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Ted Sanders argues that LLM version numbers now encode release order, lineage, and expected magnitude of improvement, not just a headline milestone. He also says model size is the main predictor of reliability, per-token cost, and factual recall, though performance across tasks is still uneven. For readers, this is a useful guide to decoding vendor naming schemes when comparing models, but it comes from one company's own framing and doesn't offer independent benchmarks.
Quoting Ted Sanders
In general, LLM performance is incredibly multidimensional. There's no guarantee of a fixed ordering where the model that is best at math is also the model that's best at jokes. Despite…
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