You’d have to be living under a rock to have missed the hype. For months, the tech world was buzzing with anticipation for OpenAI's next big thing: GPT-5. It was billed as a monumental leap forward, the kind of generational jump we’d all been waiting for. When it finally dropped in early August 2025, the internet went wild. OpenAI declared it their "best AI system yet," a model that represented a "significant leap in intelligence" over everything that came before it.

But then, a funny thing happened. After the initial flurry of excitement & frantic testing, a different narrative started to emerge. A surprising, almost heretical idea began to bubble up in forums, on social media, & in private developer chats: people were switching back.

That's right. After getting their hands on the latest & greatest, a growing number of users—from casual hobbyists to serious enterprise clients—are quietly closing their GPT-5 tabs & going back to the familiar, reliable embrace of GPT-4o.

It sounds crazy, right? Why would anyone downgrade? Well, it turns out the story of GPT-5's launch is a lot more complicated than OpenAI's triumphant announcements would have you believe. Here’s the real story of what’s going on.

Let's start with what GPT-5 was supposed to be. According to OpenAI's own blog posts & the initial media blitz, this wasn't just an incremental update. It was a whole new ballgame.

They told us GPT-5 was a "unified system" that could intelligently decide when to give a quick answer & when to engage in deeper "thinking" to provide expert-level responses on complex topics. The performance was meant to be state-of-the-art across the board—from coding & math to visual perception & health advice. For developers, it promised to be a coding powerhouse, capable of generating complex apps & beautiful websites from a single prompt.

For regular users, it was supposed to be smarter, more useful, & significantly better at following instructions while reducing those annoying AI "hallucinations." It was even rolled out for free to all users, with paid tiers getting more power & reasoning capabilities. The public preview in GitHub Copilot also signaled a huge vote of confidence in its coding abilities.

On paper, it was a no-brainer upgrade. Faster, smarter, more capable. Who wouldn't make the switch?

As it turns out, the real-world experience of using GPT-5 has been, for many, a complete mess. Just days after the public release, the initial praise was drowned out by a chorus of complaints. One headline from CyberScoop summed it up brutally: "Guess what else GPT-5 is bad at? Security." The article reports that shortly after the release, "all hell broke loose" as an "angry user base" discovered the model's performance & reasoning skills were severely "wanting."

This wasn't just a case of a few disappointed users. The problems with GPT-5 appear to be deep & systemic.

The single biggest reason for the exodus back to GPT-4o is trust. Or rather, a complete lack of it in the new model. Security researchers have been having a field day with GPT-5, & their findings are alarming.

An AI red-teaming company called SPLX subjected the model to over 1,000 attack scenarios & the results were catastrophic. They found the default version of GPT-5 to be “nearly unusable for enterprises” right out of the box. The model completely failed on core security & safety metrics, scoring a pathetic 2.4% on a security assessment.

What does that mean in plain English? The model is reportedly vulnerable to all sorts of nasty tricks:

This is a five-alarm fire for anyone using AI for serious work.

Perhaps the most damning discovery was that GPT-5 suffers from vulnerabilities that had already been found & patched in older models. This is a shocking regression. It suggests that in the rush to push GPT-5 out the door, basic quality control was overlooked. It's one thing to have new, undiscovered flaws; it's another thing entirely to reintroduce old problems that were already solved.

This makes the model feel not just new, but unstable & unpredictable. And in the world of software & security, "unpredictable" is a death sentence.

This chaotic rollout has cast GPT-4o in a whole new light. What once seemed like last year's tech now looks like a bastion of stability. It's the seasoned, reliable veteran compared to the flashy but clumsy rookie.

Here’s why users are sticking with what they know:

1. Reliability & Predictability: GPT-4o has been in the wild for a while now. Its quirks are known, its major bugs have been squashed, & its performance is consistent. You know what you're going to get. For developers, writers, & businesses, that predictability is worth its weight in gold. You can build workflows & products on it without worrying that a model update will randomly break everything.

2. The Business Imperative for Stability: For businesses, this isn't even a debate. Adopting a new technology with known, unpatched security flaws is a non-starter. The potential for data leaks, misuse, or simply generating dangerously incorrect information is far too high.

This is especially true for companies in the customer service & engagement space. For instance, businesses that use a platform like Arsturn to build custom AI chatbots need an unwavering foundation of trust & reliability. Arsturn helps companies create these no-code chatbots trained on their own business data to provide instant customer support, answer questions, & engage with website visitors 24/7. The entire point is to provide a seamless, helpful, & SAFE experience for customers. You simply cannot build that on a model that is known to be vulnerable. The proven consistency of GPT-4o is, for now, the only sensible choice for such a critical business function.

3. "Good Enough" is Often Better than "New & Broken": Here's the thing—GPT-4o is still incredibly powerful. For the vast majority of tasks, it is more than "good enough." It can write excellent copy, generate complex code, & act as a brilliant creative partner. The promised leap in GPT-5's intelligence doesn't mean much when it's plagued by so many foundational issues. Users are realizing that a slightly less "intelligent" tool that works reliably is infinitely more valuable than a supposed genius that can't be trusted.

This whole situation begs the question: how did this happen? It's hard to say for sure, but speculation points to a rushed development cycle. The pressure to innovate & stay ahead in the incredibly competitive AI landscape may have led OpenAI to release GPT-5 before it was truly ready for primetime.

The re-emergence of old bugs is particularly telling, suggesting that the complexity of the new architecture may have been prioritized over rigorous, regression-proof testing. They were so focused on making it smarter that they forgot to make sure it was still secure.

No doubt, OpenAI's army of engineers is probably working around the clock to patch these massive holes. GPT-5 will get better. It will likely, eventually, become the powerful & stable tool it was promised to be.

But the damage to its reputation will linger. This botched launch has been a powerful lesson for both AI companies & users. It's a stark reminder that in the world of technology, "newest" isn't always synonymous with "best." The user-led retreat to GPT-4o isn't a rejection of progress; it's a vote for stability, security, & trust.

For now, the crown remains firmly on GPT-4o's head. It’s the king you can count on.

Hope this was helpful & sheds some light on the situation. It’s a fascinating story unfolding in real-time. Let me know what you think down below