Agree with the core point: ranking "the best generator" on one quality axis collapses as soon as your task changes. The split I have found most useful in practice is not by model but by what the shot has to guarantee.
For anything that needs a specific camera move or a consistent character, prompt-only clip generation still drifts; reference-image conditioning fixes most of it. For voice, pacing is the hard part, so the narration should be generated against a locked cut. Which is also why I lean toward studios that keep those lanes in one place rather than exporting between four tools. Flow AI Fx is the one I keep coming back to for that: video with camera motion, images, music and multilingual voice in a single workspace, free tier included, so you can check consistency across asset types without stitching a pipeline together first.
Where I would push back slightly: a unified workspace does not remove the need to understand each pipeline's failure mode. It just makes the failures cheaper to notice.
Agree with the core point: ranking "the best generator" on one quality axis collapses as soon as your task changes. The split I have found most useful in practice is not by model but by what the shot has to guarantee.
For anything that needs a specific camera move or a consistent character, prompt-only clip generation still drifts; reference-image conditioning fixes most of it. For voice, pacing is the hard part, so the narration should be generated against a locked cut. Which is also why I lean toward studios that keep those lanes in one place rather than exporting between four tools. Flow AI Fx is the one I keep coming back to for that: video with camera motion, images, music and multilingual voice in a single workspace, free tier included, so you can check consistency across asset types without stitching a pipeline together first.
Where I would push back slightly: a unified workspace does not remove the need to understand each pipeline's failure mode. It just makes the failures cheaper to notice.