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GPT-5 is here: what is it really worth?

Model unification, loss of control for power users and a break in trust: my take on GPT-5.

Louis Graffeuil
Founder Tandem
Updated
4 minread
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For several months, we'd been waiting for GPT-5, announced as THE new super-powerful model, bringing us closer to AGI (artificial general intelligence).

Spoiler: we're still far from it

Before sharing my disappointment, I wanted to go back 8 months, to late 2024.

At that time, the first reasoning models were starting to come out. Very powerful models, able to take time to think (reason) in order to generate more reliable answers by mobilizing more resources.

The gap between models like GPT-4 and o1 was huge in terms of performance. It gave us many more use cases (and unlocked automation cases that required fairly heavy checks).

This logic of reasoning before answering changed a lot of things, and personally, it's the type of model I was using constantly.

Screenshot: shared ChatGPT conversations are no longer indexed on Google

(Regarding the image, publicly shared ChatGPT conversations are no longer indexed on Google.)

What's new

And the big change is the unification of reasoning models with classic models. This puts an end to the explosion of models, a good thing rather than having: 4o, o1, o3, 4.1, etc.

A single model that decides How To Answer (and which tool to use)

Animation: GPT-5 decides on its own how to answer and which tool to use

On top of that, the news in bulk:

  • Access to the new models for ALL users
  • GPT-5 Auto, Fast (=gpt-4o) and Thinking (=oX)
  • GPT-4o for paying users (older model)
  • A faster, more powerful model with fewer hallucinations
  • A more “human” answer (writing) style
  • And a script execution window
“Typing Speed Race” app coded and run by GPT-5 in the ChatGPT canvas

The disappointment…

And it's precisely this approach that affects power users, those who switched between several models depending on how they wanted the model to answer.

For me, it's a huge loss of control, because the model decides on the prompt's complexity, mobilizing either the fast model (simple question) or the reasoning model (complex question).

But in some cases, I want the model to be more thorough even for a simple question. A bit like not wanting to get it wrong… But of course, that has the downside of costing more for OpenAI…

GPT-5 diagram: Auto mode switches between the fast model (Fast) and the reasoning model (Thinking)
Tip: you can explicitly ask it to “think before answering” to encourage activating the Thinking mode (reasoning)

In August 2025, I used OpenAI 90% of the time rather than another LLM, mainly because it was the most advanced ecosystem: that's where you found the best models and the latest features (deep research, ChatGPT Agent, image generation, etc.).

With every announcement, it's often spectacular. But not this time (in my case).

Even though for most users, GPT-5 will let them discover reasoning models (previously reserved for those who deliberately changed the default model), and therefore have a far better experience.

And in any case, the model is faster, and the benchmarks show it more performant.

A break in trust?

In some cases, I found myself in an embarrassing situation where the GPT-5 model was completely hallucinating on basic questions. Here's an example:

Example of GPT-5 hallucinating on a basic question

The model's error mainly came from using “.” instead of “,”. But the Thinking model was able to find the right answer.

The Thinking mode finds the right answer to the same question

Since then, this type of error has been fixed. But it has the particularity of causing a loss of trust, a constant doubt that pushes me to keep favoring the Thinking reasoning mode.

Ethan Mollick pointed out that you could have significant performance gaps in the Auto mode of GPT-5, sometimes landing on good results and sometimes on poorer ones.

Performance gaps in GPT-5's Auto mode raised by Ethan Mollick

Personalizing the models

When there's a model change like this one, what can be frustrating is the shift in writing style that can occur. Even if you can go further with custom instructions.

Custom instructions screen to adjust the model's style

Many users did it on GPT-4o to get a more personal style, in tune with their expectations.

A model change means a change in behavior.

And it can be hard to get back the style you had created, and to recover, in a way, the model that had been shaped.

Even though models don't improve the more you use them, context elements are stored in memory, letting the models retrieve certain elements when relevant.

Memory settings that store context elements across conversations

This trend of cross-chat memory + profile personalization is spreading across most vendors. Anthropic rolled it out on Claude in August 2025, and Google on Gemini the same month.

Gemini's “Personal context” settings, which draw on past chats

October 2026 update: GPT-5 has not been offered in ChatGPT since February 2026, and OpenAI launched its GPT-6 family in September 2026. To choose between ChatGPT, Claude and Gemini in 2026, I've compared AI assistants by use case.

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