Comparison
Context Window vs KV Cache
Context Window and KV Cache are both common AI/LLM terms but cover different ideas. Here is a quick side-by-side.
When you would reach for Context Window
Context Window comes up when the question is fundamentally about inference.
GPT-4o: 128K context.
When you would reach for KV Cache
KV Cache comes up when the question is fundamentally about architecture.
Generating a 4K-token response: the KV cache fills up to 4K entries per layer.
Frequently asked
What is the difference between Context Window and KV Cache?
Context Window: The context window is the maximum number of tokens an LLM can consider in a single call — prompt plus generated output combined. KV Cache: The KV cache stores the key and value vectors of all earlier tokens during generation so the model does not recompute them at every step. It is the main memory cost of LLM inference.
When should I use Context Window vs KV Cache?
Context Window is the right concept when you are focused on inference. KV Cache applies when you are focused on architecture.
Are Context Window and KV Cache the same thing?
No. Context Window is inference; KV Cache is architecture. They are related but address different parts of the AI stack.