Comment by bachittle
2 months ago
OpenAI definitely tarnished the name of GPT-5 by allowing these issues to occur. It's clearly a smaller model optimized for cost and speed. Compare it to GPT-4.5 which didn't have these errors but was "too expensive for them".
This is why Anthropic naming system of haiku sonnet and opus to represent size is really nice. It prevents this confusion.
> This is why Anthropic naming system of haiku sonnet and opus to represent size is really nice. It prevents this confusion.
In contrast to GPT-5, GPT-5 mini and GPT-5 nano?
I think it's a valid complaint that the naming scheme for the various GPT-4 models were very confusing. GPT-5 just launched, and doesn't (yet?) have a GPT-5 Turbo or GPT-o5 mini to muddy the waters.
In marketing, confusion is a feature, not a bug.
The problem is that GPT-5 is a smaller model than its predecessors.
But there's nothing in Claude's naming scheme stopping Claude 5 from being smaller than its predecessors.
Yeah, one of the main reasons I switched my tooling over to default to Anthropic models despite starting out with OpenAI for months prior, was because I often switch between different model sizes depending on the complexity of the prompt vs the speed I want the result.
I would frequently spend time going back to OpenAIs site to remind me of their different models. There’s no consistency there whatsoever. But with Anthropic is was easy.
If I have to spend 5 minutes picking a model then I might as well do the task myself. So Claude became a natural solution for me.
> OpenAI definitely tarnished the name of GPT-5 by allowing these issues to occur
For a certain class of customer maybe that is true.
But the reality is that the fact that this occurs is very encouraging -- they are not micro-optimizing to solve cosmetic problems that serve no functional purpose. They are instead letting these phenomena serve as external benchmarks of a sort to evaluate how well the LLM can work on tasks that are outside of its training data, and outside of what one would expect the capabilities to be.
Oh wow, I stare at those model names every day, and I only just now after reading your comment realized what “haiku”, “sonnet”, and “opus” imply about the models! Seems super obvious in retrospect but never thought about it!
I mean yeah, but to many non-native speakers, sonnet and opus don't immediately convey size or complexity of the models.
I'm a well-educated native English speaker and "haiku", "sonnet", and "opus" don't immediately make me think of their size differences.
Exactly. Doesn't mean that OpenAI has a better or worse naming. They all don't convey anything out of the gate.
4.large, 4.medium, 4.fast, 4. reasoning etc. or something similar would probably be better.
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I agree it’s not perfect. But it’s just 3 terms those non-English speakers need to learn. Which is a lot easier than having to remember every OpenAI model name and how it compares to every other one.
Sure. I wasn't arguing that OpenAI's naming is better. It is way worse. But Anthropic also doesn't have a sure-fire naming scheme there either.
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what's so wrong with: small, medium, and large?
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I think non-native speakers have the ability to remember that one word equals big and another equals medium.
If anything it's a lot less confusing that the awful naming convention from OpenAI up until 5.
How about just calling it 4.large, 4.medium, etc.? Is it that difficult?
Sure, an opus is supposed to be large, but a sonnet is not restricted in size but rather a style of poem. So sonnet and opus mean nothing when compared to each other.