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SemiAnalysis· @SemiAnalysis_ · X·· 2 小时前AI 评分30
AI 导读

SemiAnalysis 在讨论中称,从个人体验看 OpenAI 模型存在"短期 token 效率"——能快速完成当前任务,但很多后续工作被跳过;相比之下 Anthropic 模型长期能构建更好、更可读的代码库,Astra 生成的部分测试则难以阅读。他认为模型本身对 token 效率的影响,比具体是谁在用更大。

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The fastest finish is not always the most efficient one.

“From personal experience trying out different models, you can definitely see token efficiency on the OpenAI side. But it’s what I like to think of as short-term token efficiency.”

“Yes, I’ll get this immediate task done, but there are so many follow-ups that Fable would have just done, and Astra might have just not done for the sake of completing the task faster.”

“In the long term, I feel like the Anthropic models build you the better codebase, and definitely a more readable one. If you read some of these Astra tests, it’s something else.”

“I think models matter quite a bit for token efficiency, over which user is actually using them.”

来源:SemiAnalysis · x.com