Unverified50% confidenceFactExact time
The M-series uses a hybrid architecture that retains the attention mechanism, and its inference memory is not O(1).
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50%
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Long-term
Relevance
10/19/2026
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VerifiedThe memory of LLMs depends on the context window, which is the maximum number of tokens the model can process in a single inference.66% similarUnverifiedHybrid architectures use attention in layers requiring precise matching and SSMs in layers requiring efficient sequence modeling, in order to strike a balance between inference speed and model capability.65% similarUnverifiedVSM循环将思维链推理的每一步存储到专用记忆槽中，并在继续推理前先验证：数学步骤进行真实计算校验，逻辑步骤进行基于注意力的一致性检查65% similarVerifiedThe self-attention mechanism allows the model to simultaneously reference the contextual information of all other tokens in a sequence when processing each token, rather than processing sequentially as RNNs do65% similarVerifiedState space models (SSMs) such as Mamba abandon the attention mechanism and use recurrent structures to achieve linear time complexity sequence modeling.64% similar
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