Comparison
KV Cache vs Speculative Decoding
KV Cache and Speculative Decoding are both common AI/LLM terms but cover different ideas. Here is a quick side-by-side.
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.
When you would reach for Speculative Decoding
Speculative Decoding comes up when the question is fundamentally about inference.
Llama 3 70B accelerated by Llama 3 8B as draft.
Frequently asked
What is the difference between KV Cache and Speculative Decoding?
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. Speculative Decoding: Speculative decoding speeds up generation by having a small "draft" model propose several tokens, then verifying them in a single batched call to the big model.
When should I use KV Cache vs Speculative Decoding?
KV Cache is the right concept when you are focused on architecture. Speculative Decoding applies when you are focused on inference.
Are KV Cache and Speculative Decoding the same thing?
No. KV Cache is architecture; Speculative Decoding is inference. They are related but address different parts of the AI stack.