SemiAnalysis：OpenAI 与 Anthropic 模型的 token 效率之争
SemiAnalysis 指出，最快完成任务不等于最高效，OpenAI 模型呈现短期 token 效率优势，而 Anthropic 模型长期能构建更好、更可读的代码库。作者以 Astra 与 Fable 的测试代码为例，认为模型本身对 token 效率影响很大，取决于用户实际使用场景。
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