Unverified50% confidenceTradeoffExact time
RAG依赖精确的向量检索推理成本低但受限于检索质量，超长上下文窗口避免检索失配但KV缓存显存占用随上下文长度线性增长导致推理延迟和成本上升
1
Sources
50%
Confidence
Long-term
Relevance
7/19/2026
First Seen
Sources
Related Claims
Unverified超长上下文窗口的KV缓存显存占用随上下文长度线性增长，导致推理延迟和成本显著上升78% similarUnverifiedReasoning 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71% similarUnverified采样率越高、压力点越密，功耗和数据量越大，续航和实时同步稳定性越差；日常跑量分析选中等分辨率+长续航，专业步态诊断才需高密度阵列71% similarUnverified短期记忆延迟低但成本随对话轮次线性增长；长期记忆成本固定但检索引入额外延迟，且存在检索到错误记忆的风险70% similarUnverified只有在LLM推理比embedding加向量检索慢数十倍以上时，语义缓存才能同时实现降本与提速70% similar
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