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video model comparison

Gemini Omni Flash 1.1 vs Wan 3.0 Video

Gemini Omni Flash 1.1 and Wan 3.0 Video are both current video models, from Google and Alibaba Qwen. Both cost $0.10 per video second.

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.

FactGemini Omni Flash 1.1Wan 3.0 Video
Price per video second$0.10$0.10
Artificial Analysis Video Arena (text to video)1114 Elo (#2 of 4)Not measured
Artificial Analysis Video Arena (image to video)1130 Elo (#1 of 3)Not measured
ProviderGoogleAlibaba Qwen
Release dateAugust 27, 2026August 6, 2026
AccessAPI onlyAPI only
Context window1,048,576 tokensNot reported
Max outputNot reportedNot reported
Inputtext, image, videotext, image, video, audio
Outputvideo, audiovideo

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

When to choose each

Gemini Omni Flash 1.1

Best for

  • Short clips with sound that need conversational edits

Watch out for

  • Each clip is 3 to 10 seconds; extensions add 10 seconds at a time up to 40 seconds
  • Editing uploaded videos is not available in every region, and voice editing is not supported
Full Gemini Omni Flash 1.1 profile

Wan 3.0 Video

Best for

  • Long single-shot clips
  • Reference-driven video mixing images, video and audio

Watch out for

  • Alibaba labels it a preview
  • Billing counts input video seconds as well as output, so reference clips add cost
  • The independent leaderboards list a Wan 3.0 with a later date than this API model, so no score is matched to it
Full Wan 3.0 Video profile

Gemini Omni Flash 1.1 vs Wan 3.0 Video FAQ

Which is cheaper, Gemini Omni Flash 1.1 or Wan 3.0 Video?

Both cost $0.10 per video second.

Production evaluation

Choosing between Gemini Omni Flash 1.1 and Wan 3.0 Video?

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