# GLM-5.3 自建推理基础设施，吞吐量提升 3 倍

- 来源：Z.ai (@Zai_org)
- 发布时间：2026-09-17 15:05
- AIHOT 分数：43
- AIHOT 链接：https://aihot.news/items/cmu56rqls0fr0roqbivdu0xzx
- 原文链接：https://x.com/Zai_org/status/2100481236364079277

## AI 摘要

智谱分享 GLM-5.3 如何帮助构建并优化服务 GLM-5.3-Flash 的推理基础设施，系统从首次成功运行到生产就绪用时不到两周，端到端吞吐量相对初始基线提升 3 倍。关键在于密集反馈：本地正确性测试、执行轨迹、微基准和端到端测量，使团队能进行有针对性的假设验证，而非仅依赖聚合性能指标。

## 正文

We’re sharing how GLM-5.3 helped build and optimize the inference infrastructure serving GLM-5.3-Flash.

The system went from its first successful run to production readiness in less than two weeks, with end-to-end throughput tripling relative to the initial baseline.

The key was dense feedback: local correctness tests, execution traces, microbenchmarks, and end-to-end measurements that enabled targeted hypothesis testing rather than reliance on aggregate performance metrics alone.

https://z.ai/blog/glm-built-its-inference-infrastructure