Ant Group open-sources the multimodal model Ling-3.0-flash-VL

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Ant Group announced the open-sourcing of Ling-3.0-flash-VL, the first native multimodal model in its Bailing series. Built on the MoE architecture of Ling-3.0-flash, the model has 124B parameters and activates 5.5B per inference. It supports image, text, and video inputs with a 256K token context window. On-chain data shows increasing open interest in AI model development. The model introduces a visual feedback mechanism, enabling a closed-loop process of "observe → act → validate → correct." It maintains the efficient execution of Ling-3.0-flash in Agent workflows.

ChainThink reports that on September 9, according to an official announcement, Ant Group officially released and open-sourced the first native multimodal large model in the Ling series: Ling-3.0-flash-VL.

This model is an extension of the MoE architecture of Ling-3.0-flash, with a total of 124B parameters and 5.5B parameters activated per inference. It natively supports image, text, and video inputs, with a context window of up to 256K tokens.

Simultaneously introduce a visual feedback mechanism to transform task execution from a one-time generation into a closed loop of “observe → act → verify → correct,” while maintaining Ling-3.0-flash’s capability as an efficient execution node in the Agent workflow.

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