How we compare
The method behind every comparison here: what is tested, what is sourced, what is deliberately not claimed, and how to tell us we are wrong.
A comparison is only worth reading if you know how it was made. This is the method.
What we do
- Describe what each product is built for, which is usually the deciding factor and is rarely disputed.
- State the trade-off plainly — control versus speed, depth versus breadth — rather than declaring a winner that only applies to one use case.
- Give a decision rule you can apply to your own situation, since we do not know your shots.
- Date every page, because this category changes monthly.
What we deliberately do not do
- Publish prices. They change often enough that a third-party figure goes stale and misleads. We describe the cost structure and point at the vendor's page.
- Publish benchmark scores. Output quality on shared models is a property of the model, not the platform — and a single test run measures variance.
- Rank a category as a static list. Anything ranked "best" is out of date within weeks. We give you the axes and a test instead.
- Claim a winner overall. Every comparison here resolves to "pick this if… / pick that if…", because that is the honest shape of the answer.
The thing most comparisons get wrong
Most tools in this category do not train their own models. They license the same frontier engines and compete on interface, price and workflow. So when two products both offer Sora or Kling, video quality is not the differentiator — anyone claiming a quality gap between them is reporting variance. What genuinely differs is cost per usable result, which models each carries, and whether the surrounding tools fit your work.
Corrections
If something here is wrong or has gone out of date, it should be fixed rather than defended. Pages carry a verification date so you can see how current the claim is; a page that has not been checked recently should be treated as a starting point rather than a fact. The changelog records what has been revised and when.
Common questions
Do you test every tool?
We describe what each is built for and how the category behaves. We do not publish benchmark scores, because on shared models a single run measures variance rather than quality.
Why no prices?
They change frequently and a stale third-party price misleads. The cost structure is stable and is what we describe.