M-parameter transformer to autocomplete piano performances in real time (~108 notes/sec on an iPhone 15). The idea is basically GitHub Copilot or Tabnine, except instead of prompting it with code, you prompt it by playing a few notes on a MIDI piano. The model then continues what you played, entirely on-device. The app is free if anyone wants to try it. Happy to answer questions about the model, training, Core ML, or the many things that didn't work.
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