Choosing an AI video generator is less about a flashy demo and more about whether the workflow survives a real project. Before committing to a tool, I use a small checklist that covers continuity, inputs, audio, cost, exports, and operational risk.
1. Test continuity, not just a single frame
A beautiful opening frame tells you very little. Try prompts that require a subject to move through a scene, a camera to maintain direction, or an object to remain consistent after a cut-free transition. Look for identity drift, sudden changes in lighting, broken geometry, and motion that feels physically impossible.
A useful test set includes:
- a product orbit with a fixed camera distance
- a person walking while the background remains stable
- a reference-image prompt with a specific color palette
- a scene with small text or a recognizable logo
Save the exact prompts and settings. Reproducibility matters more than one lucky result.
2. Separate text-to-video from reference workflows
Many products describe themselves as “text-to-video,” but the practical workflow may also include image-to-video, video references, or multiple reference inputs. These modes solve different problems.
Text-to-video is useful for exploration. Reference-driven generation is usually better when composition, subject appearance, or product placement matters. Evaluate each mode separately instead of treating them as interchangeable.
3. Check audio and export details early
Audio can be a major differentiator, but it is also easy to overlook during a visual demo. Verify whether sound is generated, synchronized, downloadable, and editable. Then check the actual output format, resolution, frame rate, watermark policy, and maximum duration.
If you are evaluating a Seedance 2.5 workflow, the Seedance 2.5 AI site is a useful reference point for checking the current product positioning and available workflow details. Treat model availability and API claims as something to verify directly before production use.
4. Measure cost per usable iteration
A credit price is not the same as the cost of a finished clip. Track how many attempts are normally required before you get a usable result. A simple spreadsheet can compare:
- credits per generation
- average retries per accepted clip
- resolution or duration multipliers
- image and video reference costs
- monthly minimums or expiration rules
The cheapest first generation may not be the cheapest production workflow.
5. Define a small acceptance test
Before adopting a tool, run five to ten prompts from your real workload. Score each output for subject consistency, motion quality, prompt adherence, audio, export usability, and turnaround time. Keep the raw outputs so you can compare tools fairly.
The best AI video generator is rarely the one with the most impressive homepage demo. It is the one that produces predictable results for your specific inputs, at a cost and speed your team can sustain.
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