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Control-first Wan video model

Wan 2.7 AI Video Generator

Use Wan 2.7 on Inkfox AI for image-to-video with first/last-frame and first-clip controls, 720p or 1080p output. Free monthly credits to start.

First & last frame controlSmooth motionUp to 1080p

Wan 2.7 workbench

Control first frames, end frames, and video input with Wan 2.7

This workbench defaults to Wan 2.7. Test first frame, first+last frame, or first-clip control before choosing 720p or 1080p output.

48+ credits
Creation mode
Optional · Drop or Paste0/5000
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Public

Stability proof board

Newer generation upgrade

Wan 2.7 pushes motion coherence to the next generation

Use Wan 2.7 on Inkfox AI for image-to-video with first/last-frame and first-clip controls, 720p or 1080p output. Free monthly credits to start. As the newer Wan generation, it builds on the 2.6 baseline with stronger motion coherence and finer quality, plus first/last-frame and first-clip control for a more accurate landing.

First / last frame

Upload a first frame, add a last frame when needed, and flag the subject to lock.

Motion

Write one action so the newer in-between interpolation stays coherent.

Camera

Name one move; it pairs cleanly with first-clip control.

Delivery check

State output resolution, use case, and the detail that must stay consistent.

Image-to-video stability tests

Hover to preview motion
Wan 2.7 Bundle showcase

Upgraded sample

Bundle showcase

Wan 2.7 First dance

First/last landing

First dance

Wan 2.7 City travel

High-fidelity detail

City travel

01

First & last frame control

Give a start and end frame; Wan 2.7 fills a more coherent transition between them and lands more accurately.

02

High-fidelity product shots

Finer quality than Wan 2.6 keeps label text, reflections, and materials crisp once the shot moves.

03

First-clip continuation

Drive a continuation from a first clip; the newer motion coherence joins it without jumps or drift.

04

Delivery-ready cuts

When a 720p or 1080p clip goes straight to the edit, this generation locks the quality.

Creation steps

How to get a useful first video result

The fastest path is not a longer prompt. It is one readable frame, one motion goal, and one camera choice.

  1. 1

    Step 1

    Prepare a first frame, and add a last frame when you need a precise landing.

  2. 2

    Step 2

    Describe one action and one camera move so the in-between transition stays predictable.

  3. 3

    Step 3

    Confirm on a short clip that motion coherence improves over Wan 2.6.

  4. 4

    Step 4

    Output 1080p delivery directly once it holds, skipping a separate upgrade pass.

Prompt examples

Start from prompts that are easier to use

Before spending 48+ credits on a larger batch, make sure the subject, use case, and output requirements are clear.

First / last frame

Upload a first frame, add a last frame when needed, and flag the subject to lock.

Motion

Write one action so the newer in-between interpolation stays coherent.

Camera

Name one move; it pairs cleanly with first-clip control.

Delivery check

State output resolution, use case, and the detail that must stay consistent.

Model comparison

Use the key dimensions to choose the right model

Wan 2.7 is the newer generation: more coherent motion and finer quality than Wan 2.6, plus first/last-frame and first-clip control; reach for Kling 3.0 when controlled camera and character stability lead.

DimensionWan 2.7Wan 2.6Kling 3.0
Generation roleNewer upgradePrior balancedPremium pick
Motion coherenceStrongerSteadyStrong
Output qualityFinerReliableHigh
First/last frameYesBasicPartial
Resolution720p–1080p720p–1080p720p–1080p
Credit cost48+ credits70+ credits140+ credits

Prompt examples

Start from reusable prompt patterns

These examples show how to describe the subject, scene, camera, and final use so you can adapt them to your own image or video.

Try these prompts

First-to-last transition

First frame product front-on, last frame at a 45-degree side, camera orbits slowly to match, label stays readable, coherent transition, 5 seconds.

High-fidelity push-in

From the product first frame, slow push-in, a reflection travels along the metal edge, material texture stays crisp, subject stable, delivery-ready.

First-clip continuation

Continue from a first clip, the character keeps walking forward, camera pans to follow, motion joins without jumps, city street background.

Decision guide

When to choose Wan 2.7

Choose Wan 2.7

Choose it when the job matches use wan 2.7 on inkfox ai for image-to-video with first/last-frame and first-clip controls, 720p or 1080p output. free monthly credits to start.

Compare first

Compare with Wan 2.6, Kling, Runway, Veo, Hailuo, or Grok Imagine when the brief depends on a different strength, cost, or output format.

Quick answer

What is Wan 2.7 best for?

Wan 2.7 is best for use wan 2.7 on inkfox ai for image-to-video with first/last-frame and first-clip controls, 720p or 1080p output. free monthly credits to start.. Use it when that matches your goal, check the credit cost before generating, and compare another model when you need a different strength.

Return to the workbench

FAQ

Wan 2.7 FAQ

Model behavior, cost labels, and when to use this workbench.

What is Wan 2.7 best for?

Wan 2.7 is best for controlled image-to-video generation using first frame, first+last frame, or first-clip input when you need stable product or scene motion.

Which durations does Wan 2.7 support?

The Inkfox AI workbench exposes Wan 2.7 with 3, 5, 8, and 10 second presets, with 720p and 1080p output options.

Should I use Wan 2.7 or Wan 2.6?

Use Wan 2.7 when stronger control and newer Wan behavior matter. Use Wan 2.6 for balanced bilingual and multi-shot tests.

Ready with Inkfox AI

Test this model in the Inkfox AI workspace.

Use the Inkfox AI workbench for a quick generation, then compare real examples from other creator workflows.

Start with Inkfox AIView Gallery
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Inkfox AI is a free AI image and video generator for text to image, image-to-image editing, reference image creation, background removal, image upscaling, text-to-video, image-to-video, and multi-model visual generation.

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