Unverified50% confidenceFactExact time
The MoT (Mixture of Tokens) mechanism allows the model to dynamically allocate computational resources when processing inputs of different modalities.
1
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50%
Confidence
Long-term
Relevance
9/11/2026
First Seen
Sources
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Related Claims
UnverifiedEach model invocation calculates both input tokens and output tokens simultaneously, and both together determine the cost of a single call.66% similarUnverified推理 Token（Reasoning Token）概念源自 OpenAI o 系列模型，模型在输出可见答案前会先消耗 Token 进行内部推导，这些中间步骤对用户不可见但消耗真实算力66% similarUnverifiedDuring Transformer model inference, input tokens can be processed in parallel (prefill stage), while output tokens must be generated one by one autoregressively (decode stage), causing the unit price of output tokens to typically be higher than that of input tokens.66% similarVerifiedThe token generation process of large language models is serial, based on an autoregressive mechanism, where each token's generation depends on the previous token.65% similarUnverified对于大语言模型推理，吞吐通常以 token 数为单位衡量，即 tokens/s 是评估 LLM 推理框架性能的核心指标63% similar
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