Compressing a Movie to 1MB and Reconstructing It With Wan 2.2
Willsolo · reddit · 2026-07-19
The author compressed a movie into less than 1MB of text and then reconstructed it into a video with sound using Wan 2.2.
Process
- Sliced the video into about 2,000 shots using PySceneDetect
- Used Gemini Flash-Lite to generate a structured description of around 100 words based on 8 frames extracted from each shot
- The text was then compressed to roughly 320KB using xz
- Shots were sequentially fed into a self-hosted Wan 2.2 TI2V-5B on a RunPod A6000 to generate visuals
- Audio was generated using MMAudio (sound effects) + MusicGen (soundtrack), with dialogue restored at original timestamps using ElevenLabs TTS
Main Challenges
- Character consistency was the hardest part: since each shot was generated independently, the author clustered character descriptions and injected them into the prompts
- For shots exceeding 5 seconds, a "previous frame to next frame" chained generation was used
Cost & Resources
- Estimated cost is about $30 per movie
- Provided more detailed examples, cost comparisons, write-up links, and a GitHub repository
The author is also asking for feedback.
More from coding & agent
- Gergely Orosz: Shipping 10x PRs With AI Agents, Sites Fill With Small Regressions — ducha_aiki · 2026-09-11
- Kernel integrates Stripe Link so browser agents can pay with one API call — jeff_weinstein · 2026-09-11
- Same Echo Maze prompt, three frontier models: all passed visually but shipped the same hidden bug — eyishazyer · 2026-09-11
- The full prompt-to-3D-game workflow: Hyper3D Rodin MCP plus Codex, no reference image — FellMentKE · 2026-09-11
- Building a 3D landing page with GPT-6 Astra and Hyper3D Rodin MCP, no modeling needed — FellMentKE · 2026-09-11
- Astra storyboards plus Minimax H3 per-shot generation boost video success rates — Hailuo_AI · 2026-09-11