by InclusionAI
Ling-mini-2.0 is a small-sized, high-performance large language model based on the MoE architecture. It has a total of 16 billion parameters, but only activates 1.4 billion parameters per token (non-embedding 789 million), achieving extremely high generation speed. Thanks to the efficient MoE design and large-scale high-quality training data, despite activating only 1.4 billion parameters, Ling-mini-2.0 still demonstrates top-tier performance on downstream tasks comparable to dense LLMs under 10 billion parameters and even larger-scale MoE models.
| Input | $0.07 / 1M tokens |
| Output | $0.27 / 1M tokens |
| Modalities | text |
| Features | tools, function_calling, structured_outputs |
Use inclusionAI/Ling-mini-2.0 via the AIHubMix unified API — one interface for every major LLM.