{"version":"1.0","type":"card","id":"213b3131-5c65-4733-b73d-d31de22ecee2","url":"https://stacklist.com/card/213b3131-5c65-4733-b73d-d31de22ecee2","title":"KV, Prefix, Prompt and Semantic Caching in LLMs","source_url":"https://x.com/_avichawla/status/2093265776266637739?s=12","note":"This page discusses key concepts in large language models (LLMs) including KV, prefix, prompt, and semantic caching. It provides clear explanations to help readers understand these important topics.","image":{"url":"https://ucarecdn.com/1ce94d44-7369-4f5e-82ec-efd00ff54098/","alt":"KV, Prefix, Prompt and Semantic Caching in LLMs","width":1983,"height":793},"stack":{"id":"83ceb89e-4a5a-4e29-8e12-b0030848f843","title":"AI Brains","url":"https://stacklist.com/c/technology/stack/83ceb89e-4a5a-4e29-8e12-b0030848f843"},"created_at":"2026-09-11T11:19:14.245Z","updated_at":null,"aco":{"summary":"KV, Prefix, Prompt and Semantic Caching in LLMs explains four distinct cache layers in language model inference, their trade-offs, and common problems that inhibit cache reuse. The content covers how these caching mechanisms store different objects, from attention tensors to response strings, and demonstrates their implementation with practical code examples.","tags":["kv-cache","llm-optimization","prompt-caching","semantic-cache","inference","memory-bandwidth","attention-mechanism"],"key_entities":[{"name":"Avi Chawla","type":"person","confidence":0.95},{"name":"KV cache","type":"technology","confidence":0.98},{"name":"Prefix caching","type":"technology","confidence":0.95},{"name":"Prompt caching","type":"technology","confidence":0.95},{"name":"Semantic cache","type":"technology","confidence":0.95},{"name":"transformers library","type":"technology","confidence":0.92},{"name":"DynamicCache","type":"technology","confidence":0.9},{"name":"Anthropic","type":"organization","confidence":0.88},{"name":"sentence-transformers","type":"technology","confidence":0.85},{"name":"attention-tensors","type":"concept","confidence":0.92},{"name":"causal-masking","type":"concept","confidence":0.9},{"name":"memory-bandwidth","type":"concept","confidence":0.88}],"classification":"tutorial","language":"en","confidence":0.85,"provenance":{"model":"claude-haiku-4-5","tool":"@stacklist/be@0.1.0","confidence":0.85,"timestamp":"2026-09-11T11:19:24.254Z"},"token_counts":{"approximate":5357,"cl100k":4430},"content_hash":"sha256:02def501156a9e42d4fc8efccf04a14d41ca5d91ff493e6624eed61c5e35509b","acp_version":"0.2","body_available":true,"body_tokens":5357,"visibility":"public","agent_accessible":true,"status":"final"},"_links":{"self":"/api/public/card/213b3131-5c65-4733-b73d-d31de22ecee2.json","html":"https://stacklist.com/card/213b3131-5c65-4733-b73d-d31de22ecee2","md":"/api/public/card/213b3131-5c65-4733-b73d-d31de22ecee2.md","stack_json":"/api/public/stack/83ceb89e-4a5a-4e29-8e12-b0030848f843.json"}}