Wan2.2 14B Fast

What you get here is a live inference playground for one of the more capable open-weight video generation models available right now. The 14B parameter Wan2.2 model has been pushed through two meaningful optimizations simultaneously: FP8 quantization, which cuts memory pressure by representing weights at lower precision, and AOTInductor compilation, which pre-compiles the compute graph so you skip the overhead on every run. The result is noticeably faster generation than a vanilla deployment of the same model would give you. For a founder or technical builder, the practical value is straightforward. Before you commit engineering time to self-hosting a video generation pipeline, you want a realistic read on latency and output quality together. This demo gives you that without spinning up your own GPU cluster first. The honest reservation is that ZeroGPU environments queue and throttle under load, so the speed you see here may be optimistic compared to a shared production endpoint under real traffic. -> Best for: product builders evaluating open-source video generation before committing to a hosting and inference budget.