wavespeed-ai/wan-2.1/i2v-480p

Wan2.1-i2v-480p is an open-source AI video generation model developed by Alibaba Cloud, designed for image-to-video tasks. The 14-billion-parameter professional version excels in generating complex motions and simulating physical dynamics, delivering exceptional performance. Built upon a causal 3D Variational Autoencoder (VAE) and Video Diffusion Transformer architecture, Wan2.1-i2v-480p efficiently models spatiotemporal dependencies. In the authoritative VBench evaluation, the 14B version achieved a leading score of 86.22%, surpassing models like Sora, Luma, and Pika, and securing the top position. The model is available on Wavespeed AI, providing convenient access for developers.

Key Features

• State-of-the-Art Performance: wan-2.1-i2v-480p consistently outperforms existing open-source and commercial video generation solutions on multiple benchmarks.
• Consumer-Grade GPU Support: Optimized to run on widely available hardware—with models like T2V-1.3B requiring only 8.19 GB of VRAM—enabling efficient processing on consumer-grade GPUs. For example, generate a 5-second 480P video on an RTX 4090 in about 4 minutes.
• Multi-Task Versatility: Excels across a range of applications, including text-to-video, image-to-video, video editing, text-to-image, and video-to-audio, thereby broadening its utility in creative and practical contexts.
• Dual-Language Visual Text Generation: The model pioneers video generation capable of rendering both Chinese and English text, enhancing its adaptability in global applications.
• Robust Video VAE: Integrates a powerful video variational autoencoder that efficiently encodes and decodes video content at 1080P resolution while preserving crucial temporal information.

ComfyUI

wan-2.1-i2v-480p is also available on ComfyUI, providing local inference capabilities through a node-based workflow, ensuring flexible and efficient image generation on your system.

Limitations

• Creative Rather Than Factual: wan-2.1-i2v-480p is designed for creative video generation and should not be relied upon for generating factually accurate content.
• Statistical Biases: As a data-driven model, it may reflect biases present in the training data.
• Prompt Sensitivity: Output quality and adherence are closely tied to the input prompt’s clarity and style, leading to potential variability.
• Interpretative Constraints: The model’s performance might fluctuate depending on the complexity and nuance of the task, sometimes leading to unexpected results.

Out-of-Scope Use

The model and its derivatives may not be used in any way that violates applicable national, federal, state, local, or international law or regulation, including but not limited to:

• Exploiting, harming, or attempting to exploit or harm minors, including solicitation, creation, acquisition, or dissemination of child exploitative content.
• Generating or disseminating verifiably false information with the intent to harm others.
• Creating or distributing personal identifiable information that could be used to harm an individual.
• Harassing, abusing, threatening, stalking, or bullying individuals or groups.
• Producing non-consensual nudity or illegal pornographic content.
• Making fully automated decisions that adversely affect an individual’s legal rights or create binding obligations.
• Facilitating large-scale disinformation campaigns.

Accelerated Inference

Our accelerated inference approach leverages advanced optimization technology from WavespeedAI. This innovative fusion technique significantly reduces computational overhead and latency, enabling rapid image generation without compromising quality. The entire system is designed to efficiently handle large-scale inference tasks while ensuring that real-time applications achieve an optimal balance between speed and accuracy. For further details, please refer to the blog post.