@heyshrutimishra: New video model just dropped. But this one isn't built for cinematic video. LingBot-Video is designed for embodied inte…
Summary
LingBot-Video, a 30B-parameter video model with sparse MoE, designed for embodied intelligence, is open-sourced. It outperforms existing models on RBench, trained on 70K+ hours of embodied data.
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Cached at: 07/09/26, 09:35 AM
New video model just dropped. But this one isn’t built for cinematic video.
LingBot-Video is designed for embodied intelligence. The training data is what sets it apart: 70,000+ hours of manipulation, navigation, and egocentric interaction. Internet video teaches how things look. This teaches how things change when you act on them.
30B parameters, only 3B active at inference. Sparse MoE, roughly 3x faster at long sequences. Already beats Wan2.6, Seedance 1.5 Pro, and Cosmos3 Super on RBench from Peking University and ByteDance.
It’s open source, which matters here. Researchers can actually build on it instead of just reading about it.
Robbyant (@robbyant_brain): Today we open-source LingBot-Video — the first MoE-based video foundation model built for embodied intelligence. 🔹30B params, only 3B active at inference. 🔹Augmented with 70K hours of embodied data on top of large-scale internet video pretraining. 🔹Already outperforming
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