State of Open Video Generation Models
summary
Open video models already produce near-closed-model quality: the open 1.2.2/12.2 family rivals Sora on visual fidelity and instruction adherence. Popular Apache-2 models require large VRAM (examples quoted around 47–64 GB native, down to ~11 GB with quantization + offloading), while lighter LTX runs near 13 GB. Practical workflows include text-to-video, image-to-video, frame interpolation, pose-conditioned motion and fine-tuning (Cog/FramePack examples); Diffusers provides inference, quantization backends and fine-trainer tooling to reproduce and adapt these results for experimentation and product proofs.
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chapters (12)
- 0:00Introduction
- 2:16Open source vs. closed models
- 3:16Landscape of open models
- 4:01How diffusion models work
- 7:49Architecture of diffusion
- 8:30Advanced model capabilities
- 11:26Optimizing video models
- 12:21Accessible implementation
- 13:34Practical performance tests
- 14:29Use cases and fine-tuning
- 20:17Chronology and progress
- 21:57Limitations and future
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