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Quoting Ted Sanders

Summary

Ted Sanders explains OpenAI's model naming conventions: LLM performance is multidimensional, but model size explains much of the variation, and version numbers signal release order, relationships, and magnitude of improvement.

Quoting Ted Sanders
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A quote from Ted Sanders

Simon Willison’s Weblog

Newsletter

28th October 2026

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 that complexity, much of the variation in performance is explained by just a single variable: model size. In general, models that are bigger will (a) be more performant / reliable, (b) cost more per token, and (c) have better recall of esoteric facts. As you note, our models are ordered:

Luna < Terra < Sol < Astra

[...] These days, version number signifies a few things at once: the order of release, the relationship to other releases, and the magnitude of improvement. So something like 6.1 would indicate it was launched after 5.6, may share some similarities to other 6.1 models in terms of training data / personality (which is why it's not 5.7), and isn't a giant enough leap to merit the headlines and expectations that would come with a 7.

&mdash; Ted Sanders, explaining OpenAI's model naming conventions

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This is a quotation collected by Simon Willison, posted on 28th October 2026.

ai 2,300

openai 478

generative-ai 2,041

llms 2,006

gpt 135

ted-sanders 7

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Key points and analysis

Article intelligence

EngineersIntermediate

Key points

  • LLM performance is multidimensional with no fixed ordering, but model size explains much of the variation.
  • OpenAI models are ordered Luna < Terra < Sol < Astra, with bigger models being more reliable, costlier, and better at recalling esoteric facts.
  • Version numbers convey release order, relationships to other releases, and magnitude of improvement, so 6.1 is not a leap big enough to be called 7.

Highlights and analysis are generated automatically and may contain errors. Check the original source.

Quoting Ted Sanders | AI News Hub