The GPT-5 'Dumber' Problem: A Deep Dive into Model Routing & How to Avoid the 'Mini' Models
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Zack Saadioui
8/12/2025
The GPT-5 'Dumber' Problem: A Deep Dive into Model Routing & How to Avoid the 'Mini' Models
So, GPT-5 is finally here, & the hype was REAL. We were promised a massive leap in intelligence, coding abilities that could build apps in minutes, & a genuinely more helpful AI. But then, something weird happened. A whole bunch of people started saying it actually felt… dumber.
Yeah, you read that right. The most advanced AI model ever released, & the initial chatter was about how it was worse than its predecessor, GPT-4o. Honestly, it was a bit of a mess. People were frustrated, confused, & some were even ready to cancel their subscriptions.
Turns out, it wasn't that GPT-5 itself was dumber. The problem was way more complex & it all came down to something called "model routing." It’s a behind-the-scenes system that, when it works, is pretty clever. But when it breaks, well, you get the "dumber" GPT-5 problem.
This whole situation pulled back the curtain on how these massive AI systems actually operate. It’s not just one single, giant brain anymore. It's a whole family of models working together, & understanding how that works is now SUPER important for anyone using AI, from casual users to big businesses.
So, let's get into it. What exactly is this model routing thing, why did it cause so much trouble, & most importantly, how can you make sure you’re always using the best version of GPT-5 & not some watered-down "mini" model?
What the Heck is GPT-5 Model Routing, Anyway?
Okay, so here’s the thing: GPT-5 isn't just one model. OpenAI calls it a "unified system." Think of it less like a single, all-knowing oracle & more like a team of specialists. In the core ChatGPT product, there are two main players:
The Fast & Efficient Model: This is the workhorse. It’s designed to handle the majority of everyday questions quickly & efficiently. For most simple prompts, this is the guy you'll be talking to.
The Deep Reasoning Model (GPT-5 Thinking): This is the expert, the heavy hitter. It's brought in for the really tough problems that require complex reasoning, deep analysis, or a lot of thought.
Now, how does ChatGPT decide which specialist to send your prompt to? That's where the "real-time router" comes in. This router is like a super-smart receptionist. It instantly analyzes your request based on its complexity, the type of conversation you're having, & even your explicit instructions. If you ask for the weather, it sends you to the fast model. If you ask it to "think hard about" a complex coding problem, it's supposed to send you to the deep reasoning model.
The whole point of this system is EFFICIENCY. Running the most powerful AI model for every single query would be incredibly expensive & slow. The GPUs would probably melt! So, routing is a clever way to balance performance with cost, giving you a fast experience for simple stuff & saving the big guns for when they're really needed.
The Launch Day Fiasco: Why GPT-5 Felt 'Dumber'
So if this routing system is so smart, what went wrong? Well, on launch day, a key part of it was just… broken. Sam Altman, OpenAI's CEO, admitted that a technical problem with the "autoswitcher" (the router) was to blame for the initial poor performance.
Basically, the receptionist was having a bad day. Prompts that should have been sent to the powerful "deep thinking" model were instead being misrouted to the faster, less capable one. So, users were trying to get the AI to do complex tasks, but they were unknowingly talking to the junior assistant instead of the expert. This is why it felt "dumber" – it literally was, for those queries.
This created a massive disconnect. OpenAI was showing off benchmarks where GPT-5 was acing graduate-level science questions with 89.4% accuracy & scoring 100% on some math reasoning tests. But in the real world, users were seeing it fail at tasks that GPT-4o handled with ease. It exposed a major vulnerability in these complex, multi-model AI systems: the whole experience can fall apart not because of the core AI's intelligence, but because of the layer that's supposed to be orchestrating everything.
Meet the GPT-5 Family: It's More Than Just One or Two Models
The fast model & the deep-reasoning model are just the start. The GPT-5 ecosystem is actually a whole family of models, especially when you look at the different tiers & the API. This is where the idea of "mini models" comes into play.
Here's a breakdown of what's under the hood:
GPT-5 (Full/Pro): This is the top-tier model, the one with all the bells & whistles. It includes access to the deep reasoning mode for the most complex tasks. Pro users get even more access to its extended reasoning capabilities.
GPT-5-mini: This is a lighter, balanced version of the model. It's still very capable but designed to be faster & cheaper to run. For regular ChatGPT users (both free & Plus), this is the model you'll be automatically switched to after you hit your usage cap for the main GPT-5 model.
GPT-5-nano: This one is primarily for developers using the API. It's an ultra-low latency & super cheap model, perfect for things like interactive UI elements or quick chatbot responses where speed is EVERYTHING.
So, when people talk about avoiding the "mini model," they're usually talking about ensuring they're not getting downgraded to that lighter version in the middle of their workflow, which can definitely lead to a drop in quality.
Are You Using a 'Mini' Model Without Realizing It?
This is the million-dollar question, isn't it? Here's how it generally works for users of the ChatGPT interface:
Free Users: You get access to the main GPT-5 model, but with a usage cap. Once you hit that limit, you'll be switched over to the "lighter GPT-5-mini model."
Plus Users: You get a much higher usage limit for the main GPT-5 model, but the same principle applies. After heavy use, you can also be bumped down to the mini model.
