Which AI video model to pick, by the job you are doing
Most comparisons of AI video models rank them. That is the wrong shape of answer, because the models do not fail in the same places. A model that produces a beautiful, still, dreamlike shot is useless for a product demo, and the one that nails hand movement may not do sound at all.
Here is a job-first way to choose.
The four things that actually differ
Motion stability. Does an object stay the same object for the whole clip? This is where most models break: a hand grows a finger, a logo mutates, a car changes shape mid-turn. If your shot has a recognisable object in it, this is the property that decides everything.
Sound. Some models generate an audio track together with the picture, including speech. Others give you silence and you add audio afterwards. That is a workflow decision, not a quality one.
Image-to-video. Whether you can hand it a specific first frame. If you already have a product photo or a rendered still, this usually beats describing the same scene in words.
Duration and resolution. Clip length limits vary, and only some models render at 4K. Longer is not automatically better: many models get less stable as the clip runs.
Matching model to job
A product in motion, where the object must stay itself. Prioritise motion stability. Kling holds objects together more reliably than most, and it is the safer choice when the shot has to survive a client's eye.
A talking scene, or anything where sound matters. Veo 3 generates an audio track along with the video, which removes a whole editing step. If you need speech in the clip, start here.
Animating a specific frame you already have. Use image-to-video and supply the frame. This is the highest-hit-rate workflow in AI video, and it is underused: you control composition, brand colours and the product exactly, and the model only has to supply movement.
A defined beginning and end. Some models take both a first and a last frame. If you need the shot to land on a specific composition, this is how you get it without twenty attempts.
A full sequence rather than one clip. Single clips are the wrong unit for a story. A shot list, generated scene by scene and assembled, gets you a finished piece.
The mistakes that waste the most attempts
- Describing the camera and forgetting the subject. Models respond much better to what is in frame than to how it is shot.
- Asking for too much in one clip. One action per generation. Two actions is where things fall apart.
- Starting from text when you have an image. If a still exists, use it as the first frame.
- Long clips by default. Generate short, confirm the motion is right, then extend.
- Judging a model on one prompt. The variance between two runs of the same prompt is often larger than the variance between two models.
How to actually compare
Take one real shot you need, not a demo prompt. Run it on three models with identical inputs. Look at the object in frame twelve, not at frame one, because that is where instability shows. Then repeat once, because a single run tells you very little.
In OrangeAI the models sit in one interface and the cost of each generation is shown before you press the button, so this comparison costs an amount you can see in advance rather than three separate trial subscriptions.
Frequently asked questions
Which model is the best overall
There is no honest answer to that. Motion stability, sound and image-to-video are different properties, and the best model depends on which one your shot needs.
Can I set the first and last frame
On models that support it, yes, there are separate inputs for both.
What resolution can I get
Up to 4K on models that support it. The available options appear when you select the model.
How long can a clip be
It depends on the model, and the allowed range is shown in the interface. Values outside it are clamped rather than silently accepted.
Is the price visible before generating
Yes, the cost of the specific generation is shown before you run it.