>The models don't get better, except when a new one is released. Their performance depends solely on the model training before release and how well you curate the context you feed it. That's it.

Not quite. The hosting side can change reasoning budgets (or re-assign what terms like "high" means), temperature and other decoding parameters, output length limits, finetune internal "hidden" prompt, latency optimizations, finetune attention algorithms, even change quantization - all still serving as the same model.

We know (or suspect) Anthropic frequently nerfs models while keeping their name and version the same.

This has absolutely nothing to do with the comment you replied to.

>The models don't get better, except when a new one is released.

My brother in Christ this entire thread is talking about the new model that was released

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