Overview
h3-hrx is a Rust-based tool for MiniMax H3 video and audio generation on AMD Strix Halo hardware, using Loom kernels and HRX. It generates video with sound from text, keyframes, or image/audio/video references. Inference requires no Python or PyTorch; HRX provisions the compiler and runtime, and the binary embeds its kernel sources and tokenizer. The tool has been tested on Linux with AMD Strix Halo (gfx1151) and 128 GB unified memory, while other GPUs are unvalidated. The base checkpoints occupy about 54 GB on disk and are fetched from Comfy-Org/MiniMax-H3 into the Hugging Face cache. Generation modes include text, first/last keyframes, image/audio/video references, and reusable encoded references via RefMods. Latent upscaling is supported, where a smaller clip is generated and then upscaled with a learned 3D model. The package is h3-hrx and the Rust library is h3_hrx, with session handles for encoding, denoising, and decoding. Code is licensed under Apache-2.0, with model weights licensed separately by MiniMax.
Pricing
Free
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Use Cases
- Teams use h3-hrx to generate video with sound from text prompts.
- Teams use h3-hrx to generate video from first and last keyframes.
- Teams use h3-hrx to generate video from image, audio, or video references.
- Teams use h3-hrx to generate video with reusable encoded references via RefMods.
- Teams use h3-hrx to upscale latents of a smaller clip with a learned 3D model.
- Teams use h3-hrx to produce WAV-only output and still frames.
- Teams use h3-hrx to run benchmarks for host, stage, full-render, lifecycle, and memory workloads.
Features
Generate MiniMax H3 video with audio
Create video from text prompts
Control first and last keyframes
Use image, audio, and video references
Reuse subjects and voices with RefMods
Apply LoRAs and learned latent upscaling
Save and branch H3 World sessions
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