Expired50% confidenceFactExact time
MAI Thinking-E has a total parameter count of approximately 1T (trillion), with approximately 35B activated parameters, and uses a MoE (Mixture of Experts) architecture.
1
Sources
50%
Confidence
Medium-term (~90 days)
Relevance
7/2/2026
First Seen
Valid until: 9/30/2026(expired)
Sources
Related Claims
UnverifiedHy3 adopts a Mixture of Experts (MoE) architecture with a total parameter count of 295 billion (295B), activating only 21 billion (21B) parameters per inference.73% similarVerifiedQwen3-235B总参数量为2350亿，采用MoE架构，每次前向推理实际激活的参数量约22B72% similarUnverified千问三235B MoE总参数量2350亿，但每次推理实际激活的参数约22B70% similarUnverifiedQwen Coder adopts a Mixture of Experts (MoE) architecture with 480 billion total parameters, activating only 35 billion parameters during inference.70% similarVerifiedGemma 4's 26B MoE model uses a Mixture of Experts architecture, with 26 billion total parameters but only approximately 4 billion parameters active at any given moment.69% similar
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