Ant Group has open-sourced LingBot-Video, described as the world’s first open-source video foundation model for embodied intelligence built on a Mixture-of-Experts (MoE) architecture. By replacing traditional dense architectures with MoE to expand capacity while controlling per-inference cost, the 30B-parameter model activates roughly 3B parameters during generation—about three times the inference efficiency of a comparable dense model—aiming to combine large-scale visual expressiveness with the

Ant Group has open-sourced LingBot-Video, described as the world’s first open-source video foundation model for embodied intelligence built on a Mixture-of-Experts (MoE) architecture. By replacing traditional dense architectures with MoE to expand capacity while controlling per-inference cost, the 30B-parameter model activates roughly 3B parameters during generation—about three times the inference efficiency of a comparable dense model—aiming to combine large-scale visual expressiveness with the efficient inference required for embodied intelligence.