Private generative video
Compare local video models by duration, resolution, frame rate, conditioning and memory. Video workloads multiply latent and attention costs across time, so published minimums rarely describe a useful production queue.
Selection approach
Define the resolution, duration, frame count, conditioning and acceptable render time before choosing hardware. Larger memory usually buys more useful settings, less offload and better queue concurrency.
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2 current models
Showing 2 models
Wan AI
A 5B text-and-image-to-video model that supports 720p generation and an official single-GPU offload route.
Tencent
An 8.3B text-to-video and image-to-video model with 480p and 720p checkpoints, optional super-resolution and distilled workflows.
No model matches that search and workload combination.
Model-to-hardware fit
Use the precise model version, numerical format and complete software pipeline intended for production.
Check whether it can load on one GPU or requires supported multi-GPU loading.
Allow for context, cache, batch, media encoders and concurrent users.
Measure quality, latency and stability on representative work.
Model weights are only one part of the system. Data access, runtime software, storage, monitoring and administrator handover also affect a reliable deployment.
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