Since the launch of GPT-5, a strange phenomenon has been unfolding in the AI community. Many users, from casual writers to power users, swear that GPT-4 doesn’t feel as sharp as it used to. Questions that once got detailed, nuanced answers now sometimes return vague summaries. Long-form reasoning feels less consistent. And creative prompts that once sparked brilliant outputs sometimes fall flat.
This perception has fueled countless debates on forums, social media, and even in professional AI circles: did GPT-4 actually get dumber, or are we just imagining it?
The Expectation Trap
One key factor is psychological. When GPT-5 arrived, it shifted the bar for what we consider “intelligent” machine reasoning. GPT-4, which once felt revolutionary, suddenly looked limited in comparison. This is the same phenomenon we see every year with smartphones. The iPhone 12 was cutting-edge until the 13 arrived, and now it feels dated—even though nothing changed in its hardware overnight.
Our brains recalibrate quickly. Once you’ve tasted GPT-5’s deeper contextual reasoning, broader memory handling, and faster responses, GPT-4 feels like an older generation tool. In other words, GPT-4 hasn’t necessarily declined—it’s just living in GPT-5’s shadow.
Resource Allocation and Model Downgrading
But there’s also a technical angle worth examining. Maintaining large-scale AI systems is expensive. When OpenAI launches a new model, much of the company’s engineering focus naturally shifts toward optimizing that model. GPT-5 becomes the flagship, drawing the most resources—both computational and human.
That can mean older models like GPT-4 are run in more “lightweight” configurations to save on costs and server load. We don’t know the full details of OpenAI’s internal adjustments, but there’s precedent in tech: companies often scale back support for legacy systems once a new version is out. Think of how streaming platforms reduce video quality on older devices, or how software companies gradually sunset features in older editions.
This could explain why GPT-4 feels different. It may not be “dumber” in the literal sense, but it could be running on tighter resource constraints than before.
User Trust and the Upgrade Pressure
The bigger concern here isn’t just technical—it’s about trust. If users feel that older models are being quietly weakened to nudge them toward paid upgrades or newer versions, skepticism grows. Even the perception of intentional downgrading can damage trust in AI providers.
People don’t just want innovation; they want stability. Imagine relying on GPT-4 for months in your workflow—content creation, coding, research—and suddenly finding it less reliable. That creates friction. Instead of feeling empowered by the AI, you feel cornered into switching.
A Lesson From the Software World
We’ve seen this story play out before. Microsoft, Adobe, Apple—all have faced criticism for the way they push users into newer versions by making older ones less practical. Sometimes this is inevitable: technology evolves, and old versions can’t keep up. But sometimes it’s strategic: a nudge disguised as “progress.”
With AI, the stakes are higher. These models are becoming infrastructure—the invisible engines behind industries. If people begin to see them as unstable or manipulated, adoption could slow.
So, Has GPT-4 Really Gotten Dumber?
The truth is likely a mix of perception and reality. GPT-4 hasn’t “forgotten” how to reason, but it may not be operating at the same premium configuration it once did. Combined with the psychological effect of comparing it to GPT-5, it’s easy to see why users feel let down.
And maybe that’s the bigger point. In AI, intelligence isn’t a fixed thing—it’s always relative to the newest benchmark. GPT-4 set the standard for two years. Now GPT-5 resets it. In a year or two, GPT-5 will probably feel outdated too, as GPT-6 redefines what we expect.
In the end, GPT-4 hasn’t gotten dumber—we’ve just gotten smarter about what “smart” should look like.
