A beginner's guide to the Wan-2.2-I2v-Fast model by Wan-Video on Replicate

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This is a simplified guide to an AI model called Wan-2.2-I2v-Fast maintained by Wan-Video. If you like these kinds of analysis, you should join AImodels.fyi or follow us on Twitter.

Model overview

wan-2.2-i2v-fast is an optimized image-to-video generation model created by wan-video. This model uses PrunaAI optimization to deliver fast and cost-effective video generation from static images. It builds upon the Wan 2.2 A14B architecture, focusing on speed and efficiency while maintaining video quality. The model differs from the wan-2.2-t2v-fast variant by starting with an input image rather than generating videos from text prompts alone. Compared to higher-resolution alternatives like wan-2.1-i2v-720p, this version prioritizes speed and cost-effectiveness over maximum resolution.

Model inputs and outputs

The model transforms static images into dynamic video sequences using text prompts to guide the animation style and content. It generates videos at 480p resolution with configurable frame rates and duration settings. The system supports both 16:9 and 9:16 aspect ratios, making it suitable for different video formats and platforms.

Inputs

prompt: Text description guiding the video generation process
image: Input image file that serves as the starting frame
num_frames: Number of video frames to generate (81-100 frames, with 81 recommended)
resolution: Video resolution set to 480p with aspect ratio options
frames_per_second: Frame rate from 5-24 fps (16 fps default for optimal pricing)
go_fast: Boolean option to enable faster processing
sample_shift: Adjustment factor for sampling behavior (1-20 range)
seed: Optional random seed for reproducible results