English(EN) Calling Chinese LLMs from outside China: measure first, then fix latency and stability

测量并修复从全球访问中文大语言模型的延迟问题

作者 PulseAugur 编辑部 · [1 个来源] · 2026-11-02 06:08

当从中国境外访问托管在中国的大语言模型时，用户经常会遇到显著的延迟和不稳定性。这主要是由于网络拥塞以及建立连接所花费的累积时间，包括 TCP 和 TLS 握手，尤其是在每次请求都建立新连接的情况下。为了解决这些问题，首先在高峰时段从实际用户服务器测量首次字节时间 (TTFB) 和首次令牌时间 (TTFT) 等性能指标至关重要。利用流式响应并确保读取整个流直到完成也有助于减轻感知延迟并提高稳定性。 AI

影响优化跨境大语言模型访问可以改善全球人工智能部署的用户体验和应用程序性能。

排序理由该条目提供了优化大语言模型性能的技术指南和脚本，而不是宣布新模型或研究突破。

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dev.to — LLM tag TIER_1 English(EN) · lucky wang · 2026-11-02 06:08

Calling Chinese LLMs from outside China: measure first, then fix latency and stability

<p>If you call a model hosted in mainland China from a server in Europe, the Americas or Southeast Asia, you have probably seen it: the first token takes a while, some requests hang for no clear reason, and the evening hours (yours or Beijing's) are worse than the morning. The mo…

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Calling Chinese LLMs from outside China: measure first, then fix latency and stability

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