Using Multiple AI Video Models in One Place | Our Protoface Production Experience

As AI video tools multiplied, our question changed. Instead of asking which model was best in the abstract, we needed to ask which option was appropriate for a particular shot. A visual test, a transition and a hero shot do not carry the same creative or production risk.

We did not need to commit the same level of resources to every generation. Separating exploratory shots from important final shots gave us a clearer way to review an idea before investing more effort in it.

Protoface presented model options in one interface, including Seedance 2.5, MiniMax H3, LTX 2.5, Veo 3.1, Kling 3.0, Runway and the Wan family. These are examples of models available for selection in the platform, not a list of models FourFeetz used for every shot.

Our documented production work used or tested selected options, including MiniMax H3, according to the needs of a scene. This was not a controlled benchmark of all seven models, and this article does not rank their quality. The practical value was being able to make model access and shot selection part of one production decision.

Our working sequence became simple: begin with the idea, use a faster or lower-cost generation option for an exploratory test, review the shot, keep a result that already works, choose the model needed for an important scene, and finish the sequence in the edit.

Short samples made with options including MiniMax H3 helped us judge whether the scene direction was worth continuing. The point was not that one model should replace every other model. It was that a shot should earn the next production decision.

In our production work, separating exploratory tests from important final shots was more practical than assigning one premium model to every scene. We reviewed the purpose, usable duration, subject consistency, likely retries and editability before choosing the next generation option.

A technically impressive clip could still be the wrong choice if it did not connect to the edit. Repeated failures could also consume more time and credits than choosing an appropriate model after a clear test.

For FourFeetz, reducing AI video production cost is not a race toward the cheapest model. It is the discipline of matching the production choice to the scene, testing before committing and refusing to regenerate footage that is already good enough for its editorial role.

Our earlier Protoface production experience and Seedance test explain narrower projects in more detail. Together, they support the same conclusion: production evidence and editorial purpose are more useful than a universal model ranking.