AI 导读
Ling-3.0-flash-Fin 位于智能指数与激活参数的帕累托前沿上，以每 token 5.1B 激活参数得分 23，而 Ling-3.0-flash-VL 以每 token 5.5B 激活参数得分 25。两者总参数量均为 124B，而 Qwen3.8 27B（xhigh）以 27B 总参数量得分 34，使两个 Ling 模型均处于总参数前沿之下。
正文
Ling-3.0-flash-Fin sits on the Intelligence Index vs. active parameters Pareto frontier, scoring 23 with 5.1B active parameters per token vs. a score of 25 or Ling-3.0-flash-VL which uses 5.5B active per token. Both have 124B total parameters, while Qwen3.8 27B (xhigh) scores 34 with 27B total parameters, placing both Ling models below the total-parameter frontier.
来源：@ArtificialAnlys · x.com