Wan2.2 is an upgraded series of large-scale video generation models designed to enhance video content quality, coherence, and style controllability while maintaining a relatively reasonable computational burden. Its main innovations include the use of a MoE architecture to expand parameter scale without excessively increasing inference costs, as well as the introduction of highly compressed models (such as the 5B version) to enable video generation even on consumer-grade GPUs.
Hardware Requirements
The large model (14B version) has high GPU memory requirements for inference and may require offloading/distributed strategies.
The TI2V-5B version is a lightweight model that can run on consumer-grade GPUs (e.g., some high-end graphics cards) with 720P video output.GitHub
Multi-GPU/distributed deployment can significantly improve efficiency and capacity.
Model Variants
T2V-A14B: Text → Video model
I2V-A14B: Image → Video model
TI2V-5B: Text + Image → Video, lightweight version
S2V-14B: Speech/Audio → Video model










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