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Governed Profile

Wan

Wan is a usage-based model with non-token support, suited to video generation for enterprise teams.

Try Wan with your team

Last reviewed: 2026-05-31

Wan

Remova Media

Stable
Context Window
N/A
Input
Usage-based pricing
Video Output
Usage-based

What can you do with Wan?

Practical ways teams can use Wan inside governed AI workflows.

01

Create product demos with Wan

Generate short product videos, feature explainers, and launch clips from approved creative prompts with Wan.

02

Produce social video ads with Wan

Create short-form campaign clips, motion variants, and platform-specific visual stories with Wan.

03

Animate product visuals with Wan

Turn still product images, mockups, or brand concepts into controlled motion assets with Wan.

04

Draft explainer videos with Wan

Create visual sequences for onboarding, education, support, and internal enablement workflows with Wan.

05

Generate storyboard motion with Wan

Convert creative briefs into motion studies before committing to full production with Wan.

06

Create localization variants with Wan

Adapt campaign videos for different markets, audiences, formats, and approval paths with Wan.

07

Prototype video concepts with Wan

Explore scene direction, pacing, framing, and visual treatments for marketing review with Wan.

08

Govern media generation with Wan

Keep video creation behind role access, budget controls, review workflows, and audit trails with Wan.

09

Create training clips with Wan

Generate concise internal clips for employee enablement, process walkthroughs, and safety reminders with Wan.

10

Produce event teasers with Wan

Create motion assets for launches, webinars, announcements, and customer communications with Wan.

Why this model

Wan is available in Remova as a non-token option with Usage-based pricing input pricing, Usage-based output pricing, and text->video modality support for enterprise AI operations.

  • Wan offers non-token capacity for enterprise prompts and documents.
  • Current Remova pricing band is usage-based: Usage-based pricing input and Usage-based output.
  • Best-fit workloads include: Video generation.
  • Keep audit logs enabled for high-impact use cases.

At a glance

Model ID
remova/wan-xdjxdw
Context Window
N/A
Modality
text->video
Input Modalities
text
Output Modalities
video
Input Price
Usage-based pricing
Output Price
Usage-based
Provider
Remova Media
Listing Date
2025-07-31

Strengths

  • Wan is suited for video generation.
  • Supports text->video workflows for governed media and automation use cases.
  • Pricing profile is usage-based, enabling predictable workload routing decisions.
  • Can be paired with policy guardrails for safer deployment at scale.

Tradeoffs

  • Policy exceptions should be monitored and reviewed on a fixed cadence.
  • Quality and latency should be benchmarked against your internal prompt set before broad rollout.
  • Usage-based media models need per-workflow cost estimates before broad rollout.
  • Video generation workflows need review steps for brand, rights, and factual accuracy.

Best for

  • Wan for approved video generation, editing, and review workflows.
  • Wan for campaign, enablement, and product video assets under governance controls.
  • Wan for repeatable visual production where teams need auditability and budget limits.
  • Wan for approved video generation and editing workflows with review checkpoints.

Rollout checklist

  • Define where Wan is default vs. fallback in your routing policy.
  • Enable role-based access and policy checks before opening access broadly.
  • Set spend guardrails by team and monitor weekly token consumption.
  • Start with approved teams, then expand in controlled waves.
  • Re-run quality and cost benchmarks monthly as newer releases appear.

Related models

Explore adjacent model profiles for routing and benchmarking decisions.

Free Resource

Where Should Your Team Start with AI?

Tell us your industry and team size. We'll tell you which AI use cases will save the most time with the least setup.

You get

A shortlist of AI use cases ranked by impact and effort for your situation.

Tuning notes

prompt

Keep video prompts tied to approved claims, brand rules, and source assets.

duration

Set duration limits by workflow so review effort and spend stay predictable.

reference_media

Confirm rights for reference images, audio, and source clips before generation.

review_queue

Route generated video through brand, rights, and factual review before publication.

Free Assessment

What Could Go Wrong?

5 questions about how your company uses AI today. We'll show you the risks most companies miss until it's too late.

You get

A risk breakdown with the 3 things you should fix first.

Book demo
Knowledge Hub

Wan FAQs

Choose Wan when the workload aligns with video generation and quality targets justify its pricing profile.
It depends on workload mix. Most organizations use routing policies so routine traffic stays on lower-cost tiers.
Validate quality on real internal prompts, token efficiency, latency, and policy compliance behavior.

Deploy This Model With Governance

Use policy controls, role-based access, and budget guardrails before enabling advanced model tiers at scale.

Try Wan with your team