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video model comparison

Dreamina Seedance 2.5 vs Veo 3.1 Preview

Dreamina Seedance 2.5 and Veo 3.1 Preview are both current video models, from ByteDance Seed and Google. Dreamina Seedance 2.5 is 42% cheaper per video second than Veo 3.1 Preview, $0.231 vs $0.40.

Data verified October 13, 2026 · Dataset 2026-10-13

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Side by side

Standard-tier prices in effect today. The better value in each row is highlighted.

FactDreamina Seedance 2.5Veo 3.1 Preview
Price per video second$0.231 (better)$0.40
Artificial Analysis Video Arena (text to video)1143 Elo (#1 of 4)Not measured
Artificial Analysis Video Arena (image to video)1125 Elo (#2 of 3)Not measured
Arena Text-to-VideoNot measured1364 Elo (#1 of 3)
Arena Image-to-VideoNot measured1398 Elo (#2 of 2)
ProviderByteDance SeedGoogle
Release dateNot reportedOctober 15, 2025
AccessAPI onlyAPI only
Context windowNot reportedNot reported
Max outputNot reportedNot reported
Inputtext, image, videotext, image
Outputvideovideo, audio

Scores:Artificial Analysis · 2026-10-13Artificial Analysis · 2026-10-13Arena · 2026-10-12

When to choose each

Dreamina Seedance 2.5

Best for

  • Multi-shot clips up to 30 seconds
  • Timestamp-precise video editing

Watch out for

  • Billed by tokens, not seconds: the recorded per-second rates are BytePlus estimates for a 5-second 16:9 clip without video input
  • Requests with video input count the input duration and carry a minimum charge
  • BytePlus dates the release only to June 2026
Full Dreamina Seedance 2.5 profile

Veo 3.1 Preview

Best for

  • Gemini API video generation with audio

Watch out for

  • Preview models may change and have stricter rate limits
Full Veo 3.1 Preview profile

Dreamina Seedance 2.5 vs Veo 3.1 Preview FAQ

Which is cheaper, Dreamina Seedance 2.5 or Veo 3.1 Preview?

Dreamina Seedance 2.5 is 42% cheaper per video second than Veo 3.1 Preview, $0.231 vs $0.40.

Production evaluation

Choosing between Dreamina Seedance 2.5 and Veo 3.1 Preview?

Public benchmarks narrow the shortlist. We run both on your own tasks, data and cost limits, then build the routing and review controls to run the winner in production.

  • A head-to-head evaluation on your real workload
  • Routing between models by cost and difficulty