HomeAnt Bailing Ling-2.6-1T Open Source: Trillion-Parameter Model Rivals GPT-5.4
Ant Financial's BaiLing large model, known as "Ling," announced today the open-source release of its trillion-parameter flagship model, Ling-2.6-1T. Building on the technical foundation introduced last week, this model moves away from simply chasing ultra-long reasoning chains or excessive parameter counts. Instead, it implements an innovative "Fast-Thinking" mechanism through a hybrid MLA and LinearAttention architecture, designed to tackle the efficiency challenges of trillion-parameter models in real-world production environments.
Test results indicate that Ling-2.6-1T achieves exceptional Token Efficiency in comprehensive Artificial Analysis benchmarks, completing the full evaluation using only 16M tokens. This translates to output costs roughly one-quarter of comparable models. In terms of overall intelligence, the model performs at a level comparable to GPT-5.4 (non-inference mode). For practical metrics like reasoning, code execution, tool calling, and multi-step task completion, Ling-2.6-1T sets a new SOTA (state-of-the-art) standard within the open-source domain.
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![ThomasScott]()
万亿参数？蚂蚁这是要把GPU当饭吃啊😂 开源好评，但参数多≠智商高，隔壁某模型参数少一半照样吊打。先观望实际表现，别光顾着刷榜。
Ant Financial's BaiLing large model, known as "Ling," announced today the open-source release of its trillion-parameter flagship model, Ling-2.6-1T. Building on the technical foundation introduced last week, this model moves away from simply chasing ultra-long reasoning chains or excessive parameter counts. Instead, it implements an innovative "Fast-Thinking" mechanism through a hybrid MLA and LinearAttention architecture, designed to tackle the efficiency challenges of trillion-parameter models in real-world production environments.
Test results indicate that Ling-2.6-1T achieves exceptional Token Efficiency in comprehensive Artificial Analysis benchmarks, completing the full evaluation using only 16M tokens. This translates to output costs roughly one-quarter of comparable models. In terms of overall intelligence, the model performs at a level comparable to GPT-5.4 (non-inference mode). For practical metrics like reasoning, code execution, tool calling, and multi-step task completion, Ling-2.6-1T sets a new SOTA (state-of-the-art) standard within the open-source domain.
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万亿参数？蚂蚁这是要把GPU当饭吃啊😂 开源好评，但参数多≠智商高，隔壁某模型参数少一半照样吊打。先观望实际表现，别光顾着刷榜。
