Benchmarks Don't Predict Ad Performance
Most model comparisons score cinematic quality: lighting, motion realism, prompt adherence on creative scenes.
None of that is what breaks an ad.
Ads break when the product changes shape between shots, when the actor's face shifts halfway through, when the text on packaging turns to garbage, or when one clip costs so much that testing twenty angles is off the table.
Here's the comparison through that lens.
What Actually Matters for Ad Creative
Product fidelity. Your product must look like your product in every frame. Logos legible, proportions stable, colours accurate. This is the single most common failure and the one most benchmarks ignore.
Character consistency. Multi-shot ads need the same person across every clip. Same face, same hair, same outfit. Drift here destroys the illusion faster than poor resolution ever would.
Cost per clip. Creative testing is a volume game. A model that produces slightly better footage at ten times the price usually loses, because the cheaper model gets thirty attempts and the expensive one gets three.
Audio. Native audio generation removes a whole production step. Without it you're adding voiceover separately.
Seedance (ByteDance)
Strengths: strong multi-reference handling — you can supply a character image and a product image and get both rendered coherently in the same shot. Native audio. Generation is fast, and the cheaper tiers are genuinely cheap, which makes high-volume testing practical.
Weaknesses: no reference-image or last-frame interpolation equivalent to some competitors, so certain continuity tricks aren't available.
Where it fits: high-volume ad testing where product and character consistency matter and budget per clip has to stay low. The tiering matters here — the lighter variants cost a fraction of the flagship with quality that holds up for short vertical ads.
This is the model family we generate on at Faysell, specifically because the cost structure makes volume testing viable rather than aspirational.
Veo (Google)
Strengths: excellent motion realism and prompt adherence. Native audio with good lip timing. Reference image support and last-frame interpolation for stitching longer sequences.
Weaknesses: priced per second at a level that makes large test batches expensive. Requires a paid Google Cloud or Gemini API account — there is no meaningful free tier for video, which catches a lot of people mid-build.
Where it fits: hero creative and sequences where motion quality justifies the cost.
Sora (OpenAI)
Strengths: strong at complex scene composition and physically plausible motion. Handles abstract or stylised prompts well.
Weaknesses: less predictable for product-accurate rendering. Harder to lock a specific product's appearance across shots, which is exactly what commerce creative needs.
Where it fits: concept and brand work rather than product demonstration.
Kling (Kuaishou)
Strengths: good image-to-video quality and competitive pricing. Solid motion from a single starting frame.
Weaknesses: character consistency across separate generations is weaker than the leaders, so multi-shot narratives need more retries.
Where it fits: single-clip animations from an existing product photo.
Hailuo (MiniMax)
Strengths: fast, inexpensive, good at short dynamic motion.
Weaknesses: shorter maximum durations and more variance in output quality.
Where it fits: quick motion tests and social-first content where polish matters less than speed.
The Honest Summary
| | Product fidelity | Character consistency | Cost per clip | Native audio | |---|---|---|---|---| | Seedance | Strong | Strong | Low | Yes | | Veo | Strong | Strong | High | Yes | | Sora | Moderate | Moderate | High | Yes | | Kling | Good | Moderate | Low | Partial | | Hailuo | Moderate | Moderate | Very low | Partial |
If you are comparing products rather than models, Arcads vs HeyGen covers the two most common choices for AI actor video.
How to Choose
Ignore the leaderboard and ask three questions about your own situation.
How many creatives do you need per month? Above twenty, cost per clip dominates every other consideration. Below five, pick on quality and stop optimising.
Does the same person need to appear in multiple shots? If yes, character consistency is your filter and it eliminates several options immediately.
Does the product need to be recognisable? Commerce says yes, almost always. That rules out models that render a plausible generic version of your category rather than your actual item.
Most e-commerce brands land in the same place: a model with strong multi-reference handling and a low enough per-clip cost that running thirty variations is a normal week rather than a budget request.