SemiAnalysis 认为，首次标记时间（TTFT）是人工智能推理中一个被高估的指标，尤其是在代理编码任务中，它可能显著影响端到端延迟。然而，他们指出，对于许多任务，特别是较长的生成任务，TTFT 与整体吞吐量和标记生成速度相比影响甚微。虽然更快的 TTFT 可以提高交互性，但用户通常更看重响应质量而非原始速度，这表明对于某些应用来说，延迟和成本之间的权衡可能是可以接受的。 AI
影响 认为 TTFT 对于许多人工智能任务来说不如吞吐量关键，这表明优化重点可能发生转变。
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The counter: 🟠 Agentic coding: TTFT is often the largest single chunk of end-to-end latency per call 🟠 5 chained calls × 200ms = 1s of pure dead wait, additive 🟠 Voice/real-time has a hard ~300ms window, autocomplete needs <200ms 🟠 Faster first-token compounds directly into …
On many tasks, TTFT barely moves the needle. 🟠 On a 5-min decode, 3s vs 4s prefill is noise; it’s tok/s as generation grows that matters. 🟠 Past ~10 tok/s you’re already beating the fastest human reading speeds (upper limit ~400 words per minute); above ~20–30, extra speed is ht…
TTFT (time-to-first-token) is one of the most-quoted latency numbers in inference. But does TTFT actually matter, or is it the most overrated metric in the stack? The real axis isn't "fast." It's interactivity (tok/s/user) vs throughput (tok/s/GPU). (1/3)🧵 https://t.co/omzTNDk0…