Unverified50% confidenceTradeoffExact time
推理预算越高，模型响应延迟和 Token 消耗成倍增加，但在数学证明、复杂算法设计等场景表现显著提升
1
Sources
50%
Confidence
Long-term
Relevance
7/21/2026
First Seen
Sources
Related Claims
UnverifiedReasoning Effort档位越高，模型可消耗的思考Token上限越大，但延迟和Token成本相应线性乃至超线性增长83% similarUnverified模型规模（参数量）与推理成本之间存在超线性关系，参数量翻倍会导致推理延迟与算力开销增长远超两倍78% similarUnverified随着大模型推理能力增强，单次调用消耗的token显著攀升，在固定用量限制下形成「更强模型」与「更快触及上限」的悖论75% similarUnverified增加推理次数会带来更高的计算成本，但换取了单次任务复杂度的降低，这是分组抽取策略的权衡74% similarUnverified高强度推理配置通常意味着更高费用和更长响应时间，牺牲响应速度换取逻辑严密性74% similar
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