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Wan v2.7 Reference-to-Video

Wan v2.7 Reference-to-Video is the Wan 2.7 reference-to-video model from Alibaba Cloud, generating new scenes from reference images and videos with combined subject and voice referencing at 720p or 1080p. Your use is subject to Alibaba Cloud's Terms & Privacy Policies.

reference-to-video
import { experimental_generateVideo as generateVideo } from 'ai';
const result = await generateVideo({
model: 'alibaba/wan-v2.7-r2v',
prompt: 'A serene mountain lake at sunrise.'
});
Read docs

Playground

Try out Wan v2.7 Reference-to-Video by Alibaba Cloud. Usage is billed to your team at API rates. Free users (those who haven't made a payment) get $5 of credits every 30 days.

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Images
Add up to 5 images
Videos
Add up to 3 videos
Prompt(optional)

Duration8s
2s10s
Resolution
Aspect ratio
Videos to generate
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Your generated video will appear here.

Providers

Route requests across multiple providers. Copy a provider slug to set your preference. Visit the docs for more info. Using a provider means you agree to their terms, listed under Legal.

Provider
Input
Output
Capabilities
ZDR
No Training
Release Date
$0.10/sec+1 more
04/07/2026

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About Wan v2.7 Reference-to-Video

Wan v2.7 Reference-to-Video is the reference-to-video member of Alibaba Cloud's Wan 2.7 release. You supply reference images, reference videos, or both, and Wan v2.7 Reference-to-Video places the referenced subjects into an entirely new scene described by an optional text prompt. Up to three reference videos can be attached to a single generation.

Combined subject and voice referencing is the notable addition in the 2.7 generation. Wan v2.7 Reference-to-Video lets you bind a subject's visual identity and vocal identity together from your reference material, keeping both consistent in the generated output. The reference pipeline also supports multi-subject work, so several referenced identities can interact in one scene, and multi-shot workflows keep those identities stable across scene cuts.

Output runs 2 to 10 seconds, with a default of 5 seconds, at 720p or 1080p. Five aspect ratio options cover landscape, portrait, square, and intermediate formats: 16:9, 9:16, 1:1, 4:3, and 3:4. The 2.7 generation also brings smoother, more coherent motion than the 2.6 line, which helps generated subjects hold up under close comparison to their references.

What To Consider When Choosing a Provider

  • Configuration: Reference quality drives output quality. Clear, well-lit reference material gives the extraction pipeline more identity signal to work with, so curate your references before scaling up a render queue.
  • Configuration: Pricing is per second of generated video and varies by resolution, so a 1080p clip costs more than the same clip at 720p. Run a few test prompts in the AI Gateway playground to calibrate cost and generation time before full integration.
  • Zero Data Retention: AI Gateway supports Zero Data Retention for this model via direct gateway requests (BYOK is not included). To configure this, check the documentation.
  • Authentication: AI Gateway authenticates requests using an API key or OIDC token. You do not need to manage provider credentials directly.

When to Use Wan v2.7 Reference-to-Video

Best for

  • Character-Driven Video Series: Subjects that must look and sound consistent across many generated scenes
  • Brand and Spokesperson Content: Referenced people or mascots placed into new settings without a reshoot
  • Multi-Subject Compositions: Scenes where several referenced identities interact in a single generated clip
  • Multi-Shot Identity Stability: Sequences that keep referenced subjects consistent across automatic scene cuts

Consider alternatives when

  • Text-Only Generation: Wan-v2.7-t2v handles pure text-to-video when no reference subject is involved
  • Clips Beyond 10 Seconds: Wan-v2.7-t2v extends output duration to 15 seconds
  • Previous-Generation Pipelines: Wan-v2.6-r2v remains available for workflows already tuned to the earlier release

Conclusion

Wan v2.7 Reference-to-Video is the model to reach for when generated video must stay faithful to a real subject. Combined subject and voice referencing, multi-subject support, and smoother motion than the 2.6 line make Wan v2.7 Reference-to-Video a strong default for identity-sensitive video work on AI Gateway.