Team compresses 31B video-audio diffusion model to 14B with 6-step INT8 inference

A developer team has shared a project on Hacker News describing the compression of a 31-billion-parameter video and audio diffusion model down to roughly 14 billion parameters. The optimized version reportedly runs in six inference steps and uses INT8 quantization to reduce computational requirements. The work is presented as a Show HN project, with the source code hosted in a public GitHub repository. The post gained three points and no comments at the time it was indexed, so community reception remains limited. The article itself provides few further technical details beyond the project link.