ChatGPT o3-mini: Reasoning Models for Everyone
AI that "thinks" before answering is now available for free, the first reasoning model accessible to everyone.
Remember when I told you about ChatGPT o1, that AI model that "reasons" before answering? Until recently, this technology was only available to those paying for ChatGPT or similar services. But on January 31, 2025, OpenAI launched o3-mini, and just like that, what seemed like exclusive technology is now within everyone's reach.
What's interesting isn't just that you can now access a reasoning model without paying (which is already pretty cool), but understanding how these AIs "think" and what makes them different. As I always say, understanding how your tools work transforms how you use them 😎.
Today I want to explore what o3-mini is, how a reasoning model really works, and why it might be interesting for you (or maybe not). Don't expect miracles, but don't underestimate what these tools can do either.
Ready to dive in?
What is o3-mini?
If you read my article about ChatGPT o1, you already know that a "reasoning" model is different from common, everyday AI assistants.
Imagine this: you ask your trusted AI to help you with a difficult math problem. It will probably give you an immediate answer that seems correct... until you take a closer look and find errors. Frustrating, right?
Now, with a reasoning model like o3-mini, things change. You ask the same question and, instead of giving you an answer immediately, it "thinks" before responding: it analyzes the problem, considers different approaches, and verifies its own calculations. The result is a more reliable answer.
o3-mini is like having an assistant that:
Reasons step by step: Instead of giving immediate answers, it shows how it reaches its conclusions
Corrects its own errors: It can detect flaws in its reasoning and fix them
Helps you learn: By seeing its thought process, you also understand concepts better
And all this without having to pay for a subscription. Before, only paying users like me could use these models. Now, anyone can experiment with them 🙂.
What does this mean for you? That you can tackle more complex problems, receive clearer explanations, and trust the answers you get more (although never blindly, of course).
How does a reasoning model really work?
When I talk about an AI "reasoning," I don't mean it has suddenly become conscious and is philosophizing about the meaning of life (although who knows, maybe someday...and that's when we should start worrying about Skynet taking over!). What it really means is that the model has been trained to process information in a way that mirrors human thinking patterns.
Imagine you ask o3-mini to help you decide what type of content works best for your small business on social media.
Another assistant might respond something like:
Short videos and image posts usually generate more engagement.Sounds good, but it's generic and not personalized for your specific case.
o3-mini before answering would "reason" internally:
First, I need to know what type of business we're talking about... I don't have that info.
I should also consider the target audience, the specific platform, and the available resources.
Without this data, I can't give a truly useful recommendation.
I should ask for more information or be transparent about the limitations of my response.And it would respond something like:
To give you a truly useful recommendation, I'd need to know more about your business:
- What type of business is it?
- Who is your target audience?
- Which platforms do you have a presence on?
With this information, I can give you much more relevant and effective suggestions.The difference is that the reasoning model:
Identifies what information it's missing
Recognizes the limitations of what it can answer
Asks for details before giving recommendations
Avoids responding with generalities when asked for something specific
This internal process of "thinking before speaking" is what makes the responses from models like o3-mini more useful, especially for complex questions or those requiring deeper analysis.
What can o3-mini do for you (and what can't it do)?
With each new AI model, the question shouldn't just be "how good is it?", but "what real problems can it help me solve?"
What o3-mini does well:
Explaining complex concepts: If you've ever read an AI explanation that left you more confused than before, o3-mini can make a difference. Its step-by-step explanations help you truly understand, not just memorize.
Reviewing your work: Are you writing an important email? A report? Code? o3-mini can help you identify logic or reasoning errors you might have overlooked.
Teaching you something new: Whether it's programming, mathematics, or science, o3-mini can guide you through the learning process by showing you how to approach problems step by step, instead of just giving you the final answer.
Where not to expect miracles:
It's not an expert in everything: Although it has broad knowledge, it can make mistakes in very specialized or niche topics.
It's still an AI: No matter how convincing it sounds, it's still important to verify the information. Sometimes it tells you things with absolute certainty, and then it turns out that... well, let's just say reality disagrees completely.
What's interesting about o3-mini is that it represents an advance in how AI can help us think better. It's not about replacing our reasoning, but amplifying our own thinking process.
Is it perfect? No. Is it useful? Depends on what you need. The important thing is that now everyone can experiment with this technology and discover for themselves if they find it valuable.
How to start using o3-mini?
I bet you're wondering how you can start playing with this model. Good news - it's pretty straightforward:
If you use ChatGPT (without subscription):
Select "Reason" when you want o3-mini to think more deeply about your question
If you have ChatGPT Plus or Team:
o3-mini has replaced o1-mini in the model selector
You can now make 150 messages per day with this model (previously 50 with o1-mini)
You can also choose o3-mini-high for questions requiring deeper reasoning
If you have ChatGPT Pro:
Congratulations, you're paying a $200 monthly subscription - welcome to the millionaires club! 💰
You have unlimited access to both o3-mini and o3-mini-high
What types of questions make o3-mini really shine? Based on my experience, these areas get the best results:
Mathematical and scientific questions that require step-by-step explanations
Logical analysis of situations or arguments
Programming problems and code improvement
To squeeze the most value from o3-mini, focus on questions that need structured thinking and analysis, rather than simple fact-finding or creative writing tasks. The magic happens when you ask it to work through complex problems methodically.
What's on the horizon
OpenAI keeps rolling out products and improvements at such a pace that I can barely keep up. With the launch of o3-mini, we're seeing reasoning models become accessible to everyone, but this is just the beginning of the journey.
In the coming months, we'll likely see more advances in both the o3 model series and the GPT series (I just got my hands on the research preview of ChatGPT 4.5 – I'll share my thoughts once I've had more time to put it through its paces).
My advice? Dive into o3-mini today. Experiment with it. Test what it can do in areas you care about. There's simply no better way to understand both the potential and limitations of these tools than by experiencing them firsthand.
What about you – have you tried o3-mini yet? I'd love to hear what kinds of questions you've thrown at it and whether its answers actually helped you.
Thanks for reading!
G
Hey! I'm Germán, and I write about AI in both English and Spanish. This article was first published in Spanish in my newsletter AprendiendoIA, and I've adapted it for my English-speaking friends at My AI Journey. My mission is simple: helping you understand and leverage AI, regardless of your technical background or preferred language. See you in the next one!