Fixed model workspace
Wan 2.7 is locked on this page, so generation settings stay tied to the current model.
AI Video Generator
Wan 2.7 AI Video Generator
Wan 2.7 by Alibaba is available on Videmos as a text to video model. Its supported inputs and output controls are shown directly in the generator.
Direct answer
Wan 2.7 is a video model from Alibaba available through Videmos. This page shows the configured inputs, output controls, credit cost of 14 per use, examples or workflow notes when available, and links to the provider information used to describe the model. Check the generator before submitting because availability follows the current Videmos configuration.
Last updated: July 12, 2026
Text to Video
text prompt / 1 reference image14 creditsAlibaba
Create with Wan 2.7 using the inputs and output settings shown above.
Wan 2.7
What is Wan 2.7?
Wan 2.7 by Alibaba is available on Videmos as a text to video model. Its supported inputs and output controls are shown directly in the generator.
Use the generator above to review the available inputs, output controls, and credit cost for this model.
ProviderAlibaba
Inputtext prompt / 1 reference image
Credits14 credits/use
Aspect ratio1:1 / 16:9 / 9:16 / 4:3 / 3:4
Wan 2.7 key features
Current input support
text prompt / 1 reference image
Visible controls
Aspect ratio / Duration / Quality setting / Seed / Negative prompt
Credit cost
Each submitted task uses 14 credits.
Negative prompt
Use the negative prompt field to describe content that should be excluded from the result.
Seed testing
Seed is shown only when the current generator exposes it for this model.
Wan 2.7 use cases
Prompt-first clips
Use text-to-video when the current model exposes that input mode.
Reference animation
Use image, video, or start/end frame inputs only when listed for this model.
Format testing
Use the available aspect ratio, duration, and output settings shown on the page.
Wan 2.7 examples
Prompt setup
Describe the subject, action, camera motion, scene, and duration direction for Wan 2.7.
text prompt / 1 reference image
Parameter setup
Aspect ratio / Duration / Quality setting / Seed / Negative prompt
Uses current Videmos configuration
Wan 2.7 technical capabilities
Provider
Alibaba
Input
text prompt / 1 reference image
Credits
14 credits/use
Aspect ratio
1:1 / 16:9 / 9:16 / 4:3 / 3:4
Duration
2s / 3s / 4s / 5s / 6s / 7s / 8s / 9s / 10s / 11s / 12s / 13s / 14s / 15s
Quality setting
720P / 1080P
Seed
Optional numeric value
Negative prompt
Supported
Wan 2.7 model comparison
Input
text prompt / 1 reference image
Kling API: text prompt · Kling O1: text prompt / up to 2 reference images · Kling 3.0: text prompt
Controls
Aspect ratio / Duration / Quality setting / Seed / Negative prompt
Kling API: Aspect ratio / Duration / Quality setting / Negative prompt · Kling O1: Aspect ratio / Duration / Quality setting · Kling 3.0: Aspect ratio / Duration / Quality setting / Negative prompt
Credits
14
Kling API (12) / Kling O1 (10) / Kling 3.0 (15)
Videmos suggestion
Choose Wan 2.7 when its listed inputs and controls match the task.
Use peer models when they expose a different input path, output control, or credit cost.
How to use Wan 2.7
Choose input mode
text prompt / 1 reference image
Write the prompt
Describe only the subject, scene, motion, style direction, and constraints you actually need.
Set supported controls
Aspect ratio / Duration / Quality setting / Seed / Negative prompt
Generate and review
Submitted tasks appear in Assets when the generation pipeline accepts the request.
Wan 2.7 FAQ
What is Wan 2.7?
Wan 2.7 by Alibaba is available on Videmos as a text to video model. Its supported inputs and output controls are shown directly in the generator.
Which inputs does Wan 2.7 support on Videmos?
text prompt / 1 reference image
Which controls are shown?
Aspect ratio / Duration / Quality setting / Seed / Negative prompt
How many credits does it use?
Wan 2.7 uses 14 credits per submitted task in the current catalog.
Is this an objective model ranking?
No. The comparison sections are Videmos configuration guidance based on visible inputs, controls, and credit cost.