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加上自动生成的文字稿,一条 10~20 分钟的视频对大模型来说,就是一篇格式统一、已经分好段的长文。模型通过读标题判断大类,扫一遍文字稿理解在讲什么,再用章节时间点去对齐不同话题片段。

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In voice systems, receiving the first LLM token is the moment the entire pipeline can begin moving. The TTFT accounts for more than half of the total latency, so choosing a latency-optimised inference setup like Groq made the biggest difference. Model size also seems to matter: larger models may be required for some complex use cases, but they also impose a latency cost that's very noticeable in conversational settings. The right model depends on the job, but TTFT is the metric that actually matters.

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