Wan 2.2 14B I2V
Video Generation Model

Wan 2.2 14B I2V

Alibaba's Wan 2.1 14B I2V is a cutting-edge open-source diffusion transformer that transforms static images into cinematic, temporally coherent videos with exceptional motion dynamics and prompt adherence. This 14-billion parameter model delivers professional-grade 720p video generation with native support for both English and Chinese text prompts.

Overview

Wan 2.2 14B I2V is a video generation model available on the GenVR platform. Alibaba's Wan 2.1 14B I2V is a cutting-edge open-source diffusion transformer that transforms static images into cinematic, temporally coherent videos with exceptional motion dynamics and prompt adherence. This 14-billion parameter model delivers professional-grade 720p video generation with native support for both English and Chinese text prompts.

Key Features

  • 14 billion parameter diffusion transformer architecture optimized for video generation
  • Native 720p and 480p resolution support with 81-frame sequence generation
  • Causal Video VAE for efficient temporal compression and reconstruction
  • Bilingual prompt comprehension (English and Chinese) without translation layers
  • Apache 2.0 open-source license enabling commercial modification and distribution
  • Advanced physics-aware motion synthesis for realistic object dynamics
  • Optimized inference pipeline supporting consumer-grade GPUs with 16GB+ VRAM
  • Seamless integration with LoRA fine-tuning for custom styles and characters

Popular Use Cases

  1. Animating product photography for immersive e-commerce listings and digital catalogs
  2. Converting concept art and illustrations into cinematic trailer footage for games and films
  3. Generating dynamic avatar videos and portrait animations from single profile images
  4. Creating B-roll footage and atmospheric scenes for video editing projects
  5. Producing synthetic training data for computer vision and autonomous driving models

Best For

  • Marketing agencies creating dynamic product advertisements from static photography
  • Social media content creators producing short-form video content at scale
  • E-commerce platforms generating animated product demonstrations and 360° previews
  • Independent filmmakers and storyboard artists developing pre-visualization sequences
  • Game developers creating cinematic cutscenes and character animation prototypes

Limitations to Keep in Mind

  • Restricted to 5-second maximum clip duration (81 frames) requiring stitching for longer narratives
  • Requires high VRAM capacity (16GB+ recommended) for 720p generation without aggressive quantization
  • Limited text rendering capabilities within generated video frames
  • Complex multi-character interactions may exhibit occasional anatomical inconsistencies
  • No native audio generation or lip-sync capabilities for portrait animations

Why Choose This Model

  • Commercial Freedom: Apache 2.0 license permits unrestricted business usage without per-generation fees or usage caps.
  • Cinematic Quality: Native 720p resolution delivers broadcast-standard output suitable for professional advertising and content creation.
  • Bilingual Intelligence: Native understanding of English and Chinese prompts eliminates translation artifacts and cultural context loss.
  • Motion Realism: Advanced physics simulation creates natural object movements, gravity effects, and environmental interactions.
  • Temporal Consistency: Maintains character identity, object structure, and color grading across all 81 generated frames.
  • Cost Efficiency: Self-hosted deployment eliminates ongoing API costs for high-volume video production workflows.
  • Architectural Speed: Causal Video VAE design reduces computational overhead by 40% compared to standard video diffusion models.
  • Image Fidelity: Preserves fine details from source images including textures, lighting, and reflections while adding dynamic motion.
  • Prompt Precision: High alignment between text descriptions and generated content with minimal prompt engineering required.
  • Flexible Duration: Generates consistent 5.4-second clips (81 frames) that integrate seamlessly into standard video editing timelines.
  • Open Ecosystem: Active community support provides pre-trained LoRAs, ControlNet adapters, and workflow optimizations.
  • Hardware Optimization: Efficient quantization support enables operation on consumer GPUs without significant quality degradation.
  • Style Versatility: Handles diverse aesthetics from photorealistic cinematography to animated cartoon styles.
  • Camera Control: Supports implicit camera movements including pans, zooms, and tracking shots through text prompts.

Alternatives on GenVR

  • Runway Gen 3a Turbo
  • Vidu Q3 Turbo
  • Sora 2

Pricing

Billed through GenVR credits

9 credits per second of video

Credits45
Approx. INR₹45.00
Approx. USD$0.4770

Properties

Customizable parameters available for this model.

Required

image_urlstring

URL of the input image. If the input image does not match the chosen aspect ratio, it is resized and center cropped.

promptstring

The text prompt to guide video generation.

Optional

num_frames
integerDefault: 81

Number of frames to generate.

frames_per_second
integerDefault: 16

Frames per second of the generated video. When using interpolation and adjust_fps_for_interpolation is set to true (default true), the final FPS will be multiplied by the number of interpolated frames plus one.

negative_prompt
stringDefault: bright colors, overexposed, static, blurred details, subtitles, style, artwork, painting, picture, still, overall gray, worst quality, low quality, JPEG compression residue, ugly, incomplete, extra fingers, poorly drawn hands, poorly drawn faces, deformed, disfigured, malformed limbs, fused fingers, still picture, cluttered background, three legs, many people in the background, walking backwards

Negative prompt for video generation.

seed
integer

Random seed for reproducibility. If None, a random seed is chosen.

resolution
enumDefault: 720p

Resolution of the generated video.

480p580p720p
Model Info
CategoryVideo Generation

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Launch App

Developer API Docs

Integrate this model into your own applications. Access enterprise-grade performance, scalable infrastructure, and detailed documentation for rapid deployment.

Explore API

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