OpenAI的泰德·桑德斯(Ted Sanders)对选择正确的GPT型号有一条拇指规则
OpenAI的泰德·桑德斯对新的GPT-6.1 Terra进行了分类，并解释了公司如何命名其语言模型。 桑德斯认为，模型性能是多层面的。 一个在数学上很优秀的模型不会自动擅长笑话。 尽管如此，大多数的性能差距都下降到一个变量：模型大小。 Sanders 称 OpenAI的模型名称很难简化，因为模型大小，推理努力，以及多agent系统都是独特的维度。 把它们合并成一个单一的"智商分数"会模糊细节。
而大小不能解释一切。 较新的、较小的模型通过更好的培训数据或改进的架构，可以超过较老的、较大的模型。 GPT-6.1 Terra在技术交流上可能比较大的Astra要好，在图像处理和计算机使用中大致匹配，价格要低得多，但在大多数其它领域，Sanders 称却还差。 "如果你只关心质量，就选阿斯特拉。 如果你对价格有点敏感，就选索尔。 如果你对价格很敏感，就选Terra或Luna".
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OpenAI's Ted Sanders shares a rule of thumb for picking the right GPT-model
OpenAI's Ted Sanders has categorized the new GPT-6.1 Terra and explained how the company names its language models. According to Sanders, model performance is multidimensional. A model that's great at math won't automatically be good at jokes. Still, most performance gaps come down to one variable: model size. Sanders says OpenAI's model names are difficult to simplify because model size, reasoning effort, and multi-agent systems are distinct dimensions. Combining them into a single "IQ score" would obscure details.
And size doesn't explain everything. Newer, smaller models can outperform older, larger ones through better training data or improved architectures. GPT-6.1 Terra is likely better than the larger Astra at technical communication and roughly matches it in image processing and computer use at a much lower price point, but falls short in most other areas, Sanders says. "If you care about quality only, pick Astra. If you're a bit price sensitive, pick Sol. If you're very price sensitive, pick Terra or Luna."
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