price discrimination. They want to capture low and high cost agent requests, and different workflows.

Seriously! Though I prefer GPT models to other frontier models, this shit is confusing. They keep changing the names of these models and they often don't communicate anything meaningful about the model itself, especially with these latest iterations. At least with "mini" and "nano" you understood they generally had differing speeds and "reasoning" capability, but what the hell do "Terra", "Sol", and "Astra" really mean? Which one of them is the effective successor to gpt-5.4-mini? It's hard to tell since the only objective information you'll get is token pricing. Is Terra less capable than Luna because it makes me think of dirt and grass? Or is Luna less powerful because the Earth is bigger than the Moon? Apparently that's the real answer. And why do I even have to think about this? And what comes after Astra? Galactica? Or will they start naming the succeeding models after different candy bars? Should I even care since a new model will get farted out mere days after I figured out what differentiated the last one?

What's unclear to me is who OpenAI thinks they're marketing to with this form of branding. These different models don't really mean all that much to the vast majority of people using their products who aren't developers, and developers aren't helped at all by the way they've been naming said models. Are they merely scared that they'll become irrelevant because Anthropic decided to give their models quirky names like "Opus" and "Fable"?

If OpenAI really wants to give their models names, they should name the generation of model and then have the different sub-models named by purpose or capability level. After all, I wouldn't use Mini for a job that Nano could easily do, and I wouldn't use Nano for a job that the full version of GPT-* necessitates. Similarly, I've had to discover exactly how Luna, Terra, and Sol are appropriate for different complexities and task types. OpenAI could help me skip a lot of those steps and just tell me what each model distillation is good for without causing me to look through their pricing page and make educated guesses. After all, shouldn't they not want me to pay attention to how much they're charging me?

All of this makes the days of frontend framework churn seem quaint and actually preferable.