Unverified60% confidenceFactExact time
The KV Cache, which grows dynamically during inference, continuously occupies VRAM and may suddenly trigger an OOM crash during long conversations.
2
Sources
60%
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% similarUnverifiedThe most common problem in on-device inference is memory, as context length silently inflates the KV cache until it collides with the weights.76% similarUnverifiedIn long-context or multi-turn dialogue scenarios, the KV cache occupies a large amount of VRAM, and speed may drop off a cliff.76% similarUnverifiedThe longer the context length, the greater the KV Cache usage, and inference speed typically decreases.76% similar
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