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   Agnes open-sources 28.7B-parameter MoE video model

   Agnes has open-sourced Agnes-Video-2.0-MoE, an audio-video generation model built by converting its roughly 15.3B-parameter dense pretrained model DaVinci-MagiHuman into a mixture-of-experts design: most of the structure is kept, while parts of 32 of its 40 layers are each expanded into three expert networks, with routing selecting one expert per step so activated parameters stay near 15.3B while total parameters reach about 28.7B. Agnes says the model generates a 5-second video in roughly 30 seconds on a single H200 GPU — about 20% faster inference than the dense version and more than twice as fast as comparable MoE video models. The team also applies EENP elastic expert neuron pruning, first scoring expert computation channels separately for video, audio and text and then merging the scores to cut channels; at 60% pruning, average activated parameters fall to about 11.7B and denoising time drops from 26.83s to 20.92s (about 22% less), though the VBench-2.0 score is about 92.4% of the unpruned MoE, with details degrading more in high-motion scenes as pruning deepens.

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