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