The KV cache is the stored set of attention keys and values from tokens already processed, kept so the model reuses them instead of recomputing the whole past when it drafts each new token.
Why builders care
Every active session holds its own cache, so GPU memory grows with context length times the number of concurrent sessions. Long chats, retrieval-augmented answers, and agent loops all stretch the context, and agent workloads multiply the effect because each running agent keeps a live session open. Session density, how many useful sessions fit on one card, is therefore a capacity question twice over: weights set the floor, and the KV cache sets the ceiling that moves with the workload.
KV cache quantization in plain English
KV cache quantization stores those cached keys and values in fewer bits per number, the same compact-numbers idea as weight quantization applied to memory instead of weights. For the weights side of that idea, read what quantization is. Smaller cached values mean longer contexts and more parallel sessions per card, traded against a small accuracy cost that grows if the precision is pushed too far.
A cited example
Press coverage of DeepSeek V4.1-Flash describes vendor-reported reductions in agent memory cost and more sessions fitting per GPU from its new architecture (Tech Times report). Treat those figures as vendor-reported, not independently verified: this entry cites a single secondary report, states no benchmark numbers of its own, and actual savings depend on workload, precision settings, and hardware. The durable point stands regardless of the exact ratio: shrinking per-session memory is how builders raise agent-session density.
Local relevance
On your own hardware the same tradeoff appears as context-size settings in vLLM, llama.cpp, and Ollama: larger contexts hold longer sessions but reserve more memory per slot, so the number of parallel requests you can serve drops. For the VRAM math that decides what fits, read quantized models explained, then see embeddings on consumer GPUs and what fits on a 6 GB card.