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Alibaba Wan 2.5 API – AI Video Generation with Audio Sync

Mivo · AI Video

Short‑form loops · Vertical presets · Fast iteration

Wan 2.5 is tuned for short, responsive generations where speed and control matter. It excels at vertical content, loops, and branded templates, helping creators iterate quickly without sacrificing motion continuity.

Wan 2.5 Video Generation Guide hero

Introducing the Alibaba Wan 2.5 API for AI Video Creation

Wan 2.5 focuses on fast iteration with practical control. Prompts that clearly define a single subject and action produce stable loops and consistent motion. Because it’s optimized for vertical output, it pairs well with short‑form social content and template‑driven branding.

Use Wan 2.5 when you need to test ideas rapidly. Keep the language specific and avoid over‑describing style. For loops, call out loopability and ensure the action can restart cleanly. On Mivo, publish finalized clips directly to your profile or export for post‑production.

Wan 2.5 is now available at MivoWan 2.5 cinematic forest frameWan 2.5 loopable motion example

Generation methods supported by Wan 2.5 API

Text‑to‑Video (wan2.5‑t2v‑preview api)

Generate videos directly from text prompts. Describe scenes, actions, and environments to produce cinematic clips with smooth motion and synchronized audio.

Image‑to‑Video (wan2.5‑i2v‑preview api)

Animate a still image while preserving identity and style. Introduce lifelike camera motion and lighting changes for product showcases and storytelling.

Text‑to‑video exampleImage‑to‑video exampleLoop and branding example

Key features that make Wan 2.5 API stand out

Native audio & seamless A/V sync

Generate video and audio together in a single request for immersive outputs without extra editing.

Accurate prompt adherence

Camera angles, lighting, and motion directions are followed closely, helping translate creative intent into consistent results.

Flexible style adaptation

Supports a range of looks—from cinematic realism to stylized outputs—while preserving subject identity and scene coherence.

Multi‑mode options

Text‑to‑video and image‑to‑video endpoints with multiple aspect ratios (9:16, 1:1, 16:9) for varied destinations.

How to get started with Wan 2.5 on Mivo

Step 1. Open Generate and choose Wan 2.5. Write one or two clear sentences defining subject and action, then add environment and camera.

Step 2. Select aspect ratio (9:16, 1:1, or 16:9) and keep duration short to iterate quickly.

Step 3. Preview and change a single variable per attempt—camera move, lighting, or mood—to see the effect.

Step 4. When the look is consistent, render a final pass and publish to your Mivo profile or download for external editing.

Wan 2.5 API vs Veo 3: Which Fits Your Needs?

Both Alibaba Wan 2.5 API and Google Veo 3 represent the latest in AI video generation. Each supports text‑to‑video and image‑to‑video; Veo 3 aims for premium cinematic polish, while Wan 2.5 emphasizes native audio‑video sync and rapid iteration.

Generation Modes
Wan 2.5 API (Alibaba)
Text‑to‑Video (wan2.5‑t2v‑preview), Image‑to‑Video (wan2.5‑i2v‑preview)
Veo 3.1 (Google)
Text‑to‑Video, Image‑to‑Video
Audio & A/V Sync
Wan 2.5 API (Alibaba)
Native audio generation (dialogue, ambience, BGM) aligned to visuals
Veo 3.1 (Google)
Audio available; focus remains on premium visuals
Prompt Adherence
Wan 2.5 API (Alibaba)
Strong fidelity to camera, lighting, motion
Veo 3.1 (Google)
Cinematic quality; can waver on highly abstract prompts
Style Adaptation
Wan 2.5 API (Alibaba)
Realism → stylized templates; preserves identity
Veo 3.1 (Google)
Focus on cinematic realism
Multilingual Support
Wan 2.5 API (Alibaba)
Good performance incl. Chinese
Veo 3.1 (Google)
Limited in non‑English prompts
Video Duration
Wan 2.5 API (Alibaba)
Short clips; assemble sequences in post
Veo 3.1 (Google)
Short clips (~8s typical)
Aspect Ratio Options
Wan 2.5 API (Alibaba)
9:16, 1:1, 16:9
Veo 3.1 (Google)
Primarily cinematic; fewer presets
Best For
Wan 2.5 API (Alibaba)
Loops, vertical formats, branded templates, fast iteration
Veo 3.1 (Google)
Premium cinematic looks and steady camera control

Wan 2.5 vs Sora 2: Flagship AI Video Generators Compared

Based on recent public information and previews: both models target synchronized audiovisual generation, tighter prompt adherence, and cinematic motion—yet with different philosophies. Sora 2 leans into robust world simulation and managed access; Wan 2.5 emphasizes developer‑friendly previews and fast iteration.

