When GPT-5 launched last week, it was promoted as a simplified “one size fits all” AI model with a built-in router that could automatically select the best way to respond to user questions. The aim was to remove the need for users to navigate a complex model picker, something the company’s CEO had previously criticised.
However, it now appears GPT-5 is not the fully unified system the company intended. In a recent post on X, the CEO revealed that ChatGPT users can now choose between three GPT-5 modes — Auto, Fast, and Thinking — directly from the model picker. The Auto mode functions like the original router, but users can bypass it to access faster or slower models themselves.
In addition, paid subscribers once again have access to older AI models, including GPT-4o, GPT-4.1, and o3, which were removed just last week. GPT-4o is now available by default, while other models can be enabled through settings. The CEO also said work is underway to update GPT-5’s personality so it feels “warmer” but “not as annoying” as GPT-4o, adding that more per-user personality customisation is a priority.
The return of multiple model options suggests that GPT-5’s router has not met all user expectations. The rollout has faced challenges, including a backlash over the removal of older models that many users had grown attached to. The CEO has promised to give more notice in future before retiring any models.
On launch day, GPT-5’s router reportedly experienced issues, leading some to believe it was less capable than earlier versions. This prompted the company’s VP of ChatGPT to note on X that while “we are not always going to get everything on try #1” the team can iterate quickly.
Routing prompts effectively requires matching AI behaviour to both the user’s preferences and the specific question, often in just a fraction of a second. Yet preferences go beyond speed, with some users favouring verbose answers and others appreciating a more contrarian tone.
Human attachment to AI models is an emerging phenomenon, illustrated by events such as a public farewell for another company’s discontinued AI. This emotional connection adds another layer of complexity to balancing performance, personality, and personalisation in AI systems.
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