bikabika AI
Alibaba 2026 (Wan 2.7)

Wan 2.7

Thinking Mode·first/last-frame control·reference-to-video·instruction editing AI video generation

Wan 2.7 (Tongyi Wanxiang 2.7) is Alibaba Tongyi Lab's next-generation AI video generation and editing suite, covering text-to-video, image-to-video, reference-to-video, and natural-language video editing. Wan 2.7 excels at Thinking Mode prompt planning, first/last-frame control, multi-reference consistency, and native synced audio-visual—ideal for short-video creators, ad and e-commerce teams, film pre-viz, and developers to complete an iterative production loop online from idea to refined output.

Core specialty

Thinking Mode

Workflow

Generate + edit

Duration

~2–15 sec

Resolution

720P/1080P

💡 Why Choose

Why choose Wan 2.7?

Wan 2.7 (Tongyi Wanxiang 2.7) is Alibaba Tongyi Lab's next-generation AI video suite for "controllable creation." Unlike older one-shot generation with hard precise editing, Wan 2.7 unifies text-to-video, image-to-video, reference-to-video, and natural language editing in one system—Thinking Mode improves planning quality for complex storyboards and action sequences.

For ad, e-commerce, and content teams, Wan 2.7 shifts creators from "executors" to "directors": first/last frame control motion start and end, multi-reference stabilizes character and style, instruction editing changes action/dialogue/scene without full regeneration, native synced audio-video reduces post-dubbing cost. 720P/1080P and flexible ~2–15 sec duration support layered preview trials and final delivery.

On bikabika AI, you can explore Wan 2.7 core capabilities, mode differences, typical use cases, and usage steps in one place to quickly assess whether it fits your controllable video workflow—and start AI video creation from the online experience entry.

⚡ Features

Wan 2.7 core features

The six capabilities below form Wan 2.7's core competitive strengths in controllable AI video generation and editing.

Thinking Mode Prompt Planning

Wan 2.7 plans and decomposes complex prompts before generation, improving adherence for multi-shot storytelling, action sequences, and camera language.

Text-to-Video / Image-to-Video

Wan 2.7 generates video from text or drives motion with first frame or first/last frames—covering concept validation through shot-level content production.

Reference-to-Video Consistency

Wan 2.7 constrains characters and style with multi-image/video references, strengthening cross-shot appearance consistency for serialized shorts and brand character content.

Natural-Language Video Editing

Wan 2.7 edits actions, dialogue, scenes, style, and camera work via instructions—reducing full regeneration and accelerating iteration to final output.

Native Synced Audio-Visual

Wan 2.7 generates audio and visuals together—dialogue and ambience sync with picture, lowering post-production dubbing and alignment costs.

720P / 1080P & Flexible Duration

Wan 2.7 supports ~2–15 second flexible duration and 720P/1080P output, balancing rapid trial and delivery clarity.

Want to experience Wan 2.7 director-level control?

Thinking Mode, first/last frames, multi-reference, and instruction editing are ready—start your first controllable AI video now.

🔄 Compare

Wan 2.7 instruction editing vs full regeneration

Wan 2.7 supports natural language re-editing and full regeneration—the comparison below helps you choose between fine-tuning finals and rebuilding concepts.

Wan 2.7 instruction editing vs full regeneration
DimensionInstruction editingFull regeneration
Operation methodDescribe changes in natural languageRewrite prompt and regenerate fully
Preserve originalHigh—local changes more stableLow—more output variance
Best phaseFinal tweaks, proposal revisionsConcept exploration, direction reset
Controllable dimensionsAction/dialogue/scene/style/cameraRe-interprets entire prompt
Time costUsually lowerUsually higher
Reference constraintsCan stack references and frame controlCan stack but may lose existing shots
Audio-video handlingCan adjust performance selectivelyOften requires full audio-video redo
Typical scenariosChange expression, swap background, adjust cameraSwap script, change narrative structure

💎 Highlights

Wan 2.7 technical highlights

  • Wan 2.7 unifies text-to, image-to, reference-to, and instruction-editing video workflows
  • Wan 2.7 Thinking Mode improves complex prompt planning and adherence
  • Wan 2.7 first/last-frame control makes motion start/end more predictable
  • Wan 2.7 multi-reference input strengthens character and style consistency
  • Wan 2.7 natural-language editing shortens iteration cycles
  • Wan 2.7 native synced audio-visual and 720P/1080P flexible delivery

🎯 Use Cases

Wan 2.7 use cases

From ad storyboards to instruction-based re-editing, Wan 2.7 delivers highly controllable, iterable AI video production across the six scenarios below.

