Member-only story
OpenAI just released three models and named them after celestial bodies. That is not branding.
That is an inference cost architecture announcement dressed up as a product launch. Let me show you the why.
I’ve spent the last 48 hours pulling apart what these three names actually mean for anyone building production AI systems.
Luna is the small, fast model. Terra is the medium. Sol is the large, capable one.
Pretty names.
But behind them is a cost optimisation problem that any systems architect should recognise immediately — because it maps directly to the roofline model from high-performance computing, a framework that has been around since 2009.
The branding is the distraction. The math is the announcement.
Grab coffee. This is going to take a while.
— -
Chapter 1: The Roofline Model, Translated for LLMs
The roofline model asks one question: is your computation limited by how fast your hardware can do arithmetic, or by how fast it can move data?
Define arithmetic intensity I as:
I = FLOPs_executed / bytes_transferred
If I is large — you’re doing a lot of computation per byte moved — you’re compute-bound. Faster math units help you.