Unverified50% confidenceFactExact time
推理过程中动态增长的KV Cache会持续占用显存，长对话时可能突然触发OOM崩溃
1
Sources
50%
Confidence
Long-term
Relevance
8/5/2026
First Seen
Sources
Related Claims
Unverified随着对话轮次增加，每轮需携带完整历史上下文，输入token数量持续膨胀，导致推理时间呈现非线性增长77% similarUnverified在长对话中早期的错误尝试和调试过程会持续占据上下文窗口，造成上下文污染并干扰后续推理准确性76% similarUnverified在Transformer模型推理过程中，KV Cache（键值缓存）会随对话增长不断膨胀，导致注意力分数分布越来越平坦，模型难以精准聚焦当前任务相关信息76% similarUnverified上下文越长，KV Cache 占用的显存成比例增加，手动调大上下文长度需确保剩余显存充足，否则可能出现显存溢出(OOM)导致崩溃75% similarUnverified开启思考模式会带来更长的响应延迟和更高的Token消耗74% similar
Cite This Claim
Stable URI
https://kongchang.com/claim/689097API
curl https://kongchang.com/api/v1/knowledge/claims/689097MCP
get_claim(id=689097)