Unverified60% confidenceFactExact time
The MoE architecture can have an extremely large total parameter count while activating only a small fraction of parameters per inference; top-tier models including GPT-4, Mixtral, and Gemini all adopt this architecture.
2
Sources
60%
Confidence
Long-term
Relevance
7/8/2026
First Seen
Sources
Related Claims
VerifiedGPT-4和Mixtral等主流大模型也采用了MoE架构78% similarVerifiedThe MoE architecture dynamically selects a small number of experts to participate in computation through a router, achieving sparse activation; mainstream frontier models including GPT-4, Mistral, and DeepSeek all adopt similar designs78% similarVerifiedGPT-4采用混合专家（MoE）架构，估计总参数量达1.8万亿，每次推理实际激活参数约为总量的1/877% similarVerifiedEach inference requires loading model weights into GPU memory and generating responses token by token; GPT-4-level model parameter counts are typically on the order of hundreds of billions.76% similar
Cite This Claim
Stable URI
https://kongchang.com/claim/291499API
curl https://kongchang.com/api/v1/knowledge/claims/291499MCP
get_claim(id=291499)