inter token latency
Inference interview questions tagged inter token latency, across every topic.
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Concepts behind "inter token latency"
Concept pages for the mechanisms these questions lean on.
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Prefill Versus Decode: Two Workloads on One GPUEvery LLM request runs two different workloads: prefill processes the whole prompt in one compute-bound pass, then decode generates one token per step and is bound by weight and KV reads. Which one dominates a request decides the metric you tune, the batching policy and whether the two phases belong on the same GPU.⚛️ Inference Physics🔒 Premium
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Chunked Prefill and the Token BudgetChunked prefill splits a long prompt into pieces that ride along with decode tokens, under a per-step token budget such as vLLM's max_num_batched_tokens. The budget controls how much prompt work shares a step with decode, trading prompt progress against token gaps without guaranteeing a fixed latency.⏱️ Batching & Scheduling🔒 Premium