# Wan v2.7 Reference-to-Video

Wan v2.7 Reference-to-Video advances the Wan reference-to-video line with combined subject and voice referencing, so a character's appearance and vocal identity carry from your reference material into newly generated scenes of 2 to 10 seconds.

- **Model ID:** `alibaba/wan-v2.7-r2v`
- **Type:** video
- **Providers:** alibaba
- **Context window:** Not applicable
- **Maximum output tokens:** 0
- **Pricing:** See the provider details below
- **Canonical page:** https://vercel.com/ai-gateway/models/wan-v2.7-r2v

## Supported parameters

Detailed capability metadata has not been reported for this model.

## Example

```ts
import { experimental_generateVideo as generateVideo } from 'ai';

const result = await generateVideo({
  model: 'alibaba/wan-v2.7-r2v',
  prompt: 'A serene mountain lake at sunrise.'
});
```

## About

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

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.

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.

## When to use

### Best For

- Character-driven video series where the same subject must look and sound consistent across many generated scenes
- Marketing and brand content that places a referenced spokesperson or mascot into new settings without a reshoot
- Multi-subject scenes where several referenced identities interact in a single generated clip
- Multi-shot sequences that need identity stability across automatic scene cuts

### Consider Alternatives When

- If no reference subject is involved and the video comes from a prompt alone, wan-v2.7-t2v handles pure text-to-video
- If you need clips longer than 10 seconds, wan-v2.7-t2v extends output to 15 seconds
- If your pipeline is already tuned to the previous generation, wan-v2.6-r2v remains available in the catalog

## 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

- **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

## Frequently asked questions

### What reference inputs does Wan v2.7 Reference-to-Video accept?

Wan v2.7 Reference-to-Video accepts reference images, reference videos, or both together, plus an optional text prompt describing the scene to generate. Up to three reference videos can be attached to a single generation.

### What durations and resolutions does Wan v2.7 Reference-to-Video support?

Clips run 2 to 10 seconds, with a default of 5 seconds, at 720p or 1080p. Five aspect ratios are available: 16:9, 9:16, 1:1, 4:3, and 3:4.

### How does Wan v2.7 Reference-to-Video differ from the previous Wan reference-to-video model?

Wan v2.7 Reference-to-Video adds combined subject and voice referencing, so appearance and vocal identity bind together from your reference material. Motion is also smoother and more coherent than in the 2.6 generation.

### Can Wan v2.7 Reference-to-Video keep a subject's voice consistent across generations?

Yes. Combined subject and voice referencing carries a referenced subject's vocal identity into the generated output alongside their visual appearance, keeping both consistent in new scenes.

### How do I use Wan v2.7 Reference-to-Video through AI Gateway?

Call Wan v2.7 Reference-to-Video with `generateVideo` from the AI SDK, passing your reference images or videos and an optional prompt. You can also try prompts first in the playground on this page.

### Does AI Gateway offer Zero Data Retention for Wan v2.7 Reference-to-Video?

Yes, Zero Data Retention is available for this model. Zero Data Retention is offered on a per-provider basis. See https://vercel.com/docs/ai-gateway/capabilities/zdr for details.

## Links

- [Model page](https://vercel.com/ai-gateway/models/wan-v2.7-r2v)
- [AI Gateway documentation](https://vercel.com/docs/ai-gateway)
- [Provider model documentation](https://wan.video/)
- [Provider pricing](https://modelstudio.console.alibabacloud.com/ap-southeast-1/?tab=doc#/doc/?type=model&url=prices)


If you encounter incorrect information, can’t find what you need, need a capability Vercel doesn’t currently offer, or have any other feedback to report, please do it by following the instructions at https://vercel.com/feedback.md.