Pro & Enterprise Users: These tiers generally offer more consistent access to the full-power models, with Pro getting dedicated access to the most powerful "GPT-5 Pro" version.
The tricky part is that this switch can be silent. One minute you're getting incredibly insightful, detailed responses, & the next, the output might feel shallow or generic. That's likely the model downgrade in action.
How to Take Back Control & Force the 'Deep Thinking' Model
Alright, enough with the problems. Let's talk solutions. While you can't just flip a switch in the regular ChatGPT interface to guarantee you're always on the most powerful model, you can DEFINITELY influence the router. Here’s how to nudge the AI in the right direction:
Just Tell It What You Want: This sounds almost too simple, but it's the most effective method. Start your prompt with phrases like:
"Think hard about this..."
"Engage deep reasoning mode for this task."
"Analyze this problem step-by-step."
By explicitly stating your intent for a complex analysis, you give the router a HUGE clue that it needs to call in the specialist.
Customize Your Instructions: This is a POWERFUL feature that a lot of people ignore. Go into your ChatGPT settings & find the "Custom Instructions" section. Here, you can give the AI standing orders for all your conversations. Tell it something like:
"Default to deep analysis & provide thorough, expert-level responses unless I specifically ask for a 'quick take' or a brief summary."
This essentially retrains the router for your specific account, making the powerful model your default instead of the other way around.
Don't Be Vague: The quality of your prompt matters more than ever. If you give a lazy, one-sentence prompt, the router is more likely to classify it as a simple query & send it to the fast, "dumber" model. If you provide detailed context, clear instructions, & a well-defined goal, the router is far more likely to recognize the complexity & route it correctly.
Watch for Broken JSON & False Claims: Some of the smaller GPT-5 variants, like GPT-5 Mini, have been known to have issues with tasks like generating reliable JSON or pretending to have used a tool when it actually didn't. If you're running into these issues, be more explicit in your prompts. Ask it to provide the JSON schema you want it to use, or demand that it show you a plan & then confirm the actions it completed against that plan.
For the Devs: A Closer Look at the GPT-5 API
For developers & businesses building on top of OpenAI's models, the situation is a bit different – and honestly, a lot better. When you use the API, you get direct control. You're not at the mercy of the ChatGPT interface's router.
You can simply choose which model you want to use for any given task:
1
gpt-5
: The full, powerful model.
1
gpt-5-mini
: The balanced, cheaper option.
1
gpt-5-nano
: The lightning-fast, low-cost choice.
This allows for a much more intentional & strategic approach. You can build a system that routes requests based on your own business logic. For example: a customer-facing chatbot could use
1
gpt-5-nano
for instant replies to common questions, then switch to
1
gpt-5-mini
for more complex summaries, & finally escalate to the full
1
gpt-5
for deep analysis of a customer's problem.
Even cooler, the API introduces a new parameter called
1
reasoning_effort
. This lets you fine-tune the model's performance, trading a bit of speed for more thorough reasoning. You can set values like
1
minimal
,
1
low
,
1
medium
, or
1
high
, giving you another layer of control over the model's output & cost.
Why This Matters for Your Business & The Case for Custom AI
Here's the bottom line: the GPT-5 routing fiasco highlights a major challenge with using these massive, one-size-fits-all AI models for professional business applications. When you need consistency, reliability, & a predictable user experience, you can't afford to have your AI assistant feel "dumber" because of some opaque, behind-the-scenes routing issue.
Your customers don't care about model routers or usage caps. They just want their questions answered quickly & accurately, every single time. This is where the idea of a custom-built AI solution becomes SO much more appealing.
Instead of relying on a general-purpose tool that's trying to be everything to everyone, businesses are increasingly looking for more focused solutions. And honestly, this is the perfect place to talk about a platform like Arsturn. The whole point of Arsturn is to put the power & control back in the hands of the business.
With Arsturn, you can build a no-code AI chatbot that's trained specifically on your own data. This is a HUGE deal. It means the chatbot knows your products, your policies, & your brand voice inside & out. You're not getting generic answers from a massive model that might have been trained on some random corner of the internet; you're getting precise, consistent information that's 100% relevant to your business.
It completely sidesteps the "mini model" problem. You build one, reliable AI assistant for your website. It's available 24/7 to provide instant customer support, answer detailed questions about your services, & even help with lead generation. You don't have to worry that it's going to get "tired" or be silently downgraded. The experience is consistent for every single website visitor.
For businesses that want to leverage the power of AI for customer engagement & automation, this is the way to go. A platform like Arsturn lets you build a meaningful connection with your audience through a personalized chatbot experience, boosting conversions & freeing up your human team to focus on more complex issues. You get the benefits of AI without the headaches of unpredictable model routing.
Wrapping It Up
The whole GPT-5 "dumber" episode was a fascinating, if frustrating, look into the future of AI. These systems are becoming incredibly complex, with layers of models & routers all working to deliver a seamless experience. As users, understanding these underlying mechanics is key to getting the most out of them.
Remember to be explicit with your prompts, use custom instructions, & if you're a developer, take advantage of the direct control the API gives you. But for businesses that need rock-solid consistency & a truly branded AI experience, it might be time to look beyond the general-purpose giants.
Hope this deep dive was helpful! It's a pretty wild time in the world of AI, & things are changing fast. Let me know what you think or if you've found any other tricks to get the best out of GPT-5.