Unverified50% confidenceCautionExact time
哈希路由MoE要求推理引擎和训练引擎中的哈希函数实现必须逐比特完全一致，否则会产生无法预测的数值差异
1
Sources
50%
Confidence
Long-term
Relevance
7/13/2026
First Seen
Sources
DeepSeek-V4 Flash RL Training Successfully Ported to AMD MI355X GPU: A Complete Breakdown
twitterlmsysorg7/10/2026
Related Claims
UnverifiedThe MoE architecture uses a router to dynamically select the Top-K experts for computation for each token, allowing the total parameter count to scale while keeping the number of activated parameters per inference constant.68% similarUnverifiedThe MoE architecture activates only the Top-K experts per inference, so the total parameter count far exceeds the number of parameters actually activated in a single inference.68% similarUnverifiedMoE uses a routing mechanism to let each input token dynamically select experts for processing, achieving an efficiency balance between a large total number of parameters and a small number of activated parameters.67% similarUnverifiedThe VRAM usage and inference latency of MoE architectures are calculated based on the number of activated parameters, not the total parameter count.66% similarVerified混合专家架构MoE通过稀疏激活机制，推理时只激活模型总参数的1/8至1/466% similar
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