Reddit用户称本地GLM 5.3 Flash运行速度为云端4.2倍
AI 总结
一位Reddit用户使用相同的ChatGPT生成单次提示词和Zcode框架，对比Z.ai官方订阅与本地部署的GLM 5.3 Flash。云端运行耗时43分48秒，生成117,980个输出token；本地运行耗时10分24秒，生成118,173个输出token。本地配置采用两块NVIDIA RTX PRO 6000工作站版GPU、AMD 9960X Threadripper系统和128GB DDR5内存。
深度见解
这组同提示词对比为本地部署GLM 5.3 Flash可显著缩短实际运行时间提供了一个具体的用户自述数据点。不过，该测试仅来自单一用户，未经独立验证，而且原帖没有说明云端与本地配置是否采用了等效的生成参数或后端实现。
| When it comes to the value/cost of local AI, people usually only look at token savings (money) while forgetting one of the most valuable resource of yours, time. Just did a side by side comparison of GLM 5.3 flash via Z.ai's official subscription, and GLM 5.3 flash served locally. Same chatGPT generated "one shot" prompt, both using Zcode harness, and these are my stats: Source |Duration |Input Tok |Output Tok Cloud |43:48 |7,550,929 |117,980 Local |10:24 |9,744,552 |118,173 Same model, nearly identical output (~118K tokens each), but local finished 4.2× faster. Sure on paper this one simple task only saved $0.70, but the fact that you can ship 3-4x more code a day alone makes it worth it. Same reason why UPS next day air shipping costs an arm and a leg, time is money! Edit: forgot to list the setup 2 x RTX pro 6000 workstation edition AMD 9960x threadripper 128GB DDR5 Quant: https://huggingface.co/nvidia/GLM-5.3-Flash-FP4-Local submitted by /u/hyudryu [link] [comments] |
#GLM 5.3 Flash#Z.ai#Zcode#NVIDIA RTX PRO 6000 Blackwell#AMD 9960X Threadripper