What is Wan 2.7 Reference-to-Video?

Wan 2.7 Reference-to-Video is an AI model (image to video) available on Artifio.ai through Wan. You can run it in our workspace from a single shared wallet and download your outputs.

How much does Wan 2.7 Reference-to-Video cost on Artifio?

Wan 2.7 Reference-to-Video starts at about $0.080 per second on Artifio.ai. The exact cost is shown in the workspace before you confirm and can vary with the options you select.

How do I use Wan 2.7 Reference-to-Video on Artifio?

Click Generate Now to open the workspace at /create/wan-2-7-r2v. Fill in the form fields, review the live cost estimate, and run your generation.

What kind of outputs does Wan 2.7 Reference-to-Video produce?

Wan 2.7 Reference-to-Video is configured for image to video workflows in the AI content category. See the technical parameters below for supported inputs and options.

Can I try Wan 2.7 Reference-to-Video for free?

Sign up free, top up your wallet from $5, and you can run Wan 2.7 Reference-to-Video pay-as-you-go without a separate subscription for this model.

Wan 2.7 Reference-to-Video — AI Video Generator

Name: Wan 2.7 Reference-to-Video
Brand: Artifio
Price: 0.080 USD
Availability: InStock

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Wan 2.7 Reference-to-Video — AI Video Generator | Artifio.ai

About Wan 2.7 Reference-to-Video

Wan 2.7 Reference-to-Video (Wan2.7-r2v) is the reference-driven model in Alibaba's Wan2.7-Video release of April 2026. You supply reference material for a character, prop, or scene, and the model generates new shots that preserve that identity. It extends the reference-to-video mode Alibaba introduced in Wan 2.6, and the Model Studio documentation adds two concrete upgrades: multi-entity referencing and configurable voice timbre for the generated speech.

The wider Wan 2.7 generation adds cross-video consistency for up to five distinct characters, each with an exclusive voice tone and visual identity, which is the machinery this model exposes most directly. Artifio runs it in one workspace beside 100+ other models, billed per generation.

Features

Generates new video shots from reference material while preserving the referenced identity.
Multi-entity referencing, so several characters or objects can be carried into one generated scene.
Configurable voice timbre for generated dialogue.
Outputs 720p or 1080p at 30 fps with audio.
Any integer duration from 2 to 10 seconds.
Part of a generation that holds up to five distinct characters consistent across separate videos.

What people use it for

Keeping a brand mascot or spokesperson identical across a whole campaign of generated clips.
Placing a real person into scenes that were never filmed, voice included.
Multi-character skits where two or more referenced identities share a frame.
Product continuity shots where the referenced item must look the same in every scene.

Reported strengths

Identity preservation extends beyond faces to props and scenes, per Alibaba's documentation of multi-entity referencing.
Voice timbre control means the character sounds consistent, and adjustable, across generations.
No fine-tuning step; the reference material itself carries the identity.

Reported limitations

Duration is capped at 10 seconds, below the 15 seconds of the generation's text-to-video and image-to-video models.
Resolution stops at 1080p.
Hosted-only; no open weights exist for Wan 2.7 on the Wan GitHub organization.

Sources

Alibaba unveils Wan2.7-Video to elevate creators from executors to directors (Alibaba Cloud)
Video generation, Alibaba Cloud Model Studio documentation (Alibaba Cloud)
Alibaba releases Wan2.7-Video AI model for multimodal video generation and editing (The Elec)
Wan2.2: open and advanced large-scale video generative models (GitHub (Wan-Video))