Conversation length changes the workload before decode begins.

As context grows, prompt processing and KV-cache pressure can change even when the model and hardware stay the same. Lizard records context tokens and includes a context bucket in comparable turn history.

That keeps a long-conversation slowdown from looking like an unexplained engine regression.

At what context length does your current local model begin to feel different?

Engineering fact: Lizard records context tokens and groups native turn history into context buckets because longer conversations change prefill and KV-cache costs.

Read the relevant Lizard page

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