Unverified60% confidenceFactExact time
Ling-3.0-flash adopts a Mixture of Experts (MoE) architecture with an activation ratio of only approximately 4% (approximately 5.1B activated out of 124B total parameters).
2
Sources
60%
Confidence
Long-term
Relevance
8/5/2026
First Seen
Sources
中国四大AI实验室路线对比：Qwen、DeepSeek、Moonshot、Ling战略解析
Related Claims
UnverifiedThe Ling-3.0-flash model has a total parameter count of 124B, with approximately 5.1B parameters activated per token, employs a KDA + MLA hybrid attention mechanism, and has a context length of 262k.78% similarUnverifiedXiaomi MiMo adopts a Mixture-of-Experts (MoE) architecture with a total parameter count of 24.6B, activating only approximately 5.3B parameters per inference.73% similarUnverified混元3是混合专家模型（MoE），总参数量为295B，激活参数约21B68% similarUnverified千问3.6的35B MOE模型每次只激活其中3B的参数67% similarUnverifiedMoE 架构每次前向传播只激活部分专家子网络，Qwen3.6 35B A3 中约激活 3B 参数64% similar
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