Unverified50% confidenceFactExact time
After using the KV cache, single-token latency remains essentially flat and no longer grows significantly with context length, indicating that the bottleneck is no longer matrix multiplication but fixed overheads such as CPU-side scheduling, kernel launch overhead or GPU memory bandwidth.
1
Sources
50%
Confidence
Long-term
Relevance
10/18/2026
First Seen
Sources
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Related Claims
UnverifiedThe KV cache degrades the per-step matrix multiplication from large matrix times large matrix to vector times matrix, sharply reducing the amount of computation, but all cached K/V must be read in, so arithmetic intensity drops substantially and the performance bottleneck shifts from SM compute units to fixed overheads such as HBM bandwidth and kernel launches.76% similarUnverifiedTTFT is mainly determined by the prefill phase, which is the compute bottleneck and depends on GPU matrix multiplication throughput; decode speed is memory-bandwidth-bound, requiring model weights and KV cache to be moved from memory to the compute units.74% similarUnverifiedPrompt缓存（KV Cache）在相同系统提示多次使用时可复用缓存的KV矩阵，通常将延迟降低40-60%、成本降低50-90%74% similarUnverifiedKV cache runtime provides a low-cost, fine-grained, real-time intervention capability that fills the gap between model fine-tuning and external scaffolding.73% similarUnverifiedKV Cache（键值缓存）用于避免自回归生成时对历史 token 的重复计算，但长上下文场景下预填充阶段需占用大量 HBM 显存带宽，拉长首 token 延迟（TTFT）73% similar
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