REDDIT · REDDIT// 7h agoINFRASTRUCTURE

Llama.cpp shares KV cache across parallel slots

Llama.cpp's server architecture uses a single, global KV cache pool that is dynamically shared across all parallel request slots. This shared memory design enables efficient resource use and prefix caching, though it requires careful capacity planning to avoid token eviction during concurrent requests.

// ANALYSIS

The shared KV cache model in llama.cpp is a smart approach to local inference, prioritizing overall throughput and memory reuse over rigid per-user limits.

–Total context size is a shared pool, meaning one long request can consume memory needed by others, leading to older tokens being evicted.
–This architecture naturally enables prefix caching, allowing multiple requests with the same system prompt to reuse the KV cache and reduce prefill latency.
–Server operators must scale total context capacity proportionately with the number of parallel slots to ensure reliable concurrent performance.

// TAGS

llama-cppinferenceself-hostedllm

DISCOVERED

7h ago

2026-04-12

PUBLISHED

10h ago

2026-04-12

RELEVANCE

8/ 10

AUTHOR

chibop1