Unverified50% confidenceFactExact time
The framework uses a distributed file system to build a KV cache pool with a capacity of 100,000 TB, retaining memory for three days for agent scenarios and seven days for human chat scenarios.
1
Sources
50%
Confidence
Long-term
Relevance
10/23/2026
First Seen
Sources
Related Entities
Related Claims
UnverifiedStoring the KV cache at 8-bit precision can save memory and support larger context windows; the author's daily use involves context lengths of 130,000 to 260,000.74% similarUnverifiedIn Agent workloads, the context expands from 60,000 to 400,000 tokens, and the KV cache of a single session may occupy tens of GB of GPU memory; although requests are waiting during gaps between tool calls, the cache cannot be released, further reducing the effective batch size.74% similarUnverified支持每天1亿次短链创建和100亿次重定向访问，假设每条记录500字节，5年约需900TB存储，写入约1200 QPS，读取约120K QPS73% similarUnverified以80ms为帧长，持续5分钟的对话将产生约3750帧历史上下文，每层Transformer需为每帧存储键值对，总显存占用可达数十GB72% similar
Cite This Claim
Stable URI
https://kongchang.com/claim/1088577API
curl https://kongchang.com/api/v1/knowledge/claims/1088577MCP
get_claim(id=1088577)