Ant Group’s Ling-3.0-flash-VL scores 25 on Intelligence Index with just 5.5B active parameters

Ant Group’s InclusionAI lab has released Ling-3.0-flash-VL, a multimodal AI model that scores 25 on the Artificial Analysis Intelligence Index while activating just 5.5 billion of its 124 billion total parameters per inference. The model, part of Ant Group’s Ling (Bailing) series, natively processes image, text, and video input. It’s been open-sourced under the MIT license, with BF16 and FP8 weights available on Hugging Face and ModelScope. What makes this model different The headline number, 25 on the Intelligence Index, matches the score achieved by Ling-3.0-flash, the text-only version that preceded it. Earlier evaluations actually showed the VL (vision-language) variant scoring 4 points higher than the text version, suggesting performance may vary depending on the benchmark suite applied. The model houses 124 billion parameters in total but only activates 5.5 billion for any given inference call. This mixture-of-experts style design means the model can deliver strong results without requiring the full parameter set to fire every time a query comes in. The model also features a context window stretching between 256K and 262K tokens, particularly relevant for enterprise use cases...