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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. — Ted Sanders, explaining OpenAI's model naming conventions Recent articles - The October inflection point for vibe game development - 28th October 2026 - Battle Drones - a vibe coded RTS with audio-based multiplayer - 20th October 2026 - Hello Python 3.15, goodbye 3.10, and now I can use 3.11 - 12th October 2026 - A new feature for my blog, built using my voice - 9th October 2026
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