Argon 与 GPT-6 Astra 对比：标注强、预测弱
作者称在 next-action 预测基准上 OpenAI Astra 胜过 Gemini 4 Argon，但 Argon 在长程理解与标注上碾压 Astra，更适合做标注模型。
Foundational Models and Annotation Models are different. Former makes the robot work and the latter understands the data to feed into the formers training. Among frontier lab models. @OpenAI’s Astra is the superior foundational model beating @GeminiApp Argon on the next-action prediction benchmark (the foundational model benchmark) But Argon destroys Astra on truly understanding and labeling across a long horizon. Hence comparatively is a better annotation model. The takeaway here is that there isn’t just one generalizable omni-model that wins both on prediction and labeling, use cases are differentiated. Safe to say @microagi nanoannot ended up leading MicroAnnotationBench
这条是引用着另一条写的：「新基准测试：nanoannot-1 击败 Gemini 4 Argon」