"I should explain that both the “python” and “python_user_visible” tools execute Python code and are stateful. The “python” tool is for internal calculations and won’t show outputs to the user, while “python_user_visible” is meant for code that users can see, like file generation and plots."
But really the most important thing, is that we as end-users cannot with any certainty know if the model used python, or didn't. That's what the alignment faking article describes.
> To avoid timeouts, try using background mode. As our most advanced reasoning model, GPT-5 pro defaults to (and only supports) reasoning.effort: high. GPT-5 pro does not support code interpreter.
You are wrong from the link you shared. It was about ChatGPT not the api.
The documentation makes it unambiguously clear that gpt 5 pro does not support code interpreter. Unless you think they secretly run it which is a conspiracy, is it enough to falsify?
> Unless you think they secretly run it which is a conspiracy
tbh this doesn't sound like a conspiracy to me at all. There's no reason why they couldn't have an internal subsystem in their product which detects math problems and hands off the token generation to an intermediate, more optimized Rust program or something, which does math on the cheap instead of burning massive amounts of GPU resources. This would just be a basic cost optimization that would make their models both more effective and cheaper. And there's no reason why they would need to document this in their API docs, because they don't document any other internal details of the model.
I'm not saying they actually do this, but I think it's totally reasonable to think that they would, and it would not surprise me at all if they did.
Let's not get hung up on the "conspiracy" thing though - the whole point is that these models are closed source and therefore we don't know what we are actually testing when we run these "experiments". It could be a pure LLM or it could be a hybrid LLM + classical reasoning system. We don't know.
“Code interpreter” is a product feature the customer can use that isn’t being discussed.
They can obviously support it internally, and the feature exists for ChatGPT, but they’re choosing not to expose that combo in the API yet because of product rollout constraints.
Alright let's say I'm wrong about the details/nuances. That's still really not the point.
The point is this:
> we as end-users cannot with any certainty know if the model used python, or didn't
These tools can and do operate in ways opposite to their specific instructions all the time. I've had models make edits to files when I wasn't in agent mode (just chat mode). Chat mode is supposedly a sandboxed environment. So how does that happen? And I am sure we've all seen models plainly disregard an instruction for one reason or another.
The models, like any other software tool, have undocumented features.
You as an end-user cannot falsify the use of a python tool regardless of what the API docs say.