Ad creative · Brand ops

Ad storyboards and brand narrative

Use Wan 2.7 Thinking Mode to plan multi-shot beats, then lock start/end frames—quickly produce reviewable ad narrative samples.

  • Ad storyboard
  • Brand film
  • Wan 2.7

E-commerce ops · Visual design

E-commerce product demo clips

Wan 2.7 image-to-video shows unboxing and usage actions; use instruction editing to fine-tune material sheen or camera push when results need adjustment.

  • E-commerce
  • Image-to-video
  • Wan 2.7

IP ops · Short content teams

Character-consistent series content

Wan 2.7 multi-reference input stabilizes character appearance and style—ideal for series shorts, character voiceover, and coherent brand content.

  • Character consistency
  • Reference-to-video
  • Wan 2.7

Directors · Production teams

Film pre-visualization and shot validation

Before formal shooting, use Wan 2.7 to validate shot size, camera motion, and story pacing—reducing live-action trial cost and aligning team visual language.

  • Pre-visualization
  • Storyboard
  • Wan 2.7

Editors · Content production

Instruction-based re-editing of existing footage

Wan 2.7 natural language editing can change action, dialogue, scene, and style—ideal for low-cost revisions in final stages without full regeneration.

  • Video editing
  • Iteration
  • Wan 2.7

Creators · Content teams

Short video hooks and social creatives

Wan 2.7 quickly generates vertical short-video hooks—Thinking Mode improves complex action prompt adherence for high-frequency creative trial-and-error.

  • Short video
  • Social media
  • Wan 2.7

📖 Guide

How to use Wan 2.7

Follow the steps below to get started quickly and create your first controllable AI video with Wan 2.7.

  1. Define control goals

    Define aspect ratio, duration, and resolution (e.g., 16:9, 8–15 seconds, 1080P) and write structured prompts covering subject, action sequence, camera, and mood.

  2. Prepare references and frame constraints

    Specify first/last frames for stronger control; upload multiple reference images or video for character consistency.

  3. Enable Thinking / audio

    Enable Thinking Mode for complex storyboards; enable native audio for voiceover scenarios.

  4. Generate and iterate with instructions

    When unsatisfied, prefer natural-language edit instructions over rewriting entire prompts.

❓ FAQ

Wan 2.7 FAQ

Below are the most common questions about Wan 2.7 Thinking Mode, workflow, audio-video capabilities, and usage paths.

What is Wan 2.7? Who is it for?

Wan 2.7 is Alibaba Tongyi Lab's AI video generation and editing suite covering text-to-video, image-to-video, reference-to-video, and instruction editing. Ideal for short-video creators, ad and brand teams, e-commerce operators, film pre-viz teams, and developers needing higher controllability and iteration efficiency.

What is Wan 2.7 Thinking Mode for?

Thinking Mode plans and decomposes complex prompts before generation, helping the model better understand multi-shot storytelling, action sequences, and camera constraints—typically improving adherence on complex instructions.

What generation and editing modes does Wan 2.7 support?

Wan 2.7 commonly supports text-to-video (t2v), image-to-video (i2v, including first/last frame), reference-to-video (r2v), and natural-language video editing (videoedit)—switching between generation, extension, reference, and re-editing.

Can Wan 2.7 generate video with sound directly?

Yes. Wan 2.7 supports native synced audio-visual—dialogue or ambience sync during generation. Disable audio per platform options to export video-only when not needed.

How does Wan 2.7 differ from HappyHorse?

Both are from the Alibaba ecosystem. Wan 2.7 (Tongyi Wanxiang) emphasizes Thinking Mode, first/last-frame control, multi-reference consistency, and instruction-editing workflow; HappyHorse highlights native audio-visual, multilingual lip sync, and unified text/image/editing generation experience. Choose or cross-test by platform capability and project needs.

How do I use Wan 2.7 online?

Submit prompts and reference assets on platforms supporting Tongyi Wanxiang / Wan. Or learn Wan 2.7 features and use cases on bikabika AI, then jump to the online experience entry to start AI video creation.

💡 Tips

Wan 2.7 prompt and creation tips

  • For complex storyboards, enable Thinking Mode and structure prompts by "shot/action/camera/dialogue".

  • Use first frame or first/last frames for precise start/end; provide multi-angle references for character series content.

  • Use 720P and shorter duration for preview; switch to 1080P and longer duration for finals once direction is confirmed.

  • For voiceover, enable native audio and specify language/tone; disable audio track for picture-only delivery.

  • In fine-tuning phase, prefer instruction editing (change one thing at a time) over full regeneration to preserve satisfactory shots.

Ready to try Wan 2.7?

Get started now and unlock your AI creative potential with Wan 2.7