Positioning
Sora 2 (OpenAI)
Flagship integrated with ChatGPT & Sora App
Wan 2.5 (Alibaba)
Next‑gen Wan aimed at open previews & developer workflows
Native Audio
Sora 2 (OpenAI)
Yes: synchronized dialogue, ambience, effects
Wan 2.5 (Alibaba)
Yes: first Wan with native audio tracks aligned to visuals
Prompt Control
Sora 2 (OpenAI)
Strong multi‑shot narrative control; maintains world state/physics
Wan 2.5 (Alibaba)
Improved obedience to camera moves, layout, and timing vs Wan 2.2
Motion & Physics
Sora 2 (OpenAI)
Physics‑aware simulation to avoid artifacts; continuity across shots
Wan 2.5 (Alibaba)
Smoother motion and temporal consistency than Wan 2.2
Resolution & Length
Sora 2 (OpenAI)
Reports of 1080p+ in some modes (limits undisclosed)
Wan 2.5 (Alibaba)
Preview info points to 1080p clips; caps evolving
Input Modalities
Sora 2 (OpenAI)
Text prompts, cameo uploads, style conditioning
Wan 2.5 (Alibaba)
Text‑to‑video, image‑to‑video, stylization, scripted dialogue timing
Deployment & Access
Sora 2 (OpenAI)
Closed ecosystem via OpenAI apps/APIs
Wan 2.5 (Alibaba)
Open‑preview via partners (e.g., Fal/Pollo AI)
Monetization/Pricing
Sora 2 (OpenAI)
Subscription (ChatGPT Pro, enterprise tiers)
Wan 2.5 (Alibaba)
Promotional credits; pricing still forming
Cameo/Identity
Sora 2 (OpenAI)
Cameo insertion supported in Sora App
Wan 2.5 (Alibaba)
No confirmed parity yet (may evolve)
Strengths
Sora 2 (OpenAI)
Airtight controllability, robust physics, managed infra
Wan 2.5 (Alibaba)
Developer‑friendly, native audio, fast iteration, cost‑aware
Ideal Use Cases
Sora 2 (OpenAI)
Complex narrative scenes, identity control, premium polish
Wan 2.5 (Alibaba)
Rapid prototyping, vertical/loopable formats, modular pipelines

Notes: Summaries based on public previews and community coverage as of late 2025; details may evolve.

Prompt guidance

Use active verbs and keep each clip to one action. Add background, mood, and color briefly to set the look without over‑constraining the model. If you need a seamless loop, say so explicitly and frame the motion so it can repeat.

For branded templates, define composition first, then mention the subject and motion. This helps preserve layout while still allowing expressive movement.

Vertical composition and safe areas

In vertical layouts, keep the subject centered and leave space at the top and bottom for captions or CTA overlays. Early in the process, test typography against your framing so titles and stickers do not clash with motion. For repeatable formats, lock a composition and only vary subject and color.

When the clip includes quick movement, aim for a steady camera with a single subject action so the frame remains readable. Subtle parallax and foreground elements add depth without distracting from the core message.

Loop craft and transitions

To design a seamless loop, choose a motion that can reset naturally—a hand wave, a pendulum sway, or a rotating turntable. Keep lighting steady and avoid sudden occlusions that make the cut visible. If needed, add a micro‑dissolve in post to hide the seam.

For carousel or multi‑clip posts, match color tone and contrast between takes so transitions feel intentional. A gentle global vignette or light halation can unify shots generated at different times.

Text‑to‑video vs image‑to‑video

Use text‑to‑video to brainstorm quickly and discover a direction for motion and framing. When branding or character identity must stay consistent, switch to image‑to‑video so the subject, logo position, or composition remains stable as you add movement.

Many teams start with short text‑based clips to validate concepts, then lock a strong reference frame and iterate with image‑to‑video for finals. This preserves proportions and layout across attempts.

Template‑driven branding

Define a template with fixed margins, type styles, and a safe area for product or subject. Then describe only the subject motion and mood in each prompt. This approach speeds up production while keeping every post on‑brand.

When reusing templates, favor consistent camera language and lighting. If a variation feels off, reduce style text and keep descriptors that directly support your theme, like “soft daylight studio” or “neon arcade glow.”

Aspect ratios and duration

Choose 9:16 for vertical placements, 1:1 when center‑weighted composition matters, and 16:9 for widescreen contexts. Start with short durations to iterate rapidly; extend only after you are confident in framing and motion.

Short loops between five and twelve seconds perform well for discovery feeds. If you need a longer narrative, assemble several concise clips in post rather than forcing a single extended take.

Post‑production workflow

Export from Mivo and add captions, stickers, or light color finishing in your editor. Keep overlays within the vertical safe area and test on different device sizes. A consistent text style and a subtle audio bed help unify a series of clips.

To maintain loop integrity, avoid hard cuts at the seam and place transitions on downbeats. When pacing a set of clips, arrange them by energy to guide attention from quiet moments to highlights.

Troubleshooting and refinement

If motion looks busy, simplify to one action and reduce background detail. When the subject drifts off center, restate framing and specify a steady camera. If style varies across takes, reuse a compact prompt skeleton and only change one variable between attempts.

For loops that pop at the join, shorten the move, reduce highlights near the seam, and add a subtle crossfade in post. Keep comparisons side by side to measure progress against a clear target.

Vertical template stillLoopable motion stillFinal branded pass

FAQs

What is Wan 2.5 API?
Wan 2.5 is an advanced AI video model. Through its preview APIs, it supports text‑to‑video (wan2.5‑t2v‑preview) and image‑to‑video (wan2.5‑i2v‑preview) for generating cinematic short clips.
How is Wan 2.5 different from Veo 3?
Both handle text/image → video. Wan 2.5 emphasizes native audio‑video sync, flexible outputs, and fast iteration; Veo 3.1 focuses on premium cinematic polish and stable camera control.
Does Wan 2.5 support audio sync?
Yes. Wan 2.5 can align dialogue, ambient effects, and background music with visuals in supported environments. You can still replace or enhance audio in post.
What aspect ratios and resolutions are available?
Common ratios include 9:16, 1:1, and 16:9. Resolutions depend on mode; start with social‑friendly sizes to iterate quickly, then increase when the look is locked.
How long can the generated clips be?
Short durations are recommended for best fidelity and speed. For longer stories, assemble several concise shots in post.
Does it support both text‑to‑video and image‑to‑video?
Yes. Use text‑to‑video for ideation and image‑to‑video to preserve identity and composition while adding motion.
How do I get started on Mivo?
Open Generate, pick Wan 2.5, write a concise prompt, choose ratio and duration, preview, iterate one variable at a time, then publish or download.
Is Wan 2.5 suitable for production?
Yes. Its responsive iteration and stable motion make it reliable for branded templates, vertical formats, and loopable clips.