Start with the shot you need, then choose the model.
There are now dozens of AI video models, and each one is good at something different. Picking by reputation or by whichever clip went viral last week usually ends with a wasted budget and a folder of unusable takes. A better approach is to decide what the project needs first, then check each model against a short list of criteria.
This checklist is written for creators, small studios and marketers who generate video for real projects: ads, music visuals, explainers, short films, social posts. It does not assume any particular tool.
1. Start with the shot, not the model
Write down what a single finished shot has to do. How long does it run? Is it a locked-off product shot, a character walking through a room, a slow camera move across a landscape? Models that excel at sweeping camera motion are not always the ones that keep a face stable for ten seconds. If you cannot describe the shot in two sentences, no model will rescue it.
2. Clip length
Most models generate short segments, often somewhere between 2 and 15 seconds. Check the maximum per request, not the marketing headline. If your edit needs 20 seconds of continuous action, you will either stitch several clips or use a tool that continues a clip from its last frame. Plan the cut points before you generate, because every join is a place where color, lighting or motion can drift.
3. Resolution and frame rate
Higher resolution costs more per second, so ask what the final destination is. A vertical social clip rarely needs 1080p source material; a client presentation on a big screen might. Frame rate matters too: if your timeline runs at 24 fps and the model outputs another rate, expect to convert, and check that motion still looks natural afterwards. A practical habit is to draft at the lowest resolution and re-run only the winners at the final size.
4. Motion quality
Motion is where models differ most. Look for these specific failures when you review a draft:
Limbs that bend the wrong way or hands that change shape between frames.
Backgrounds that "swim" when the camera moves.
Slow-motion look when you asked for normal speed.
Physics that feels floaty: cloth, hair, liquids.
Test with the type of motion your project actually needs, not a generic demo prompt.
5. Identity and style consistency
If the same character, product or logo appears in several shots, consistency is the criterion that decides everything. Some models drift noticeably between clips even with the same prompt. Image-to-video workflows help, because the starting frame pins down the look. Reference inputs go further: several models accept reference images or a reference video so the subject carries across shots. Check whether the model supports the kind of reference you have.
6. Reference and frame controls
Look at what inputs a model accepts beyond text:
First frame: the clip starts from your image.
First and last frame: you define both ends and the model fills the motion in between, which is useful for transitions and loops.
Reference images: several pictures of a subject to keep it consistent.
Reference video: motion or style carried over from an existing clip.
More control means fewer wasted generations, which is often worth a higher per-second price.
7. Native audio
Some models generate sound with the picture: ambient noise, effects, sometimes speech. Others output silent video. If you plan to add your own music and voice-over anyway, native audio is a bonus, not a requirement. If you need lip movement that matches dialogue, check this early, since it narrows the field a lot.
8. Content policy of the model
Different models apply different rules. Some builders apply their own moderation, and a prompt that passes on one model can be declined on another. Look for a platform that labels each model clearly, so you find out before paying rather than after. Also read the license or usage terms that apply to commercial work, and make sure you have the right to use any people, products or music you feed in as references.
9. Price per second and how to budget
Video is usually priced per output second, and the price climbs with resolution. Platforms that show the exact price before a run starts make budgeting much easier than those that bill afterwards.
Here is a worked example using public prices at the time of writing (October 2026), on a catalog called SpicyAPI. Suppose you need one 10-second shot.
Wan 3.0 (Alibaba) image-to-video is listed from $0.045 per second at 480p up to $0.18 per second at 1080p. At 720p it is $0.09 per second, so a 10-second shot costs $0.90.
Seedance 2.5 (ByteDance) is listed at $0.1234 per second at 480p, $0.2773 at 720p and $0.6823 at 1080p, so the same 10-second shot costs $2.77 at 720p and $6.82 at 1080p.
Now add retries. If you expect to throw away three takes for every keeper, multiply the per-shot figure by four. Ten finished shots of 10 seconds at Wan 3.0 720p would be about 10 x 4 x $0.90 = $36. The same plan on Seedance 2.5 at 720p would be about $111, and at 1080p roughly $273. Those are very different budgets for the same storyboard, and the higher-priced model may well be the right one for a hero shot. The point is to make that choice on purpose.
10. Test cheap, finish expensive
A reliable workflow looks like this:
Generate quick drafts at the lowest resolution and shortest duration that still show the motion.
Compare two or three models on the same prompt and the same start image.
Pick the model that handles your hardest shot, not your easiest one.
Re-run only the approved drafts at final resolution.
Keep notes on prompts and seeds so you can reproduce a result.
This costs a few dollars and saves a lot more than it spends.
A one-page checklist
Before you commit to a model, confirm:
Maximum clip length per request fits your cut plan.
Resolution and frame rate match the delivery format.
Motion holds up on your own test shot.
Subject stays consistent across at least three takes.
It accepts the reference inputs you need.
Audio: native, or you will add your own.
The content policy label and the license fit the project.
You know the price per second before you press run, and you have budgeted for retries.
Conclusion
No single AI video model wins every project. The useful question is which model fits this shot, at this resolution, at a price you can predict. Run a small side-by-side test, keep the receipts, and let the results decide. A half-hour of drafts at the start is a sensible insurance against a bad render at the end.